Patent Publication Number: US-2023133750-A1

Title: Video conference interruption prediction

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims the benefit of U.S. Provisional Application No. 63/274,985, filed Nov. 3, 2021, the contents of which are incorporated by reference herein. 
    
    
     TECHNICAL FIELD 
     This disclosure application relates generally to monitoring systems. 
     BACKGROUND 
     Many properties are equipped with property monitoring systems that include sensors and connected system components. Property monitoring systems can receive and analyze data from sensors throughout a property. 
     SUMMARY 
     Systems and methods for conference interruption prediction and prevention and response are disclosed. A property monitoring system can use the disclosed techniques to monitor audio and video conferences. The disclosed techniques can be used to detect and predict conference interruptions, distractions, and participant fatigue. The disclosed techniques can also be used to prevent and mitigate conference interruptions, distractions, and participant fatigue. 
     Webcams used for video conferencing can be used to monitor conference participants. Webcams are often positioned very close to the participant and are typically aimed at the participant&#39;s face. Camera images from webcams can be used to monitor participant characteristics and behavior such as eye-tracking and facial expression. Camera image data from webcams can be used to detect signs of videoconference fatigue and distraction. Based on detecting fatigue or distraction, a monitoring system can perform actions to reduce the fatigue or distraction. 
     Video conferences can be impacted by distractions from roommates, children, spouses, pets, etc. Sensors at properties where videoconferences take place can be used to predict conference interruptions. Based on predicting a conference interruption, a monitoring system can perform actions to prevent or mitigate the conference interruption. 
     In general, one innovative aspect of the subject matter described in this specification can be embodied in methods that include the actions of accessing, for a video conference in progress in an area of a property, data indicating activity at the property; predicting, using the data indicating activity at the property, that a video conference interruption is likely to occur; and in response to determining that a video conference interruption is likely to occur, performing one or more actions to reduce a likelihood that the video conference interruption will be presented during the video conference. 
     In general, one innovative aspect of the subject matter described in this specification can be embodied in methods that include the actions of accessing, for a video conference in which a user is participating, data indicating characteristics of the video conference; determining, using the characteristics of the video conference, that the user is likely experiencing fatigue during the video conference; and in response to determining that the user is likely experiencing fatigue, performing one or more actions. 
     Other implementations of this aspect include corresponding computer systems, apparatus, computer program products, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods. A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions. One or more computer programs can be configured to perform particular operations or actions by virtue of including instructions that, when executed by data processing apparatus, cause the apparatus to perform the actions. 
     The foregoing and other implementations can each optionally include one or more of the following features, alone or in combination. 
     In some implementations, the method can include accessing data indicating that the video conference is in progress in the area of the property, wherein accessing the data indicating the activity at the property is responsive to accessing the data indicating that the video conference is in progress in the area of the property. 
     In some implementations, the method can include performing the one or more actions to reduce the likelihood that the video conference interruption will be presented during the video conference including performing one or more actions that have at least a threshold likelihood of preventing the video conference interruption. 
     In some implementations, the method can include performing the one or more actions including sending an instruction to a smart device to cause the smart device to reduce the likelihood of the video conference interruption. 
     In some implementations, the method can include sending the instruction to the smart device including sending the instruction to a network connected door to cause the door to lock to reduce a likelihood of the video conference interruption. 
     In some implementations, the method can include performing the one or more actions to reduce the likelihood that the video conference interruption will be presented during the video conference including deactivating at least one sensor used for the video conference. 
     In some implementations, the method can include deactivating the at least one sensor including deactivating one of a camera or a speaker for the video conference. 
     In some implementations, the method can include predicting that the video conference interruption is likely to occur including: determining, using the data indicating activity at the property, a predicted path of a person at the property; and predicting, using the predicted path of the person at the property, that the video conference interruption is likely to occur. 
     In some implementations, the method can include performing the one or more actions to reduce the likelihood that the video conference interruption will be presented during the video conference including performing one or more actions to reduce a likelihood that the video conference interruption will be presented audibly or visibly during the video conference. 
     In some implementations, the method can include performing the one or more actions to reduce the likelihood that the video conference interruption will be presented during the video conference including: determining, for each of a plurality of actions, an action likelihood that the action will reduce the likelihood that the video conference interruption will be presented during the video conference; and selecting, using the plurality of action likelihoods, the one or more actions to perform. 
     In some implementations, the method can include determining that a user is participating in a video conference, wherein accessing the data indicating the characteristics of the video conference is responsive to determining that the user is participating in the video conference. 
     In some implementations, the method can include accessing the data indicating the characteristics of the video conference including: accessing data for at least one of video or audio for the video conference; and determining, using at least one of the video or the audio of the video conference, data indicating characteristics of the user during the video conference. 
     In some implementations, the method can accessing the data indicating the characteristics of the video conference including accessing at least one of microphone data, speaker data, or camera data for the video conference. 
     In some implementations, the method can include determining a likely source of the fatigue of the user, wherein performing the one or more actions including performing the one or more actions to mitigate the likely source of the fatigue of the user. 
     In some implementations, the method can include determining a time difference between when input data is captured for the video conference and output data is presented for the video conference; and determining whether the time difference satisfies a difference threshold, wherein: performing the one or more actions is responsive to determining that the time difference satisfies the difference threshold. 
     In some implementations, the method can include performing the one or more actions including causing a modification to the video conference in response to determining that the user is likely experiencing fatigue. 
     In some implementations, the method can include determining that a number of people participating in the video conference who are likely experiencing fatigue satisfies a threshold number, wherein: performing the one or more actions is responsive to determining that the number of people participating in the video conference who are likely experiencing fatigue satisfies the threshold number. 
     The subject matter described in this specification can be implemented in various implementations and may result in one or more of the following advantages. In some implementations, the systems and methods described in this specification can reduce computational resource usage by reducing, or eliminating, processing by a microphone, a camera, or both, of video conference interruptions that would otherwise be processed by the corresponding device. In some implementations, the systems and methods described in this specification can reduce the length of video conferences, thus reducing the amount processing used to conduct conferences. Some implementations can improve the efficacy and pleasantness of a conference by reducing fatigue and distraction; prevent embarrassing interruptions or breaches of privacy caused by unintended capture of background activities; or both. Some implementations can prevent disruption or distraction for other video conference members. 
     The details of one or more implementations of the subject matter described in this specification are set forth in the accompanying drawings and the description below. Other features, aspects, and advantages of the subject matter will become apparent from the description and the drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a diagram illustrating an example diagram illustrating an example property monitoring system for predicting and preventing conference interruptions. 
         FIGS.  2 A and  2 B  are flow diagrams illustrating an example process for predicting and preventing conference interruptions. 
         FIG.  3    is a diagram illustrating an example system for conference distraction monitoring. 
         FIG.  4    is a flow diagram illustrating an example process for predicting and preventing conference distractions. 
         FIG.  5    is a diagram illustrating an example of a property monitoring system. 
     
    
    
     Like reference numbers and designations in the various drawings indicate like elements. 
     DETAILED DESCRIPTION 
       FIG.  1    is a diagram illustrating an example property monitoring system  100  for predicting and preventing conference interruptions. The property  102  can be, for example, a school property, an office property, a residential property, a multiple dwelling unit, an apartment complex, etc. 
     The property includes a first room, e.g., office  103 , and a second room, e.g., living room  104 . A conferencer  111  is participating in a conference using computing system  120 . The conference can be a communication session using audio, video, or both. In the example of  FIG.  1   , the conferencer  111  is participating in a videoconference using audio and video. The conferencer  111  views video on a screen  118  of the computing device. The conferencer  111  listens to audio of the conference using an audio device, e.g., speakers of a headset  125 . The conferencer  111  participates in the conference by speaking into a microphone  123  of the headset  125 . Images of the user are captured by a webcam  108 . The images of the conferencer  111  are visible to participants of the conference. 
     Although shown in  FIG.  1    as being part of a headset  125 , the microphone  123  and the speakers can each be a separate device. In some examples, the microphone  123 , the speakers, or both can be integrated into the computing device, e.g., as components of a laptop computer. 
     The microphone  123  and webcam  108  can be operated by the conferencer  111 . For example, the conferencer  111  can switch the microphone  123  and/or the webcam  108  on or off by operating a switch of the headset  125  and/or a switch attached to the webcam  108 . In some examples, the conferencer  111  can switch the microphone  123  and/or the webcam  108  on and off by selecting an option on an interface displayed on the screen  118 . In some examples, the conferencer  111  can adjust settings of the webcam  108  and/or the microphone  123 . For example, the conferencer  111  can adjust a tilt or zoom of the webcam  108 , and can adjust a volume of the microphone  123 . In some examples, the computing system  120  can switch on and off the microphone  123  and/or the webcam  108 . For example, the computing device may switch off the microphone  123  and/or the webcam  108  when the conferencer  111  first joins the conference. 
     The monitoring system  100  can perform conference interruption prediction and prevention at the property  102  using sensors  140  throughout the property  102 . The sensors can include, for example, motion sensor  107  and camera  105  at the property  102 . The sensors can also include door position sensors for the doors  106 ,  128 . The door position sensors can include, for example, physical contact sensors that detect whether a door is open or shut. The sensors can also include door lock sensors that detect whether a door is locked or unlocked. 
     Conference interruption prediction and prevention can include using the sensors to monitor the activities or anomalies that are detected at the property  102 . Based on the activities detected and tracked by the sensors at the property  102 , the monitoring system  100  can perform one or more actions. The monitoring system  100  can perform actions to mitigate the interruption, to prevent the interruption, to assist the interruption, or any combination of these. 
     In some examples of the monitoring system assisting the interruption includes the monitoring system  100  predicting that a particular interruption satisfies a likelihood threshold of occurring. In response, the monitoring system  100  can determine that additional information might be necessary for the interruption, e.g., when a child is likely going to ask to watch a television show. In these examples, the monitoring system  100  can prompt the interrupter for additional information and provide the additional information to a conference participant. In this way, assisting an interruption can also potentially mitigate the interruption. 
     The system  100  can include at least one local network. The network can be any communication infrastructure that supports the electronic exchange of data between a control unit  130  and other components of the monitoring system. For example, the network may include a local area network (LAN). The network may be any one or combination of wireless or wired networks and may include any one or more of Ethernet, Bluetooth, Bluetooth LE, Z-wave, Zigbee, or Wi-Fi technologies. In some examples, the property  102  includes a network, and sensors throughout the property  102  communicate with the control unit  130  over the network. 
     The sensors can transmit the sensor data to the control unit  130  via the network. Example sensor data can include indoor and outdoor motion sensor data, images and video analysis data from security cameras, and door and window position and lock data. The control unit  130  can collect and assess the data from the sensors to monitor the conditions of the property  102 . 
     The control unit  130  may be, for example, one or more computer systems, server systems, or other computing devices that are located at or near the property  102  and that are configured to process information related to the monitoring system at the property  102 . In some implementations, the control unit  130  is a cloud computing platform. The control unit  130  can be, for example, a computer system or other electronic device configured to communicate with the sensors. The control unit  130  can also perform various management tasks and functions for the monitoring system. In some implementations, a resident, a visitor, or another user can communicate with the control unit  130  (e.g., input data, view settings, or adjust parameters) through a physical connection, such as a touch screen or keypad, through a voice interface, or over a network connection. 
