Patent Publication Number: US-2020281521-A1

Title: Apparatus, system, and method for monitoring sleep patterns

Description:
TECHNICAL FIELD 
     The present disclosure generally relates to an apparatus, system, and method for monitoring patterns in behavior, and more particularly to an apparatus, system, and method for monitoring sleep patterns. 
     BACKGROUND 
     Existing baby monitors typically collect and transfer audio and/or video data to a device, such as an audio and/or video display, which is monitored by a guardian. Such devices typically provide a real-time stream of an audio recording and/or a video display that a guardian monitors. 
     Existing baby monitors typically provide the real-time stream of audible sounds and video display of a baby, infant, or child, without recording and further analyzing data associated with the baby. Accordingly, conventional methods do not provide analysis and/or recommendations to the guardian such as analysis and/or recommendations regarding sleep patterns of a baby. Instead, conventional methods merely provide real-time audio recordings and/or a real-time video display to a guardian, with any adjustments to sleep conditions of the baby left entirely to the discretion of the guardian. Accordingly, conventional baby monitors provide no assistance further to providing audio and video information for managing the sleep patterns of a baby. 
     The exemplary disclosed apparatus, system, and method are directed to overcoming one or more of the shortcomings set forth above and/or other deficiencies in existing technology. 
     SUMMARY OF THE DISCLOSURE 
     In one exemplary aspect, the present disclosure is directed to a system. The system includes a sleep pattern module, comprising computer-executable code stored in non-volatile memory, a processor, a sensor array, and a device array. The sleep pattern module, the processor, the sensor array, and the device array are configured to sense data of a sleep subject using the sensor array, process the sensed data, issue an alert to a guardian of the sleep subject based on the processed data, control the device array based on the processed data, and provide sleep pattern modification recommendations to the guardian of the sleep subject based on the processed data. 
     In another aspect, the present disclosure is directed to a method. The method includes sensing data of a sleep subject using a sensor array, processing the sensed data, the processed data indicating whether the sleep subject is in a restless state or a deep sleep state, issuing an alert to a guardian of the sleep subject based on the processed data, and controlling a device array based on the processed data, the device array including a soothing device and a lighting device. The method also includes providing sleep pattern modification recommendations to the guardian of the sleep subject based on the processed data, activating the soothing device when the sleep subject is in the restless state, and varying a brightness of the lighting device when the sleep subject is in the deep sleep state. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a schematic view of an exemplary embodiment of the present invention; 
         FIG. 2  is a schematic view of an exemplary embodiment of the present invention; 
         FIG. 3  is a schematic view of an exemplary embodiment of the present invention; 
         FIG. 4  is a schematic view of an exemplary user interface of the present invention; 
         FIG. 5  illustrates an exemplary process of an exemplary embodiment of the present invention; 
         FIG. 6  illustrates an exemplary process of an exemplary embodiment of the present invention; 
         FIG. 7  is a schematic illustration of an exemplary computing device, in accordance with at least some exemplary embodiments of the present disclosure; and 
         FIG. 8  is a schematic illustration of an exemplary network, in accordance with at least some exemplary embodiments of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION AND INDUSTRIAL APPLICABILITY 
       FIG. 1  illustrates an exemplary system  300  for monitoring sleep patterns. For example, system  300  may be used to monitor sleep patterns of an infant or young child. System  300  may be used to monitor sleep patterns of any suitable person of any desired age (e.g., infant, child, adult, or elder person). System  300  may also be used for monitoring sleep patterns of any desired animals such as, for example, mammals or other animals that may be protected in a zoo or other refuge and/or under treatment. System  300  may also be used for monitoring a human in any suitable medical setting such as, for example, a medical diagnostic application, in preparation for, during, and/or following medical treatment, and/or any other suitable application for monitoring sleep as part of medical treatment. System  300  may also be used to provide recommendations for improving sleep quality, duration, and safety of a monitored subject (e.g., infant, young child, or any other suitable subject) to the parent, guardian, and/or caregiver of the subject, with the recommendations for example being individualized to that subject. 