     In some examples, the control unit  130  can control the microphone  123  and/or the webcam  108 . For example, the control unit  130  can transmit commands to the computing system  120 . The commands can cause the microphone  123  and/or the webcam  108  to turn on and off. The control unit  130  can communicate with the microphone  123 , the webcam  108 , or both, over the local network. 
     In some examples, the control unit  130  analyzes some or all of the sensor data. For example, the control unit  130  can analyze motion sensor data, video images, and microphone  123  data to determine the occupancy of the properties of the property  102 . The control unit  130  can also analyze sensor data to determine locations of the residents and/or other occupants within the property  102 . The control unit  130  can use the occupancy data, location data, or both, to aid in preventing a conference interruption. 
     The monitoring system  100  includes one or more sensors located at the property  102  that collect sensor data related to the property  102 . The monitoring system  100  has the ability to control various sensors and other devices on the property  102  through automation controls. The sensors of the monitoring system collect various sensor data from the property  102 . Example sensors can include cameras, motion sensors, microphones, thermometers, smoke detectors, and water meters. The sensors can also include position sensors and lock sensors for doors and windows at the property  102 . 
     An example sensor at the property  102  is a camera  105 . The camera  105  may be used to monitor people, vehicles, and animals at the property  102 . In some implementations, the camera  105  may perform video analysis on the images captured by the camera  105 . In some implementations, the camera  105  may transmit images to a control unit  130  and the control unit  130  may perform video analysis on the images. The camera  105  and/or the control unit  130  may perform video analysis on the images to detect and identify objects and/or perform facial recognition within the field of view of the camera  105 . For example, the camera  105  may detect and identify animals, vehicles, and people. 
     The camera  105  can include any type of camera. The cameras can capture images of the interior and exterior areas of the property  102 . The images can be generated from any appropriate type of light. For example, the images can be generated from any combination of visible light, IR light, or UV light. The images can also be generated from RADAR, LIDAR, and/or microwave imaging. 
     In some examples, the control unit  130  includes a property model database. The database stores a virtual property model of the property  102 . In some examples, the property model database can store virtual models of multiple properties. 
     The property model can include a two-dimensional (2D) map, a three-dimensional (3D) map, or both, of the property  102 . For example, the property model can include a floor plan of each floor of the property  102 . The property model can include a map of sensors of each of the properties of the property  102 . For example, the property model can include a position of the camera  105  indicated on the map of the property  102 . The property model can include data indicating a sensor area of each sensor. The sensor area of a sensor can include, for example, a maximum range of the sensor, a field of view of the sensor, an area or volume of the property that is within detection range of the sensor, etc. For example, the property model can include data indicating a 2D or 3D field of view of the camera  105 . The field of view of the camera  105  can be overlaid on the map of the property  102 . 
     The property model can include a map of devices at each of the properties of the property  102 . For example, the property model can include a position of doors, windows, locks, alarms, lights, speakers, etc. The property model can include, e.g., a location of the camera  105  at the property  102  and a location of the computing system  120  at the property  102 . The devices can include automated devices, e.g., devices that can be operated by the control unit  130  using automated controls. Automated devices can include, for example, the camera  105 , a warning light  124 , a door lock  126 , the microphone  123 , and the webcam  108 . 
     The property model can be generated at or after a time when the property  102  is registered with the monitoring service. For example, when a manager or owner of the property  102  registers the property  102  with the monitoring service, the manager or another user can provide information to the control unit  130  indicating a layout of the property, locations of sensors, types of sensors, etc. In some examples, the manager can provide the information to the control unit  130  through a user interface of a computing system. In some examples, the manager can provide the information to the monitoring service by recording or streaming a video walkthrough of the property  102  to the control unit  130 . 
     In some examples, the control unit  130  can update the property model over time. For example, the control unit  130  can update the property model based on sensor data  142  collected at the property  102  over time. In some examples, the control unit  130  can update the property model based on user input. As an example, a user may reposition the camera  105  at the property  102 . The control unit  130  can update the property model based on user input indicating the updated position of the camera  105 . In some cases, the control unit  130  can detect movement of the camera  105 , and can prompt the user to input an updated position of the camera  105 . In some cases, the control unit  130  can detect movement of the camera  105 , and can automatically update the position of the camera  105  in the property model based on camera images collected from the camera  105 . 
       FIG.  1    illustrates a flow of data, shown as stages (A) to (D), which can represent steps in an example process. Stages (A) to (D) may occur in the illustrated sequence, or in a sequence that is different from the illustrated sequence. For example, some of the stages may occur concurrently. 
     In the example scenario illustrated in  FIG.  1   , a conferencer  111  is participating in a conference in the office  103 . A person  110  enters the living room  104  of the property  102  through the door  106  of the property  102 . The person  110  approaches the door  128  to the office  103 . 
     In stage (A) of  FIG.  1   , the control unit  130  receives conference data from the computing device. For example, the conference system data  122  can include a status of the microphone  123 , the webcam  108 , and the speakers. The conference system data  122  can also include a status of conferencing software indicating that a conference is in progress. In some examples, the conference data can include image data captured by a camera in the office. The camera can be the webcam  108  or another camera. The image data may depict the conferencer  111  looking in the direction of the screen  118 . The image data may also include images of one or more conference participants depicted on the screen  118 . 
     The conference system data  122  can include audio data captured by a microphone in the office. The microphone can be the microphone  123  of the headset  125  or another microphone. The audio data may include audio of the conferencer  111  speaking. In some examples, the audio data may include audio of another conference participant speaking. The control unit  130  can determine, based on the conference system data  122 , that a conference is in progress in the office. 
     In some examples, based on determining that the conference is in progress in the office, the control unit  130  can monitor for possible interruptions. For example, the control unit  130  can receive and analyze sensor data  142  from sensors at the property  102  to predict interruptions. 
     In stage (B) of  FIG.  1   , sensors  140  send sensor data  142  to a control unit  130 . The control unit  130  receives the sensor data  142  from the sensors  140  at the property  102 . The sensors  140  can include, for example, motion sensors, cameras, microphones, temperature sensors, humidity sensors, door and window lock sensors, door and window position sensors, etc. 
     In the example of  FIG.  1   , the sensor data  142  includes door lock data indicating that the door  128  is unlocked and door position data indicating that the door  106  opened and shut. The sensor data also includes camera image data from camera  105 . The camera image data depicts the person  110  entering the property through the door and moving through the property towards the office  103 . In some examples, the sensor data  142  can also include results of image analysis of the images captured by the camera  105 . The results of the image analysis can indicate, for example, that the door  106  opened and shut and that the person  110  is walking across the living room  104 . 
     In some examples, cameras at the property  102  can analyze captured images, e.g., using video analytics. For example, the camera  105  can perform video analysis on the images to classify objects within the images. The cameras may identify and classify the person  110  within the images. The cameras can also perform object tracking of the person  110  as the person  110  travels across the property  102 . 
     In some examples, cameras at the property  102  can transmit image data to the control unit  130 , and the control unit  130  can perform video analysis on the image data. For example, the camera  105  can capture an image of the person  110  and transmit the image to the control unit  130 . The control unit  130  can perform video analysis in order to classify the object in the image as a person, to determine a direction of motion of the person, to perform facial recognition of the person  110 , etc. 
     The control unit  130  can track movement of objects around the property based on the sensor data. For example, the control unit can track movement of people and animals around the property. In some examples, the control unit  130  can identify people at the property  102 . For example, the control unit  130  can perform facial or voice recognition to identify a person  110  at the property and can track movements of the person  110 . In some examples, the control unit  130  can identify and/or differentiate people at the property based on characteristics of the people. For example, the control unit can determine whether the person  110  is an adult or a child based on characteristics such as the height of the person  110 . 
     The sensor data  142  can include timestamps associated with the data. The timestamps can indicate a time that the data was generated by the sensors or a time that the data was sent to the control unit. For example, the door position data can be associated with a timestamp of 1:15:30 pm. The image data including the person  110  walking through the living room  104  can be associated with a timestamp of 1:16:00 pm. 
     In some examples, the control unit  130  can send the conference system data  122 , the sensor data  142 , or both to a monitoring server over a long-range data link. The long-range data link can include any combination of wired and wireless data networks. For example, the control unit  130  can exchange information with the monitoring server through a wide-area-network (WAN), a broadband internet connection, a cellular telephony network, a wireless data network, a cable connection, a digital subscriber line (DSL), a satellite connection, or other electronic means for data transmission. In some implementations, the long-range data link between the control unit  130  and the monitoring server is a secure data link (e.g., a virtual private network) such that the data exchanged between the control unit  130  and the monitoring server is encoded to protect against interception by an adverse third party. 
     In stage (C) of  FIG.  1   , the control unit  130  assesses activities at the property  102  based on the sensor data  142 . The control unit  130  can analyze the sensor data  142  to determine conditions at the property  102 . 
     The control unit  130  can determine, based on the sensor data, that an interruption is likely to occur. For example, the control unit can determine that the person  110  is approaching the door  128  to the office, and that the door  128  is unlocked. Based on determining that the person  110  is approaching the unlocked door  128 , the control unit can predict that the person  110  is likely to interrupt the conference by entering the office  103 . 
     In some examples, the control unit  130  can determine a confidence that the interruption will occur. The control unit  130  can determine the confidence based on the sensor data. For example, the control unit  130  may determine a confidence of fifty percent that the interruption will occur based on the person  110  entering the property  102  through the door  106 . The control unit  130  may determine a higher confidence, e.g., of sixty percent, based on the person  110  approaching the door  128  to the office. 
     In some examples, the control unit  130  can predict a time that the interruption will occur. For example, the control unit  130  can determine that the person  110  entered the property  102  at 1:15:30 pm and can predict that the interruption will occur at 1:16:30 pm. 
     The control unit  130  uses the property model and the sensor data  142  to assess an interruption level of different areas of the property  102 . The control unit  130  outputs an interruption assessment to the control unit  130 . The control unit  130  determines one or more actions  152  to perform based on the predicted interruption. 
     The control unit  130  determines the interruption assessment based on the sensor data  142 . For example, the control unit  130  can receive the sensor data  142  generated from sensors at the property  102 . In response to receiving the sensor data  142  from the sensors at the property  102 , the control unit  130  can retrieve the property model of the property  102  from the property model database. The control unit  130  can map the sensor data  142  to the property model. For example, the control unit  130  can map the audio data of sensor data to the property  102 . In some examples, the control unit  130  can map the audio data of sensor data to a particular area of the property  102  based on the location of a motion sensor. For example, the control unit  130  can map motion sensor data to a particular room, floor, hallway, stairway, etc. of the property  102  based on the detection range of the motion sensor. 
     Based on the sensor data  142 , the control unit  130  can determine that an interruption exists at the property  102  and can classify the interruption. For example, based on the door  106  opening and shutting, the control unit  130  can determine that a potential interruption exists at the property  102 . In some examples, the control unit  130  can detect and classify activities using programmed rules. In some examples, the control unit  130  can detect and classify activities using machine learning algorithms. The machine learning algorithms can be trained using supervised or unsupervised methods. The control unit  130  can update machine learning parameters over time based on sensor data and interruption events detected at the property  102  and other properties. 
     In some examples, the control unit  130  can evaluate a likelihood or confidence that an interruption exists at the property  102 . The control unit  130  can update the confidence of the interruption based on additional sensor data. For example, based on the door position data indicating the door  106  opened and shut, the control unit  130  may determine a confidence of sixty percent that a potential interruption exists at the property  102 . Based on the image of the person  110  walking across the living room  104 , the control unit may determine an updated confidence of eighty percent that a potential interruption exists at the property  102 . 
     In some examples, the control unit  130  can determine the confidence that an interruption exists at the property  102  based on confidence levels of the sensor data. The control unit  130  can determine a confidence that the interruption exists at the property  102  based on a combination of confidence levels of different sensor data. The combination can include, for example, a weighted sum or a weighted average of confidence levels. 
     In stage (D) of  FIG.  1   , the control unit  130  determines to perform monitoring system actions  152  and performs the actions  152  based on detecting that an interruption is likely to occur. In some examples, the control unit  130  can perform actions based on the confidence of the interruption exceeding a threshold confidence value. For example, the threshold confidence value may be seventy percent. The control unit  130  may determine, based on the sensor data, that the confidence value of the interruption occurring is eighty percent. Based on determining that the confidence value of eighty percent exceeding the threshold confidence value of seventy percent, the control unit  130  can determine to take one or more actions. 
     The actions  152  can be performed, for example, to warn the person  110  that a conference is in progress, prevent the person  110  from entering the office, to prevent the presence of the person  110  from interrupting the conference, to warn the conferencer  111  of the predicted interruption, and/or to minimize disruption to the conference caused by the person  110 . 
     The actions can include providing a single-click shortcut option for the conferencer  111  to be able to quickly turn off both the webcam  108  and microphone  123 . This action can also include a customizable placeholder to be shown to other conference participants in place of the image of the conferencer  111 , for example, a message stating “Conferencer will return shortly.” 
     In some examples, the control unit  130  can determine that a person or animal is attempting to get the attention of the conferencer  111 . For example, the control unit  130  can determine that a person is attempting to get the attention of the conferencer  111  based on image data showing the person waving their hands, based on microphone data indicating shouting sounds, etc. In these cases, the control unit  130  can perform actions to notify the conferencer  111  of the attention seeker and can provide the conferencer  111  with a shortcut to disable the microphone  123  and webcam  108 . 
     The control unit  130  determines monitoring system actions  152  based on the predicted interruption. The control unit  130  can determine monitoring system actions  152  based on pre-programmed settings and rules. Rules and settings can be customizable and may be programmed, e.g., by an owner, resident, an installer, an operator, or another user of the monitoring system. For example, a rule may state that the control unit  130  sends a notification  154  to the conferencer  111  when a confidence of a conference interruption exceeds sixty percent. In some examples, a rule may state that the control unit  130  shuts and locks the door  128  when a confidence of a conference interruption exceeds seventy percent. 
     In some examples, the control unit  130  may be programmed to request permission from a user, e.g., conferencer  111  or person  110 , before adjusting a device at the property  102 . For example, the control unit  130  can send a command to the computing system  120  that causes the computing system  120  to display, on the screen  118 , a recommendation perform an action, and selectable options to approve or reject the recommendation. In an example, the displayed recommendation can recommend muting the microphone  123 . The displayed recommendation can include a selectable icon that, when selected by the conferencer  111 , mutes the microphone  123 . In another example, the control unit  130  can send a command that causes the computing system  120  to display a recommendation to lock the door  128 , and a selectable icon that, when selected by the conferencer  111 , locks the door  128 . In some examples, the recommendation can be displayed in a user interface including a “yes” icon and a “no” icon, where selection of the “yes” icon causes the control unit  130  to perform the recommended action, and selection of the “no” icon causes the control unit  130  not to perform the recommended action. 
     In some examples, the control unit  130  can determine one or more actions based on the predicted interruption. The bulk actions can include a pre-determined set of actions to be taken for a given interruption. For example, a first set of bulk actions may apply to a potential interruption by an adult entering the office  103 . The first set of bulk actions may include notifying the interrupting person  110 , notifying the conferencer  111 , locking the door  128 , and illuminating  144  the warning light  124 . A second set of bulk actions may apply to a potential interruption by a child entering the office. The second set of bulk actions may include notifying an adult other than the conferencer  111  and turning on a television set in the living room  104 . A third set of bulk actions may apply to a potential interruption by a person ringing the doorbell. The third set of actions can include deactivating the doorbell and/or activating a filter of the microphone  123  to filter out frequencies associated with the doorbell chime. A fourth set of actions may apply to a potential interruption by an animal. The fourth set of actions can include, for example, opening a pet door and activating a filter of the microphone  123  to filter out frequencies associated with dog barking. 
     The control unit  130  can determine monitoring system actions  152  based on the confidence of the detected interruption. The actions can include sending notifications to users. For example, at an interruption confidence of fifty percent, the control unit  130  can determine to send a notification  134  to the person  110 . At an interruption level of seventy percent, the control unit  130  can determine to send a notification  154  to the conferencer  111 . At an interruption level of seventy-five percent, the control unit  130  can determine to lock  114  the door  128  by sending a command to the door lock  126 . 
     The control unit  130  can determine monitoring system actions  152  based on tracking the person  110 . For example, the predicted interruption can include an estimated path that the person  110  has taken through the property  102 , an estimated current location of the person  110 , a predicted path of the person  110 , or any combination of these. The predicted interruption can include an estimated current location of the person  110  as being in the living room  104  of the property  102 . Based on the estimated current location of the person  110  as being in the living room  104  of the property  102 , the control unit  130  can determine monitoring system actions  152  that prevent the person  110  from entering the office  103 . The monitoring system actions  152  can include, for example, shutting the door  128 , locking the door  128 , or both. Thus, the control unit  130  can perform actions in order to prevent the interruption. 
     In some examples, the control unit  130  can perform system actions  152  that include adjusting or configuring one or more devices at the property  102 . The control unit  130  can adjust sensors and devices at the property via automation controls. 
     The control unit  130  may send a command to adjust a device at the property  102 . For example, the control unit  130  can send a command to shut and lock doors at the property  102 . In some examples, the control unit  130  can trigger an alarm or warning at the property  102 , e.g., by illuminating  144  the warning light  124 . 
     In an example scenario, a vehicle may approach the property  102 . The control unit  130  can receive camera image data indicating that the vehicle has approached the driveway and a person has exited the vehicle. The control unit  130  can perform video analysis to determine that the person is not a resident of the property  102 . The control unit  130  can determine, based on the camera image data, that the person exiting the vehicle is likely to ring the doorbell, and therefore that a potential conference interruption exists. 
     Based on determining that a potential conference interruption exists due to the likely ringing of the doorbell, the control unit  130  can perform one or more actions  152 . In some examples, the actions can include muting the doorbell or reducing the volume of the doorbell. In some examples, the actions can include disabling the doorbell chime in the office  103  while the doorbell chime remains activated in other areas of the property  102 . In some examples, the actions can include providing a notification to be displayed on the screen  118 , where the notification indicates that the doorbell is likely to be rung or that the doorbell has been rung. The notification can be displayed on the screen  118  in addition to, or instead of, activating the doorbell chime. In some examples, the control unit  130  can identify one or more occupants of the property  102  who are not participating in the conference, and can provide the doorbell notification to a mobile device associated with each of the one or more occupants, while concealing the doorbell notification from the conferencer  111 . 
     In some examples, the actions  152  can prevent the person  110  from entering the office  103 . For example, the actions can include shutting the door to the office or locking the door  128  to the office. The control unit  130  can select actions to perform based on the identity of the person  110 . For example, the control unit  130  can select a first set of actions to perform when the person  110  is an adult, and a second set of actions to perform when the person  110  is a child. As an example, the control unit  130  can select to lock the door  128  when the person  110  is an adult, and to leave the door  128  unlocked when the person  110  is a child. 
     In some examples, the control unit  130  can select actions to perform that enable other occupants of the property  102  to perform actions without assistance from the conferencer  111 . For example, the system  100  can control restrictions to certain devices, websites, television channels, etc. 
     In an example, a child may require permission of the conferencer  111  before using a tablet computer. When the conferencer  111  is engaged in a conference, the control unit  130  can provide the conferencer  111  with options on the screen  118  that enable the conferencer  111  to control permissions for the child to use the tablet computer without disrupting the conference. Similarly, the system  100  may control a lock or unlock status of a dog door. When the conferencer  111  is engaged in a conference, the control unit  130  can provide the conferencer with options on the screen  118  that enable the conferencer  111  to control the lock/unlock status of the dog door without disrupting the conference. 
     In some examples, the system can be integrated as a part of conferencing software and/or as a chatbot. When the conferencer is participating in conference through a particular conferencing application, the control unit  130  can communicate with the conferencer through the conferencing application, e.g., through a chat messaging function of the conferencing application. For example, the conferencer may receive a chat message asking permission to unlock the dog door, with options for the conferencer to respond “yes” or “no.’ 
     The actions  152  can be performed to prevent the presence of the person  110  from interrupting the conference, or to minimize disruption to the conference caused by the person  110 . For example, the actions  152  can include transmitting an instruction to the computing system  120  to adjust settings of the microphone, the camera, or both. In an example, the control unit  130  can transmit an instruction that mutes the microphone and/or turns off the camera. The control unit  130  can transmit the instruction prior to the person  110  entering the office, upon the person  110  opening the door  128 , upon the person  110  entering the office, or after the person  110  enters the office. 
     In some examples, the actions can include adjusting one or more settings of the camera, e.g., by zooming the camera in or out. For example, the actions can include zooming the camera in on the conferencer  111  to reduce the amount of background scene that is visible to the camera. In some examples, the actions can include blurring the background scene of the camera. In some examples, the actions can include panning or tilting the camera away from the door  128 . In some examples, the actions can include adjusting one or more settings of the microphone e.g., by reducing a volume of the microphone and/or by increasing background noise filtering of the microphone. 
     In some examples, the control unit  130  can select actions to perform based on the conference system data  122 . For example, the control unit  130  can determine, using the conference data, whether or not the conferencer  111  is currently speaking into the microphone. Based on determining that the conferencer  111  is speaking into the microphone, the control unit  130  can determine not to turn off the microphone, and can determine instead to increase background noise filtering of the microphone. Based on determining that the conferencer  111  is not speaking into the microphone, the control unit  130  can determine to turn off the microphone. 
     In some examples, the control unit  130  can prompt the conferencer at an earlier step with options such as “Mute Microphone,” “Snooze Prompts” and “Ignore,” and can take action automatically at a later step only if the user has not responded to the prompt. Thus, in some examples, the control unit  130  can adjust devices at the property  102  without any user action. 
     In some examples, the control unit  130  can provide recommended actions to a user, and can perform the actions upon approval by the user. For example, the control unit  130  may provide recommended actions to a user such as the manager or owner of the property, and request approval of the actions. The user may be the conferencer  111  or another person. Upon approval of the actions, the monitoring server can perform the actions  152 . In some examples, the control unit  130  can provide recommended actions to the user with a time limit. If the user does not respond to approve or deny the actions within the time limit, the control unit  130  may perform the actions  152 . 
     The actions  152  can include sending an alert to users that includes the predicted time of the interruption, and the current location, route, speed of the person  110 , and/or other information. The alert can also include details about the person  110  based on the sensor data  142 , e.g., camera images from the camera  105 . 
     In some examples, the actions  152  can signal to the person  110  that the conference is in progress in the office. For example, the actions  152  can include illuminating a warning light  124  near the door  128  to the office  103 . The warning light  124  can be, for example, a red light and/or a blinking light. In some examples, the light can illuminate text, e.g., text that reads “on air” or “conference in progress.” In some examples, the actions  152  can include broadcasting audio sounds. For example, the actions can include activating a speaker near the door  128 . The speaker can broadcast audio sounds such as a beeping sound or a voice that informs the person  110  that a conference is in progress in the office  103 . In some examples, the control unit  130  can send another notification to the person  110  when the conference is complete, indicating that the conference is complete. 