     As illustrated in  FIG. 1 , system  300  may include a subsystem  305 , a sensor array  310 , a device array  315 , and a user interface  320 . For example, system  300  may include a plurality of a sensor arrays  310 , device arrays  315 , and/or user interfaces  320 . Subsystem  305 , sensor array  310 , device array  315 , and user interface  320  may be connected for example via network  301 , which may be similar to exemplary network  201  disclosed below regarding  FIG. 8 . 
     As illustrated in  FIG. 1 , subsystem  305  may include components similar to the exemplary computing device and network components described below regarding  FIGS. 7 and 8 . For example, subsystem  305  may include one or more modules having computer-executable code stored in non-volatile memory. Subsystem  305  may also include a processor for processing data associated with system  300  as disclosed herein that may be partially or substantially entirely integrated into any component (e.g., or combination of components) of system  300 . Subsystem  305  may for example include a sensor module  325 , a device module  330 , and an information module  335 , which may operate in conjunction with the other components of system  300  as described for example herein. Sensor module  325 , device module  330 , and information module  335  may each be a separate module or may be integrated into one or more exemplary modules (e.g., one or more sleep pattern modules). Subsystem  305  may include any suitable modules for example for receiving and processing sensed data from sensor array  310  (e.g., and/or device array  315 ), controlling device array  315  based on the processed data from sensor array  310  (e.g., and/or device array  315 ), and providing any suitable information to one or more users of system  300 . 
     In at least some exemplary embodiments, sensor module  325  may receive and process any suitable data from sensor array  310  (e.g., and/or device array  315 ), any other suitable components of system  300 , and/or any other suitable source. Sensor module  325  may analyze and/or perform artificial intelligence operations utilizing the sensed data transferred from sensor array  310  (e.g., and/or device array  315 ) as described for example herein. Device module  330  may control (e.g., provide instructions and/or command data to) device array  315  based on the sensed data from sensor array  310  (e.g., and/or device array  315 ) processed by sensor module  325  and/or based on input provided by a user of system  300  as described for example herein. Information module  335  may provide any suitable data (e.g., output data such as sleep pattern information) to users of system  300  via user interface  320  as described for example herein. 
     Subsystem  305  may for example include a controller  340  for controlling an operation of sensor module  325 , device module  330 , information module  335 , sensor array  310 , device array  315 , user interface  320 , and/or any other desired components. Controller  340  may include for example a micro-processing logic control device or board components. Also for example, controller  340  may include input/output arrangements that allow it to be connected (e.g., via wireless and/or electrical connection) to any suitable component of system  300 . For example, controller  340  may communicate with components of system  300  via wireless communication, electrical lines, and/or any other suitable communication technique. For example, controller  340  may control sensors of sensor array  310 , device array  315 , and/or user interface  320  so that components of system  300  act as Internet of Things (IoT) devices that may provide data to and/or be controlled by system  300  as data-providing devices. 
     Returning to  FIG. 1 , subsystem  305  may communicate with other components of system  300  via network  301  (e.g., as disclosed below regarding  FIG. 8 ). Subsystem  305  may also be partially or substantially entirely integrated with one or more components of system  300  such as, for example, network  301 , user interface  320 , sensor array  310 , and/or device array  315 . Subsystem  305  may include components similar to the exemplary components disclosed below regarding  FIGS. 7 and 8 . For example, subsystem  305  may include computer-executable code stored in non-volatile memory. Subsystem  305  may also include a processor, or alternatively, a processor for processing data associated with system  300  may be partially or substantially entirely integrated into any portion (e.g., or combination of portions) of system  300 . 
     Subsystem  305  may be configured to retrieve, store, process, and/or analyze data transmitted from one or more sensor arrays  310  (e.g., and/or one or more device arrays  315 ) to subsystem  305 . For example, subsystem  305  may operate using data from any desired number of sensors of sensor array  310  and/or devices of device array  315 . 