     The actions can include providing a notification  134  to a device associated with the interrupter. For example, the control unit  130  can identify the person  110  based on the sensor data, and can transmit the notification  134  to a mobile device  116  associated with the person  110 . In some examples, the control unit  130  can transmit the notification  134  to a screen or panel that is near the person  110 , e.g., a panel of the control unit  130  or a panel of an appliance. The notification  134  can include, for example, a message indicating that a conference is in progress in the office  103 . 
     The actions  152  can be performed to warn the conferencer  111  of the predicted interruption. For example, the actions  152  can include transmitting a notification  154  to the computing system  120  and/or to a mobile device associated with the conferencer  111 . The notification can include a message warning that the person  110  is approaching the door  128 . 
     The notifications  134 ,  154  can include a message stating that a conference is in progress. The control unit  130  can send the notifications  134 ,  154  to residents or occupants via, for example, a text message that the occupants can receive on a mobile device, e.g., mobile device  116 . The mobile device can be any type of data carrying computing device. For example, the mobile device can be a laptop computer, a tablet, smart watch, or a video game console, or a smart car. The control unit  130  can also send the notification to users via, for example, a telephone call. 
     Though described above as being performed by a particular component of system  100  (e.g., the control unit  130 ), any of the various control, processing, and analysis operations can be performed by the control unit  130 , the sensors  140 , or another computer system of the system  100 . For example, the control unit  130 , the sensors  140 , or another computer system such as a monitoring server can analyze the images and data from the sensors  140  to predict an interruption. Similarly, the control unit  130 , the sensors, or another computer system can control the various sensors, and/or the property automation controls, to collect data or control device operation. 
     The system  100  is an example of a system implemented as computer programs on one or more computers in one or more locations, in which the systems, components, and techniques described in this specification are implemented. The user devices mobile device  116 , computing system  120 , and others can include personal computers, mobile communication devices, and other devices that can send and receive data over a network. The network (not shown), such as a local area network (“LAN”), wide area network (“WAN”), the Internet, or a combination thereof, connects the user devices to the system  100 . The system  100  can use a single server computer or multiple server computers operating in conjunction with one another, including, for example, a set of remote computers deployed as a cloud computing service. 
     The system  100  can include several different functional components, including the control unit  130 , or the sensors  140 , or a combination of these, can include one or more data processing apparatuses, can be implemented in code, or a combination of both. For instance, each of the control unit  130 , or the sensors  140  can include one or more data processors and instructions that cause the one or more data processors to perform the operations discussed herein. 
     The various functional components of the system  100  can be installed on one or more computers as separate functional components or as different modules of a same functional component. For example, the components the control unit  130 , or the sensors  140  of the system  100  can be implemented as computer programs installed on one or more computers in one or more locations that are coupled to each through a network. In cloud-based systems for example, these components can be implemented by individual computing nodes of a distributed computing system. 
       FIG.  2 A  is a flow diagram illustrating an example process  200  for conference interruption prediction and prevention and response based on property monitoring. In some implementations, some or all of the process can be performed by a control unit, e.g., control unit  130  of the system  100 , or by another computer system located at the monitored property  102  or at another location. 
     Briefly, process  200  includes accessing, for a video conference in progress in an area of a property, data indicating activity at the property ( 202 ), predicting, using the data indicating activity at the property, that a video conference interruption is likely to occur ( 204 ), and in response to determining that a video conference interruption is likely to occur, performing one or more actions to reduce a likelihood that the video conference interruption will be presented during the video conference ( 206 ), 
     In more detail, the process  200  includes accessing, for a video conference in progress in an area of a property, data indicating activity at the property ( 202 ). For example, the control unit  130  can obtain conferencing system data  122  indicating that a video conference is in progress in the office  103  of the property  102 . The conferencing system data  122  includes data indicating that the conference application is open, the calendar status is busy, the webcam is on, the microphone is on, and the speaker is on. The conferencing system data  122  includes data indicating that the computing system  120  is located in the office  103  of the property  102 . Data indicating activity at the property can include any appropriate data. For example, the control unit  130  can obtain sensor data  142  indicating that the person  110  has entered the property  102  and is approaching the office  103 . The sensor data  142  includes data indicating that the front door sensor has detected the front door  106  opening and shutting, the office door lock sensor detects that the door  128  is unlocked, and the person  110  is approaching the office  103 . 
     The process  200  includes, predicting, using the data indicating activity at the property, that a video conference interruption is likely to occur ( 204 ). For example, based on determining that the conference is in progress in the office, and that the person  110  is approaching the office, the control unit  130  can determine that a video conference interruption is likely to occur. 
     The process  200  includes, based on determining that a video conference interruption is likely to occur, performing one or more actions to prevent the interruption ( 208 ). For example, based on determining that a video conference interruption is likely to occur, the control unit  130  can perform actions  152  to prevent the interruption. For example, the control unit  130  can perform actions of locking  114  the office door  128 , sending a notification to the conferencer  111  and/or the person  110 , and illuminating  144  the warning light  124 . 
     The order of steps in the process  200  described above is illustrative only, and  200  can be performed in different orders. For example, accessing the data indicating activity at the property ( 202 ) can occur again after predicting that the video conference interruption is likely to occur ( 204 ), after performing the one or more actions to reduce a likelihood that the video conference interruption will be presented during the video conference ( 206 ), or both. 
     In some implementations, the process  200  can include additional steps, fewer steps, or some of the steps can be divided into multiple steps. For example, the step accessing, for a video conference in progress in an area of a property, data indicating activity at the property ( 202 ) can be split into detecting a conference is occurring and detecting other activity at a property. In some examples, the process  200  can include on or more steps from the process  210 , described in more detail below. 
       FIG.  2 B  is a flow diagram illustrating an example process  210  for conference interruption prediction and prevention and response based on property monitoring. In some implementations, some or all of the process can be performed by a control unit, e.g., control unit  130  of the system  100 , or by another computer system located at the monitored property  102  or at another location. 
     Briefly, process  210  includes obtaining data indicating that a conference is in progress using one or more conferencing sensors at a property ( 212 ), obtaining data indicating activity at the property ( 214 ), based on the data indicating activity at the property, predicting that a conference interruption is likely to occur ( 216 ), and in response to determining that a conference interruption is likely to occur, deactivating at least one of the conferencing sensors ( 218 ). 
     In more detail, the process  210  includes obtaining data indicating that a conference is in progress using one or more conferencing sensors at a property ( 212 ). For example, the control unit  130  can obtain data indicating that a conference is in progress using the microphone  123  and the webcam  108 . 
     The process  210  includes obtaining data indicating activity at the property ( 214 ). For example, the control unit  130  can obtain sensor data  142  indicating activity at the property  102 . 
     The process  210  includes based on the data indicating activity at the property, predicting that a conference interruption is likely to occur ( 216 ). For example, based on the activity at the property  102 , the control unit  130  can predict that a conference interruption is likely to occur. 
     The process  210  includes, in response to determining that a conference interruption is likely to occur, deactivating at least one of the conferencing sensors ( 218 ). For example, based on determining that a conference interruption is likely to occur, the control unit  130  can deactivate at least one of the microphone  123  or the webcam  108 . 
     The order of steps in the process  210  described above is illustrative only, and  210  can be performed in different orders. For example, the obtaining the data indicating activity at the property ( 214 ) can occur before obtaining the data indicating that a conference is in progress using the one or more conferencing sensors at the property ( 212 ). 
     In some implementations, the process  210  can include additional steps, fewer steps, or some of the steps can be divided into multiple steps. For example, the step obtaining data indicating activity at the property ( 214 ), obtaining data indicating that a conference is in progress using one or more conferencing sensors at a property ( 212 ), or both, can occur again after the step predicting that a conference interruption is likely to occur ( 216 ). The step obtaining data indicating activity at the property ( 214 ) can be omitted. 
       FIG.  3    shows an example system for conference distraction monitoring. The system includes a computing system  120 . The computing device can be a computer that operates a conferencing application  310  and other applications  340 . The computing device can be, for example, a laptop computer, desktop computer, tablet, or mobile device. 
     The system  300  can monitor for conference distraction and fatigue. The system  300  includes a webcam  108 , a microphone  123 , and a speaker  133 . In some examples, the system can receive data from external sensors, such as cameras, motion sensors, and microphones. 
     The system  300  includes a distraction detector  321 . The distraction detector  321  includes a user monitor  324  and a conference monitor  322 . The user monitor  324  can monitor the user for indications of distraction. The conference monitor  322  can monitor an in-progress conference for indications of distraction and for conditions that are likely to cause user fatigue and distraction. Based on monitoring the user and monitoring the conference, the distraction detector can detect and/or predict distractions  330 . 
     The user monitor  324  can monitor behavior of the conferencer  111  using data from the webcam  108 , the microphone  123 , and the other applications  340 . In some examples, the user monitor  324  can compare user behavior to predicted user behavior. In some examples, the user monitor  324  can store data indicating a layout of the conferencer&#39;s computer workstation. The model can include, for example, a position of the webcam in relation to the screen  118  or multiple screens. The model of the computer workstation can be established upon setup of the computing device and/or can be developed over time. For example, the user monitor  324  can determine that when the conferencer  111  is engaged in a conference, the conferencer&#39;s eyes are directed at a particular location of the screen  118 . The user monitor  324  can determine that when the conferencer  111  is distracted, the conferencer&#39;s eyes are directed to the side, e.g., towards a window of the office  103 , or downwards, e.g., towards a mobile device in the conferencer&#39;s hands. 
     In some examples, the predicted user behavior can be based on a global model. For example, the user monitor  324  can store a global model that represents general user behavior when users are distracted during a conference. The user monitor  324  can refine the user behavior model over time based on observations of the conferencer  111 . The user monitor  324  can refine the user behavior model, e.g. using machine learning methods. 
     The user monitor  324  can learn to predict fatigue and distraction, e.g., based on self-reporting by the conferencer  111 . For example, the conferencing application  310  can provide periodic or end-of-meeting polling to determine a level of fatigue of the conferencer  111 . 
     The user monitor  324  can develop a fatigue detection model over time based on observed user behaviors. For example, the user monitor  324  can compare user behavior observed in the camera data  306  and microphone data  302  to reported fatigue levels of participants to identify user behaviors that cause fatigue or are correlated with increasing levels of fatigue. 
     The user monitor  324  can receive application usage data  344  from other applications  340  run by the computing system  120 . The other applications  340  can include, e.g., a web browsing application, a note-taking application, and/or other types of applications. The application usage data  344  can include, for example, data indicating the types of applications that are in use by the conferencer  111 . In some examples, the application usage data  344  can include data indicating interactions of the conferencer  111  with the other applications  340 . For example, the application usage data  344  can include data indicating whether the conferencer  111  is typing notes into the note-taking application. The user monitor  324  can determine that the conferencer  111  is engaged based on the conferencer  111  typing notes into the note-taking application. The user monitor  324  can determine a degree of relevance between subject matter of the notes being typed and the contents of the meeting as a measure of attention of the conferencer  111 . 
     The application usage data  344  can include data indicating whether the conferencer  111  is performing tasks unrelated to the conference. For example, the user monitor  324  can determine that the conferencer  111  is distracted based on the conferencer  111  using other applications  340  to perform searches in a web browser, view a social media website, watch videos, listen to music, etc. 
     The user monitor  324  can track eye movement of the user using image data from the camera. For example, the user monitor can determine a location on the screen  118  where the conferencing application is displayed. In some examples, the computing system  120  can include more than one screen. The user monitor can determine a particular screen on which the conferencing application window is displayed, and a location on the particular screen where the conferencing application window is displayed. 
     In some examples, the user monitor  324  can determine whether the conferencer  111  is making eye contact with a speaking participant of the conference. For example, the user monitor  324  can determine a window in which the speaking participant is located, and a position of the window on the screen  118 . The user monitor  324  can determine whether the conferencer&#39;s eyes are looking at the window in which the speaking participant is located. In some examples, the user monitor  324  can determine that the conferencer  111  is engaged in the conference based on the conferencer  111  looking towards the speaking participant, or looking towards the webcam  108 . The user monitor  324  may determine that the conferencer  111  is distracted based on the conferencer  111  looking away from the speaking participant and away from the webcam  108 . 
     In some examples, the webcam  108  can store data mapping an eye direction of the conferencer  111  to a location of the screen  118 . For example, upon installation of the webcam  108 , the camera can undergo a calibration phase. During the calibration phase, the webcam  108  can capture images of the conferencer  111  as the conferencer looks at different positions on the screen  118 . The webcam  108  can then store calibration data mapping images of the conferencer to the locations on the screen at which the user was looking. This can be an explicit guided calibration step or performed in the background as the conferencer is actively interacting with the interface. For example, the user monitor  324  might assume the focus of the conferencer&#39;s eyes when the conferencer  111  clicks on a target such as a button on the screen  118 . 
     In some examples, the user monitor  324  can determine whether the conferencer  111  is distracted based on determining a level of participation of the conferencer  111 . The user monitor  324  can compare the level of participation of the conferencer  111  to an expected level of participation of the conferencer. The level of participation can include, for example, an amount of time that the conferencer  111  is speaking during the conference. The user monitor  324  can determine an expected level of participation at least in part based on a number of conference participants. For a larger number of participants, the expected level of participation of the conferencer  111  may be less than for a smaller number of participants. 
     In some examples, the user monitor  324  can determine whether the conferencer  111  is distracted based on analyzing camera data  306  from the webcam  108  to perform eye analysis, including blink-rate and pupilometry. The eye analysis can include determining a frequency at which the conferencer  111  moves his or her eyes from the webcam  108  to the conference window on the screen  118 . 
     The user monitor  324  can also analyze camera data  306  to detect signs of fatigue. For example, the user monitor  324  can perform facial analysis to determine a level of attention and interest of the conferencer  111 . The user monitor  324  can also analyze the camera data  306  to perform analysis of the posture of the conferencer  111 . The user monitor  324  can detect other signs of fatigue, e.g., images of the conferencer  111  drinking coffee or rubbing eyes. 
     In some examples, the user monitor  324  can determine whether the conferencer  111  is distracted or fatigued based on analyzing microphone data  302  from the microphone  123  to perform voice analysis, including analyzing volume of speech, voice frequency, speed of speech, and/or other speech characteristics of the conferencer  111 . 
     The conference monitor  322  can monitor the conference for indications of conditions that are likely to cause distraction or fatigue. Conditions that are likely to cause distraction or fatigue can include, for example, poor video quality, poor audio quality, a lag between a speaker talking and a listener hearing the speech, a lag between audio and video of the conference, etc. The conference monitor  322  monitors the conference for indications of conditions that are likely to cause fatigue based on monitoring microphone data  302  from the microphone  123 , speaker data  304  from the speaker  133 , and camera data  306  from the webcam  108 . 
     Videoconferencing tools sometimes have audio/video synchronization problems that can cause user fatigue. The conference monitor  322  can monitor the conference for audio and video delays. For example, the conference monitor  322  can compare a time of audio input to the computing device to a time of audio output by the computing device, e.g., through the speakers. The conference monitor can determine that a condition for user fatigue exists based on a delay between the audio input and the audio output existing. In some examples, the conference monitor can determine that a condition for user fatigue exists based on a delay exceeding a threshold delay. 
     In some examples, the conference monitor  322  can compare a time of video display to a time of corresponding audio output. For example, the conference monitor can receive image data of the screen  118  and audio data representing audio output by the speakers. The conference monitor can compare a time of video output on the screen  118  to a time of corresponding audio output by the speakers  133 . Corresponding audio and video can be, for example, audio and video that are received by the computing device at the same time and/or audio and video having a same timestamp. The conference monitor can determine that a condition for user fatigue exists based on a delay between the audio and video of the conference. In some examples, the conference monitor can determine that a condition for user fatigue exists based on a delay exceeding a threshold delay. 
     In some examples, the conference monitor  322  can monitor the conference for signs of delays between a first participant speaking and second participant hearing the speech. Signs of delays can include overtalk or crosstalk between multiple participants. Signs of delays can also include participants beginning to speak and then stopping. The conference monitor  322  can monitor for delays based on microphone data  302  from the microphone  123  and speaker data  304  from the speaker  133 . 
     The conference monitor  322  can also monitor for indications of conditions that are likely to cause fatigue based on monitoring application usage data  344  from other applications  340 . For example, the other applications  340  can include a calendar application. The conference monitor  322  can determine, based on application usage data  344  from the calendar application, a conference schedule for the conferencer  111 . The conference monitor  322  may predict  320  a distraction based on a number of conferences or a frequency of conferences scheduled in the calendar application. 
     The conference monitor  322  can learn to predict fatigue and distraction, e.g., based on self-reporting by the conferencer  111  and other conference participants. For example, the conferencing application  310  can provide periodic or end-of-meeting polling to determine a level of fatigue of the conference participants. 
     The conference monitor  322  can develop a fatigue detection model over time based on observed conference conditions and behaviors. For example, the conference monitor  322  can compare conference conditions to reported fatigue levels of participants to identify conference conditions that cause fatigue. 
     The system  300  can perform one or more actions based on predicting  330  user fatigue or distraction. The computing system  120  can include a communication module  332 . The communication module  332  can communicate internally, e.g., with the conferencing application  310 . The communication module  332  can communicate externally, e.g., with the control unit  130 , with the mobile device  316 , and/or with devices at the property  102  such as a light  334 . 
     The distraction detector  321  outputs an indication of a detected or predicted distraction  330  to the communication module  332 . Based on receiving the indication of the detected or predicted distraction, the communication module  332  can communicate with devices and applications in order to perform actions to prevent or mitigate the detected fatigue. 
     In some examples, the actions can be performed to attract the attention of the user to the conference. For example, the actions can include displaying a notification on the screen  118  and/or on a display of a mobile device  316  associated with the conferencer  111 . In some examples, the notification can include text asking the user if he or she is distracted, or reminding the user to pay attention to the conference. In some examples, the actions include flashing a light or sound to attract the attention of the user. For example, the screen can display a flashing light, the speakers  133  can broadcast an alert sound while the microphone  123  is temporarily muted, or both. In some examples, based on the distraction detector  321  detecting fatigue, the conferencing application  310  can offer 5-minute “pay attention” reminders until the end of the conference. 
     In some examples, the communication module can output an internal notification  335  to the conferencing application  310 . The internal notification  335  can include a message that fatigue is detected or predicted. Based on receiving the internal notification  335 , the conferencing application  310  can perform an operation to prevent the fatigue or to draw the attention of the conferencer  111  to the conference. For example, the conferencing application  310  can present a notification to the conferencer  111 , e.g., by displaying the notification on the screen  118 . 
     In some examples, the conferencing application  310  can suggest a break in the conference. In some examples, the conferencing application  310  can deactivate the microphone  123 , the webcam  108 , or both. In some examples, the conferencing application  310  can deactivate the video view for the conferencer  111  or for all participants, e.g., switching the conference from a video conference to an audio-only conference. 
     In some examples, the conferencing application  310  can propose a conference modification to a conference leader before making modifications to the conference. For example, the conferencing application  310  can present a proposal to the conference leader that suggests taking a break or suggests switching to an audio-only conference. The conferencing application  310  can provide a selectable option that allows the conference leader to authorize the conference modification or to reject the conference modification. 
     In some examples, based on the distraction detector detecting fatigue, the conferencing application  310  can offer a voting process to determine a number of participants that would like to take a break. In some examples, the conferencing application can use weighted voting. For example, each participant&#39;s conferencing application can present a report indicating an amount of fatigue from the participants, and the conference leader can determine whether a break is necessary. 
     Both the voting process and the conference analysis can be anonymized such that participants who are distracted or fatigued are not identified. The conferencing application can inject random data, votes, or results into the mix in order to avoid direct correlations of results to certain participants. Since the conferencing application is monitoring the conference and conversation cadence, the conferencing application can time breaks or break suggestions with pauses in the discussion. Likewise, the conferencing application can wait until a participant is finished speaking before turning off their webcam or muting their mic. 
     In some examples, the communication module  332  can output an external notification  336 . The external notification  336  can be output to a device such as the mobile device  316  associated with the conferencer  111 . The external notification can include, for example, a flashing light or a text notification reminding the conferencer  111  to pay attention to the conferencer. In some example, the user monitor  324  may determine that the conferencer  111  is distracted by the mobile device  316 . In these examples, the external notification  336  can disable the mobile device  316  or can disable a subset of application on the mobile device, e.g., social media or entertainment applications. 
     The actions can include adjusting one or more devices at the property. For example, the computing device can communicate with devices such as lighting and speakers located at the property. In an example, the computing device can transmit an instruction to a light  334  that causes the light  334  to turn on or to increase a brightness level. In some examples, the computing system  120  can transmit an instruction to a speaker that causes the speaker to broadcast a sound to attract the attention of the user. 
     In some examples, the communication module  332  can output a device adjustment  342  that causes an adjustment to one or more devices at the property  102 . In some examples, the communication module  332  can output a message to the control unit  130 , and the control unit  130  can perform the device adjustment  342 . 
     The device adjustment  342  can include, for example, adjusting one or more devices such as a light  334 . The device adjustment  342  can include increasing brightness of the light  334 . In some examples, the device adjustment  342  can include decreasing brightness of the light  334  or turning on or off the light. In some examples, the device adjustment  342  can include adjusting a thermostat. For example, the device adjustment  342  can include reducing temperature of the office  103  by lowering a thermostat. 
     In the example of  FIG.  3   , the computing system  120  performs actions of turning off the microphone and the camera, sending a notification to the mobile device  316 , and sending a command to the light  334  to turn the light  334  on. The actions also include adjusting the microphone  123  and the webcam  108 . For example, based on determining that the conferencer  111  is distracted or fatigued, the actions can include turning off the microphone  123 , turning off the webcam  108 , or both. 
     In some examples, the actions may be overridden by the conferencer  111  after the actions are performed. In these examples, the computing system  120  can detect that the action was overridden and determine that the action was unnecessary or unwanted. The computing system  120  can therefore avoid taking the same action in the future, and/or the computing system can update its model of indications that the conferencer  111  was truly fatigued. The timing of overriding the action can be taken into account. For example, in determining that the action was unwanted, the conferencer  111  immediately raising the thermostat could be weighted more heavily than the conferencer  111  raising the thermostat twenty minutes after the action was taken to lower the thermostat. 
     In some examples, the conferencer  111  can be presented with controls and feedback options to assist the computing system  120  with learning when the conferencer  111  is fatigued or distracted. For example, the conferencer  111  can provide feedback indicating that the conferencer  111  was not tired prior to the action of increasing brightness of the light  334 . In another example, the conferencer  111  can provide feedback indicating that the conferencer  111  was tired prior to the action of increasing brightness of the light  334 , but that the increased brightness level of the light  334  was too bright. 
     The system  300  is an example of a system implemented as computer programs on one or more computers in one or more locations, in which the systems, components, and techniques described in this specification are implemented. The user devices mobile device  316 , computing system  120 , and others can include personal computers, mobile communication devices, and other devices that can send and receive data over a network. The network (not shown), such as a local area network (“LAN”), wide area network (“WAN”), the Internet, or a combination thereof, connects the user devices to the system  300 . The system  300  can use a single server computer or multiple server computers operating in conjunction with one another, including, for example, a set of remote computers deployed as a cloud computing service. 
     The system  300  can include several different functional components, including the distraction detector  321 , the communication module  332 , the conference application  310 , and the other applications  340 . The distraction detector  321 , the communication module  332 , the conference application  310 , the other applications  340 , or a combination of these, can include one or more data processing apparatuses, can be implemented in code, or a combination of both. For instance, each of the distraction detector  321  and the communication module  332  can include one or more data processors and instructions that cause the one or more data processors to perform the operations discussed herein. 
     The various functional components of the system  300  can be installed on one or more computers as separate functional components or as different modules of a same functional component. For example, the components distraction detector  321  and the communication module  332  of the system  300  can be implemented as computer programs installed on one or more computers in one or more locations that are coupled to each through a network. In cloud-based systems for example, these components can be implemented by individual computing nodes of a distributed computing system. 
       FIG.  4    is a flow diagram illustrating an example process  400  for conference distraction detection and mitigation and response based on property monitoring. In some implementations, some or all of the process can be performed by a control unit, e.g., control unit  130  of the system  100 , or by another computer system located at the monitored property  102  or at another location. 
     Briefly, process  400  includes determining that a user is participating in a video conference ( 402 ), obtaining data indicating characteristics of the video conference ( 404 ), obtaining data indicating characteristics of the user during the video conference ( 406 ), using at least one of the characteristics of the video conference or the characteristics of the user during the video conference, determining that the user is likely experiencing fatigue during the video conference ( 408 ), and in response to determining that the user is likely experiencing fatigue, performing one or more actions ( 410 ). 
     In more detail, the process  400  includes determining that a user is participating in a video conference ( 402 ). For example, the computing system  120  can determine that the conferencer  111  is participating in a video conference using the conferencing application  310 , the microphone  123 , the screen  118 , and the webcam  108 . 
     The process  400  includes obtaining data indicating characteristics of the video conference ( 404 ). For example, the conference monitor  322  of the computing system  120  can obtain microphone data  302 , speaker data  304 , and camera data  306  indicating characteristics of the video conference. 
     The process  400  includes obtaining data indicating characteristics of the user during the video conference ( 406 ). For example, the user monitor  324  can obtain microphone data  302 , camera data  306 , and application usage data  344  indicating characteristics of the conferencer  111  during the video conference. 
     The process  400  includes, using at least one of the characteristics of the video conference or the characteristics of the user during the video conference, determining that the user is likely experiencing fatigue during the video conference ( 408 ). For example, based on the characteristics of the conference or the characteristics of the conferencer  111 , the distraction detector can determine that the conferencer  111  is likely experiencing fatigue. 
     The process  400  includes in response to determining that the user is likely experiencing fatigue, performing one or more actions ( 410 ). For example, based on determining that the conferencer is likely experiencing fatigue, the communication module  332  can output at least one of an internal notification  335 , an external notification  336 , or a device adjustment  342 . 
     The order of steps in the process  400  described above is illustrative only, and  400  can be performed in different orders. For example, the determining that a user is participating in a video conference ( 402 ), obtaining data indicating characteristics of the video conference ( 404 ), and obtaining data indicating characteristics of the user during the video conference ( 406 ) can be performed in various orders. 
     In some implementations, the process  400  can include additional steps, fewer steps, or some of the steps can be divided into multiple steps. For example, the obtaining data indicating characteristics of the video conference ( 404 ) or obtaining data indicating characteristics of the user during the video conference ( 406 ), or both, can be omitted. 
       FIG.  5    is a diagram illustrating an example of a home monitoring system  500 . The monitoring system  500  includes a network  505 , a control unit  510 , one or more user devices  540  and  550 , a monitoring server  560 , and a central alarm station server  570 . In some examples, the network  505  facilitates communications between the control unit  510 , the one or more user devices  540  and  550 , the monitoring server  560 , and the central alarm station server  570 . 
     The network  505  is configured to enable exchange of electronic communications between devices connected to the network  505 . For example, the network  505  may be configured to enable exchange of electronic communications between the control unit  510 , the one or more user devices  540  and  550 , the monitoring server  560 , and the central alarm station server  570 . The network  505  may include, for example, one or more of the Internet, Wide Area Networks (WANs), Local Area Networks (LANs), analog or digital wired and wireless telephone networks (e.g., a public switched telephone network (PSTN), Integrated Services Digital Network (ISDN), a cellular network, and Digital Subscriber Line (DSL)), radio, television, cable, satellite, or any other delivery or tunneling mechanism for carrying data. Network  505  may include multiple networks or subnetworks, each of which may include, for example, a wired or wireless data pathway. The network  505  may include a circuit-switched network, a packet-switched data network, or any other network able to carry electronic communications (e.g., data or voice communications). For example, the network  505  may include networks based on the Internet protocol (IP), asynchronous transfer mode (ATM), the PSTN, packet-switched networks based on IP, X.25, or Frame Relay, or other comparable technologies and may support voice using, for example, VoIP, or other comparable protocols used for voice communications. The network  505  may include one or more networks that include wireless data channels and wireless voice channels. The network  505  may be a wireless network, a broadband network, or a combination of networks including a wireless network and a broadband network. 
     The control unit  510  includes a controller  512  and a network module  514 . The controller  512  is configured to control a control unit monitoring system (e.g., a control unit system) that includes the control unit  510 . In some examples, the controller  512  may include a processor or other control circuitry configured to execute instructions of a program that controls operation of a control unit system. In these examples, the controller  512  may be configured to receive input from sensors, flow meters, or other devices included in the control unit system and control operations of devices included in the household (e.g., speakers, lights, doors, etc.). For example, the controller  512  may be configured to control operation of the network module  514  included in the control unit  510 . 
     The network module  514  is a communication device configured to exchange communications over the network  505 . The network module  514  may be a wireless communication module configured to exchange wireless communications over the network  505 . For example, the network module  514  may be a wireless communication device configured to exchange communications over a wireless data channel and a wireless voice channel. In this example, the network module  514  may transmit alarm data over a wireless data channel and establish a two-way voice communication session over a wireless voice channel. The wireless communication device may include one or more of a LTE module, a GSM module, a radio modem, cellular transmission module, or any type of module configured to exchange communications in one of the following formats: LTE, GSM or GPRS, CDMA, EDGE or EGPRS, EV-DO or EVDO, UMTS, or IP. 
     The network module  514  also may be a wired communication module configured to exchange communications over the network  505  using a wired connection. For instance, the network module  514  may be a modem, a network interface card, or another type of network interface device. The network module  514  may be an Ethernet network card configured to enable the control unit  510  to communicate over a local area network and/or the Internet. The network module  514  also may be a voice band modem configured to enable the alarm panel to communicate over the telephone lines of Plain Old Telephone Systems (POTS). 
     The control unit system that includes the control unit  510  includes one or more sensors. For example, the monitoring system may include multiple sensors  520 . The sensors  520  may include a lock sensor, a contact sensor, a motion sensor, or any other type of sensor included in a control unit system. The sensors  520  also may include an environmental sensor, such as a temperature sensor, a water sensor, a rain sensor, a wind sensor, a light sensor, a smoke detector, a carbon monoxide detector, an air quality sensor, etc. The sensors  520  further may include a health monitoring sensor, such as a prescription bottle sensor that monitors taking of prescriptions, a blood pressure sensor, a blood sugar sensor, a bed mat configured to sense presence of liquid (e.g., bodily fluids) on the bed mat, etc. In some examples, the health-monitoring sensor can be a wearable sensor that attaches to a user in the home. The health-monitoring sensor can collect various health data, including pulse, heart rate, respiration rate, sugar or glucose level, bodily temperature, or motion data. 
     The sensors  520  can also include a radio-frequency identification (RFID) sensor that identifies a particular article that includes a pre-assigned RFID tag. 
     The control unit  510  communicates with the home automation controls  522  and a camera  530  to perform monitoring. The home automation controls  522  are connected to one or more devices that enable automation of actions in the home. For instance, the home automation controls  522  may be connected to one or more lighting systems and may be configured to control operation of the one or more lighting systems. In addition, the home automation controls  522  may be connected to one or more electronic locks at the home and may be configured to control operation of the one or more electronic locks (e.g., control Z-Wave locks using wireless communications in the Z-Wave protocol). Further, the home automation controls  522  may be connected to one or more appliances at the home and may be configured to control operation of the one or more appliances. The home automation controls  522  may include multiple modules that are each specific to the type of device being controlled in an automated manner. The home automation controls  522  may control the one or more devices based on commands received from the control unit  510 . For instance, the home automation controls  522  may cause a lighting system to illuminate an area to provide a better image of the area when captured by a camera  530 . 
     The camera  530  may be a video/photographic camera or other type of optical sensing device configured to capture images. For instance, the camera  530  may be configured to capture images of an area within a building or home monitored by the control unit  510 . The camera  530  may be configured to capture single, static images of the area and also video images of the area in which multiple images of the area are captured at a relatively high frequency (e.g., thirty images per second). The camera  530  may be controlled based on commands received from the control unit  510 . 
     The camera  530  may be triggered by several different types of techniques. For instance, a Passive Infra-Red (PIR) motion sensor may be built into the camera  530  and used to trigger the camera  530  to capture one or more images when motion is detected. The camera  530  also may include a microwave motion sensor built into the camera and used to trigger the camera  530  to capture one or more images when motion is detected. The camera  530  may have a “normally open” or “normally closed” digital input that can trigger capture of one or more images when external sensors (e.g., the sensors  520 , PIR, door/window, etc.) detect motion or other events. In some implementations, the camera  530  receives a command to capture an image when external devices detect motion or another potential alarm event. The camera  530  may receive the command from the controller  512  or directly from one of the sensors  520 . 
     In some examples, the camera  530  triggers integrated or external illuminators (e.g., Infra-Red, Z-wave controlled “white” lights, lights controlled by the home automation controls  522 , etc.) to improve image quality when the scene is dark. An integrated or separate light sensor may be used to determine if illumination is desired and may result in increased image quality. 
     The camera  530  may be programmed with any combination of time/day schedules, system “arming state”, or other variables to determine whether images should be captured or not when triggers occur. The camera  530  may enter a low-power mode when not capturing images. In this case, the camera  530  may wake periodically to check for inbound messages from the controller  512 . The camera  530  may be powered by internal, replaceable batteries if located remotely from the control unit  510 . The camera  530  may employ a small solar cell to recharge the battery when light is available. Alternatively, the camera  530  may be powered by the controller&#39;s  512  power supply if the camera  530  is co-located with the controller  512 . 
     In some implementations, the camera  530  communicates directly with the monitoring server  560  over the Internet. In these implementations, image data captured by the camera  530  does not pass through the control unit  510  and the camera  530  receives commands related to operation from the monitoring server  560 . 
     The system  500  also includes thermostat  534  to perform dynamic environmental control at the home. The thermostat  534  is configured to monitor temperature and/or energy consumption of an HVAC system associated with the thermostat  534 , and is further configured to provide control of environmental (e.g., temperature) settings. In some implementations, the thermostat  534  can additionally or alternatively receive data relating to activity at a home and/or environmental data at a home, e.g., at various locations indoors and outdoors at the home. The thermostat  534  can directly measure energy consumption of the HVAC system associated with the thermostat, or can estimate energy consumption of the HVAC system associated with the thermostat  534 , for example, based on detected usage of one or more components of the HVAC system associated with the thermostat  534 . The thermostat  534  can communicate temperature and/or energy monitoring information to or from the control unit  510  and can control the environmental (e.g., temperature) settings based on commands received from the control unit  510 . 
     In some implementations, the thermostat  534  is a dynamically programmable thermostat and can be integrated with the control unit  510 . For example, the dynamically programmable thermostat  534  can include the control unit  510 , e.g., as an internal component to the dynamically programmable thermostat  534 . In addition, the control unit  510  can be a gateway device that communicates with the dynamically programmable thermostat  534 . In some implementations, the thermostat  534  is controlled via one or more home automation controls  522 . 
     A module  537  is connected to one or more components of an HVAC system associated with a home, and is configured to control operation of the one or more components of the HVAC system. In some implementations, the module  537  is also configured to monitor energy consumption of the HVAC system components, for example, by directly measuring the energy consumption of the HVAC system components or by estimating the energy usage of the one or more HVAC system components based on detecting usage of components of the HVAC system. The module  537  can communicate energy monitoring information and the state of the HVAC system components to the thermostat  534  and can control the one or more components of the HVAC system based on commands received from the thermostat  534 . 
     In some examples, the system  500  further includes one or more robotic devices  590 . The robotic devices  590  may be any type of robots that are capable of moving and taking actions that assist in home monitoring. For example, the robotic devices  590  may include drones that are capable of moving throughout a home based on automated control technology and/or user input control provided by a user. In this example, the drones may be able to fly, roll, walk, or otherwise move about the home. The drones may include helicopter type devices (e.g., quad copters), rolling helicopter type devices (e.g., roller copter devices that can fly and roll along the ground, walls, or ceiling) and land vehicle type devices (e.g., automated cars that drive around a home). In some cases, the robotic devices  590  may be devices that are intended for other purposes and merely associated with the system  500  for use in appropriate circumstances. For instance, a robotic vacuum cleaner device may be associated with the monitoring system  500  as one of the robotic devices  590  and may be controlled to take action responsive to monitoring system events. 
     In some examples, the robotic devices  590  automatically navigate within a home. In these examples, the robotic devices  590  include sensors and control processors that guide movement of the robotic devices  590  within the home. For instance, the robotic devices  590  may navigate within the home using one or more cameras, one or more proximity sensors, one or more gyroscopes, one or more accelerometers, one or more magnetometers, a global positioning system (GPS) unit, an altimeter, one or more sonar or laser sensors, and/or any other types of sensors that aid in navigation about a space. The robotic devices  590  may include control processors that process output from the various sensors and control the robotic devices  590  to move along a path that reaches the desired destination and avoids obstacles. In this regard, the control processors detect walls or other obstacles in the home and guide movement of the robotic devices  590  in a manner that avoids the walls and other obstacles. 
     In addition, the robotic devices  590  may store data that describes attributes of the home. For instance, the robotic devices  590  may store a floorplan and/or a three-dimensional model of the home that enables the robotic devices  590  to navigate the home. During initial configuration, the robotic devices  590  may receive the data describing attributes of the home, determine a frame of reference to the data (e.g., a home or reference location in the home), and navigate the home based on the frame of reference and the data describing attributes of the home. Further, initial configuration of the robotic devices  590  also may include learning of one or more navigation patterns in which a user provides input to control the robotic devices  590  to perform a specific navigation action (e.g., fly to an upstairs bedroom and spin around while capturing video and then return to a home charging base). In this regard, the robotic devices  590  may learn and store the navigation patterns such that the robotic devices  590  may automatically repeat the specific navigation actions upon a later request. 
     In some examples, the robotic devices  590  may include data capture and recording devices. In these examples, the robotic devices  590  may include one or more cameras, one or more motion sensors, one or more microphones, one or more biometric data collection tools, one or more temperature sensors, one or more humidity sensors, one or more air flow sensors, and/or any other types of sensors that may be useful in capturing monitoring data related to the home and users in the home. The one or more biometric data collection tools may be configured to collect biometric samples of a person in the home with or without contact of the person. For instance, the biometric data collection tools may include a fingerprint scanner, a hair sample collection tool, a skin cell collection tool, and/or any other tool that allows the robotic devices  590  to take and store a biometric sample that can be used to identify the person (e.g., a biometric sample with DNA that can be used for DNA testing). 
     In some implementations, the robotic devices  590  may include output devices. In these implementations, the robotic devices  590  may include one or more displays, one or more speakers, and/or any type of output devices that allow the robotic devices  590  to communicate information to a nearby user. 
     The robotic devices  590  also may include a communication module that enables the robotic devices  590  to communicate with the control unit  510 , each other, and/or other devices. The communication module may be a wireless communication module that allows the robotic devices  590  to communicate wirelessly. For instance, the communication module may be a Wi-Fi module that enables the robotic devices  590  to communicate over a local wireless network at the home. The communication module further may be a 900 MHz wireless communication module that enables the robotic devices  590  to communicate directly with the control unit  510 . Other types of short-range wireless communication protocols, such as Bluetooth, Bluetooth LE, Z-wave, Zigbee, etc., may be used to allow the robotic devices  590  to communicate with other devices in the home. In some implementations, the robotic devices  590  may communicate with each other or with other devices of the system  500  through the network  505 . 
     The robotic devices  590  further may include processor and storage capabilities. The robotic devices  590  may include any suitable processing devices that enable the robotic devices  590  to operate applications and perform the actions described throughout this disclosure. In addition, the robotic devices  590  may include solid-state electronic storage that enables the robotic devices  590  to store applications, configuration data, collected sensor data, and/or any other type of information available to the robotic devices  590 . 
     The robotic devices  590  are associated with one or more charging stations. The charging stations may be located at predefined home base or reference locations in the home. The robotic devices  590  may be configured to navigate to the charging stations after completion of tasks needed to be performed for the monitoring system  500 . For instance, after completion of a monitoring operation or upon instruction by the control unit  510 , the robotic devices  590  may be configured to automatically fly to and land on one of the charging stations. In this regard, the robotic devices  590  may automatically maintain a fully charged battery in a state in which the robotic devices  590  are ready for use by the monitoring system  500 . 
     The charging stations may be contact based charging stations and/or wireless charging stations. For contact based charging stations, the robotic devices  590  may have readily accessible points of contact that the robotic devices  590  are capable of positioning and mating with a corresponding contact on the charging station. For instance, a helicopter type robotic device may have an electronic contact on a portion of its landing gear that rests on and mates with an electronic pad of a charging station when the helicopter type robotic device lands on the charging station. The electronic contact on the robotic device may include a cover that opens to expose the electronic contact when the robotic device is charging and closes to cover and insulate the electronic contact when the robotic device is in operation. 
     For wireless charging stations, the robotic devices  590  may charge through a wireless exchange of power. In these cases, the robotic devices  590  need only locate themselves closely enough to the wireless charging stations for the wireless exchange of power to occur. In this regard, the positioning needed to land at a predefined home base or reference location in the home may be less precise than with a contact based charging station. Based on the robotic devices  590  landing at a wireless charging station, the wireless charging station outputs a wireless signal that the robotic devices  590  receive and convert to a power signal that charges a battery maintained on the robotic devices  590 . 
     In some implementations, each of the robotic devices  590  has a corresponding and assigned charging station such that the number of robotic devices  590  equals the number of charging stations. In these implementations, the robotic devices  590  always navigate to the specific charging station assigned to that robotic device. For instance, a first robotic device may always use a first charging station and a second robotic device may always use a second charging station. 
     In some examples, the robotic devices  590  may share charging stations. For instance, the robotic devices  590  may use one or more community charging stations that are capable of charging multiple robotic devices  590 . The community charging station may be configured to charge multiple robotic devices  590  in parallel. The community charging station may be configured to charge multiple robotic devices  590  in serial such that the multiple robotic devices  590  take turns charging and, when fully charged, return to a predefined home base or reference location in the home that is not associated with a charger. The number of community charging stations may be less than the number of robotic devices  590 . 
     In addition, the charging stations may not be assigned to specific robotic devices  590  and may be capable of charging any of the robotic devices  590 . In this regard, the robotic devices  590  may use any suitable, unoccupied charging station when not in use. For instance, when one of the robotic devices  590  has completed an operation or is in need of battery charge, the control unit  510  references a stored table of the occupancy status of each charging station and instructs the robotic device to navigate to the nearest charging station that is unoccupied. 
     The system  500  further includes one or more integrated security devices  580 . The one or more integrated security devices may include any type of device used to provide alerts based on received sensor data. For instance, the one or more control units  510  may provide one or more alerts to the one or more integrated security input/output devices  580 . Additionally, the one or more control units  510  may receive one or more sensor data from the sensors  520  and determine whether to provide an alert to the one or more integrated security input/output devices  580 . 
     The sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the integrated security devices  580  may communicate with the controller  512  over communication links  524 ,  526 ,  528 ,  532 ,  538 , and  584 . The communication links  524 ,  526 ,  528 ,  532 ,  538 , and  584  may be a wired or wireless data pathway configured to transmit signals from the sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the integrated security devices  580  to the controller  512 . The sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the integrated security devices  580  may continuously transmit sensed values to the controller  512 , periodically transmit sensed values to the controller  512 , or transmit sensed values to the controller  512  in response to a change in a sensed value. 
     The communication links  524 ,  526 ,  528 ,  532 ,  538 , and  584  may include a local network. The sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the integrated security devices  580 , and the controller  512  may exchange data and commands over the local network. The local network may include 802.11 “Wi-Fi” wireless Ethernet (e.g., using low-power Wi-Fi chipsets), Z-Wave, Zigbee, Bluetooth, “Homeplug” or other “Powerline” networks that operate over AC wiring, and a Category 5 (CATS) or Category 6 (CAT6) wired Ethernet network. The local network may be a mesh network constructed based on the devices connected to the mesh network. 
     The monitoring server  560  is an electronic device configured to provide monitoring services by exchanging electronic communications with the control unit  510 , the one or more user devices  540  and  550 , and the central alarm station server  570  over the network  505 . For example, the monitoring server  560  may be configured to monitor events generated by the control unit  510 . In this example, the monitoring server  560  may exchange electronic communications with the network module  514  included in the control unit  510  to receive information regarding events detected by the control unit  510 . The monitoring server  560  also may receive information regarding events from the one or more user devices  540  and  550 . 
     In some examples, the monitoring server  560  may route alert data received from the network module  514  or the one or more user devices  540  and  550  to the central alarm station server  570 . For example, the monitoring server  560  may transmit the alert data to the central alarm station server  570  over the network  505 . 
     The monitoring server  560  may store sensor and image data received from the monitoring system and perform analysis of sensor and image data received from the monitoring system. Based on the analysis, the monitoring server  560  may communicate with and control aspects of the control unit  510  or the one or more user devices  540  and  550 . 
     The monitoring server  560  may provide various monitoring services to the system  500 . For example, the monitoring server  560  may analyze the sensor, image, and other data to determine an activity pattern of a resident of the home monitored by the system  500 . In some implementations, the monitoring server  560  may analyze the data for alarm conditions or may determine and perform actions at the home by issuing commands to one or more of the controls  522 , possibly through the control unit  510 . 
     The monitoring server  560  can be configured to provide information (e.g., activity patterns) related to one or more residents of the home monitored by the system  500  (e.g., conferencer  111 ). For example, one or more of the sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the integrated security devices  580  can collect data related to a resident including location information (e.g., if the resident is home or is not home) and provide location information to the thermostat  534 . 
     The central alarm station server  570  is an electronic device configured to provide alarm monitoring service by exchanging communications with the control unit  510 , the one or more user devices  540  and  550 , and the monitoring server  560  over the network  505 . For example, the central alarm station server  570  may be configured to monitor alerting events generated by the control unit  510 . In this example, the central alarm station server  570  may exchange communications with the network module  514  included in the control unit  510  to receive information regarding alerting events detected by the control unit  510 . The central alarm station server  570  also may receive information regarding alerting events from the one or more user devices  540  and  550  and/or the monitoring server  560 . 
     The central alarm station server  570  is connected to multiple terminals  572  and  574 . The terminals  572  and  574  may be used by operators to process alerting events. For example, the central alarm station server  570  may route alerting data to the terminals  572  and  574  to enable an operator to process the alerting data. The terminals  572  and  574  may include general-purpose computers (e.g., desktop personal computers, workstations, or laptop computers) that are configured to receive alerting data from a server in the central alarm station server  570  and render a display of information based on the alerting data. For instance, the controller  512  may control the network module  514  to transmit, to the central alarm station server  570 , alerting data indicating that a sensor  520  detected motion from a motion sensor via the sensors  520 . The central alarm station server  570  may receive the alerting data and route the alerting data to the terminal  572  for processing by an operator associated with the terminal  572 . The terminal  572  may render a display to the operator that includes information associated with the alerting event (e.g., the lock sensor data, the motion sensor data, the contact sensor data, etc.) and the operator may handle the alerting event based on the displayed information. 
     In some implementations, the terminals  572  and  574  may be mobile devices or devices designed for a specific function. Although  FIG.  5    illustrates two terminals for brevity, actual implementations may include more (and, perhaps, many more) terminals. 
     The one or more authorized user devices  540  and  550  are devices that host and display user interfaces. For instance, the user device  540  is a mobile device that hosts or runs one or more native applications (e.g., the home monitoring application  542 ). The user device  540  may be a cellular phone or a non-cellular locally networked device with a display. The user device  540  may include a cell phone, a smart phone, a tablet PC, a personal digital assistant (“PDA”), or any other portable device configured to communicate over a network and display information. For example, implementations may also include Blackberry-type devices (e.g., as provided by Research in Motion), electronic organizers, iPhone-type devices (e.g., as provided by Apple), iPod devices (e.g., as provided by Apple) or other portable music players, other communication devices, and handheld or portable electronic devices for gaming, communications, and/or data organization. The user device  540  may perform functions unrelated to the monitoring system, such as placing personal telephone calls, playing music, playing video, displaying pictures, browsing the Internet, maintaining an electronic calendar, etc. 
     The user device  540  includes a home monitoring application  552 . The home monitoring application  542  refers to a software/firmware program running on the corresponding mobile device that enables the user interface and features described throughout. The user device  540  may load or install the home monitoring application  542  based on data received over a network or data received from local media. The home monitoring application  542  runs on mobile devices platforms, such as iPhone, iPod touch, Blackberry, Google Android, Windows Mobile, etc. The home monitoring application  542  enables the user device  540  to receive and process image and sensor data from the monitoring system. 
     The user device  540  may be a general-purpose computer (e.g., a desktop personal computer, a workstation, or a laptop computer) that is configured to communicate with the monitoring server  560  and/or the control unit  510  over the network  505 . The user device  540  may be configured to display a smart home user interface  552  that is generated by the user device  540  or generated by the monitoring server  560 . For example, the user device  540  may be configured to display a user interface (e.g., a web page) provided by the monitoring server  560  that enables a user to perceive images captured by the camera  530  and/or reports related to the monitoring system. Although  FIG.  5    illustrates two user devices for brevity, actual implementations may include more (and, perhaps, many more) or fewer user devices. 
     In some implementations, the one or more user devices  540  and  550  communicate with and receive monitoring system data from the control unit  510  using the communication link  538 . For instance, the one or more user devices  540  and  550  may communicate with the control unit  510  using various local wireless protocols such as Wi-Fi, Bluetooth, Z-wave, Zigbee, HomePlug (ethernet over power line), or wired protocols such as Ethernet and USB, to connect the one or more user devices  540  and  550  to local security and automation equipment. The one or more user devices  540  and  550  may connect locally to the monitoring system and its sensors and other devices. The local connection may improve the speed of status and control communications because communicating through the network  505  with a remote server (e.g., the monitoring server  560 ) may be significantly slower. 
     Although the one or more user devices  540  and  550  are shown as communicating with the control unit  510 , the one or more user devices  540  and  550  may communicate directly with the sensors and other devices controlled by the control unit  510 . In some implementations, the one or more user devices  540  and  550  replace the control unit  510  and perform the functions of the control unit  510  for local monitoring and long range/offsite communication. 
     In other implementations, the one or more user devices  540  and  550  receive monitoring system data captured by the control unit  510  through the network  505 . The one or more user devices  540 ,  550  may receive the data from the control unit  510  through the network  505  or the monitoring server  560  may relay data received from the control unit  510  to the one or more user devices  540  and  550  through the network  505 . In this regard, the monitoring server  560  may facilitate communication between the one or more user devices  540  and  550  and the monitoring system. 
     In some implementations, the one or more user devices  540  and  550  may be configured to switch whether the one or more user devices  540  and  550  communicate with the control unit  510  directly (e.g., through link  538 ) or through the monitoring server  560  (e.g., through network  505 ) based on a location of the one or more user devices  540  and  550 . For instance, when the one or more user devices  540  and  550  are located close to the control unit  510  and in range to communicate directly with the control unit  510 , the one or more user devices  540  and  550  use direct communication. When the one or more user devices  540  and  550  are located far from the control unit  510  and not in range to communicate directly with the control unit  510 , the one or more user devices  540  and  550  use communication through the monitoring server  560 . 
     Although the one or more user devices  540  and  550  are shown as being connected to the network  505 , in some implementations, the one or more user devices  540  and  550  are not connected to the network  505 . In these implementations, the one or more user devices  540  and  550  communicate directly with one or more of the monitoring system components and no network (e.g., Internet) connection or reliance on remote servers is needed. 
     In some implementations, the one or more user devices  540  and  550  are used in conjunction with only local sensors and/or local devices in a house. In these implementations, the system  500  includes the one or more user devices  540  and  550 , the sensors  520 , the home automation controls  522 , the camera  530 , and the robotic devices  590 . The one or more user devices  540  and  550  receive data directly from the sensors  520 , the home automation controls  522 , the camera  530 , and the robotic devices  590 , and sends data directly to the sensors  520 , the home automation controls  522 , the camera  530 , and the robotic devices  590 . The one or more user devices  540 ,  550  provide the appropriate interfaces/processing to provide visual surveillance and reporting. 
     In other implementations, the system  500  further includes network  505  and the sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the robotic devices  590 , and are configured to communicate sensor and image data to the one or more user devices  540  and  550  over network  505  (e.g., the Internet, cellular network, etc.). In yet another implementation, the sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the robotic devices  590  (or a component, such as a bridge/router) are intelligent enough to change the communication pathway from a direct local pathway when the one or more user devices  540  and  550  are in close physical proximity to the sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the robotic devices  590  to a pathway over network  505  when the one or more user devices  540  and  550  are farther from the sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the robotic devices  590 . 
     In some examples, the system leverages GPS information from the one or more user devices  540  and  550  to determine whether the one or more user devices  540  and  550  are close enough to the sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the robotic devices  590  to use the direct local pathway or whether the one or more user devices  540  and  550  are far enough from the sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the robotic devices  590  that the pathway over network  505  is required. 
     In other examples, the system leverages status communications (e.g., pinging) between the one or more user devices  540  and  550  and the sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the robotic devices  590  to determine whether communication using the direct local pathway is possible. If communication using the direct local pathway is possible, the one or more user devices  540  and  550  communicate with the sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the robotic devices  590  using the direct local pathway. If communication using the direct local pathway is not possible, the one or more user devices  540  and  550  communicate with the sensors  520 , the home automation controls  522 , the camera  530 , the thermostat  534 , and the robotic devices  590  using the pathway over network  505 . 
     In some implementations, the system  500  provides end users with access to images captured by the camera  530  to aid in decision making. The system  500  may transmit the images captured by the camera  530  over a wireless WAN network to the user devices  540  and  550 . Because transmission over a wireless WAN network may be relatively expensive, the system  500  can use several techniques to reduce costs while providing access to significant levels of useful visual information (e.g., compressing data, down-sampling data, sending data only over inexpensive LAN connections, or other techniques). 
     In some implementations, a state of the monitoring system and other events sensed by the monitoring system may be used to enable/disable video/image recording devices (e.g., the camera  530 ). In these implementations, the camera  530  may be set to capture images on a periodic basis when the alarm system is armed in an “away” state, but set not to capture images when the alarm system is armed in a “home” state or disarmed. In addition, the camera  530  may be triggered to begin capturing images when the alarm system detects an event, such as an alarm event, a door-opening event for a door that leads to an area within a field of view of the camera  530 , or motion in the area within the field of view of the camera  530 . In other implementations, the camera  530  may capture images continuously, but the captured images may be stored or transmitted over a network when needed. 
     The described systems, methods, and techniques may be implemented in digital electronic circuitry, computer hardware, firmware, software, or in combinations of these elements. Apparatus implementing these techniques may include appropriate input and output devices, a computer processor, and a computer program product tangibly embodied in a machine-readable storage device for execution by a programmable processor. A process implementing these techniques may be performed by a programmable processor executing a program of instructions to perform desired functions by operating on input data and generating appropriate output. The techniques may be implemented in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from, and to transmit data and instructions to, a data storage system, at least one input device, and at least one output device. 
     Each computer program may be implemented in a high-level procedural or object-oriented programming language, or in assembly or machine language if desired; and in any case, the language may be a compiled or interpreted language. Suitable processors include, by way of example, both general and special purpose microprocessors. Generally, a processor will receive instructions and data from a read-only memory and/or a random access memory. Storage devices suitable for tangibly embodying computer program instructions and data include all forms of non-volatile memory, including by way of example semiconductor memory devices, such as Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and Compact Disc Read-Only Memory (CD-ROM). Any of the foregoing may be supplemented by, or incorporated in, specially designed ASICs (application-specific integrated circuits). 
     It will be understood that various modifications may be made. For example, other useful implementations could be achieved if steps of the disclosed techniques were performed in a different order and/or if components in the disclosed systems were combined in a different manner and/or replaced or supplemented by other components. Accordingly, other implementations are within the scope of the disclosure.