     Subsystem  305  may perform analysis using the data received from one or more sensor arrays  310  (e.g., and/or one or more device arrays  315 ) to for example provide information and recommendations regarding sleep patterns as described herein. For example, subsystem  305  may utilize sophisticated machine learning and/or artificial intelligence techniques to perform predictive analysis using some or substantially all data collected by one or more sensor arrays  310  (e.g., and/or one or more device arrays  315 ). For example, system  300  (e.g., subsystem  305 ) may utilize the collected data to prepare and submit (e.g., via network  301 , for example via wireless transmission such as via 4G LTE networks) datasets and variables to cloud computing clusters and/or other analytical tools (e.g., predictive analytical tools), which may analyze such data using artificial intelligence neural networks. Subsystem  305  may for example include cloud computing clusters performing predictive analysis. For example, subsystem  305  may utilize neural network-based artificial intelligence to provide information and recommendations for improving sleep quality, duration, and safety based on sensed data (e.g., continuously collected data) transmitted from sensor array  310 , device array  315 , and/or any other suitable source as described herein. For example, the exemplary neural network may include a plurality of input nodes that may be interconnected and/or networked with a plurality of additional and/or other processing nodes to determine recommendations. 
     For example, exemplary artificial intelligence processes may include filtering and processing datasets, processing to simplify datasets by statistically eliminating irrelevant, invariant or superfluous variables or creating new variables which are an amalgamation of a set of underlying variables, and/or processing for splitting datasets into train, test and validate datasets using at least a stratified sampling technique. For example, exemplary artificial intelligence processes may also include processing for training a machine learning model to provide recommendations for improving sleep quality, duration, and/or safety based on data collected by sensor array  310  and/or device array  315  as described herein. For example, the prediction algorithms and approach may include regression models, tree-based approaches, logistic regression, Bayesian methods, deep-learning and neural networks both as a stand-alone and on an ensemble basis, and final prediction may be based on the model/structure which delivers the highest degree of accuracy and stability as judged by implementation against the test and validate datasets. Also for example, exemplary artificial intelligence processes may include processing for training a machine learning model to provide recommendations for improving sleep quality, duration, and/or safety based on data collected by sensor array  310  and/or device array  315  as described herein. 
     For example, system  300  (e.g., subsystem  305 ) may utilize continuously collected data from sensor array  310  and/or device array  315 , which may include thousands, millions, and/or billions of data points, to perform predictive analysis using artificial intelligence and/or machine learning. System  300  (e.g., subsystem  305 ) may for example use the continuously-growing body of data collected by one or more sensor arrays  310  and/or one or more device arrays  315  to establish benchmarks and metrics for evaluating sleep patterns (e.g., metrics for evaluating sleep quality, sleep duration, and/or sleep safety). For example, system  300  (e.g., subsystem  305 ) may use substantially all available data to continuously refine predictive analysis for providing recommendations to users to improve sleep quality, duration, and/or safety. 
     As illustrated in  FIG. 2 , sensor array  310  may include one or more sensors that may be disposed at or near a subject  345  (e.g., a human such as an infant or young child, an animal, or any other suitable subject). 
     Sensor array  310  may include a visual sensor  350 . Visual sensor  350  may be a camera. For example, visual sensor  350  may be a video camera. Visual sensor  350  may be any suitable video camera such as a digital video camera, a webcam, and/or any other suitable camera for recording visual data (e.g., recording a video or taking pictures). Visual sensor  350  may be for example a three-dimensional video sensor or camera. For example, visual sensor  350  may utilize infrared beams to determine depth data (e.g., using between about 10,000 and about 50,000 infrared beams, for example about 30,000 infrared beams, to determine depth data of corresponding points) to provide three-dimensional imaging of subject  345 . For example, visual sensor  350  may utilize infrared beams to track sleep movements of subject  345  by using infrared beams to determine depth data of subject  345  (e.g., acting as a three-dimensional imaging sensor). Visual sensor  350  may include a plurality of cameras or a single camera configured to collect three-dimensional image data. In at least some exemplary embodiments, visual sensor  350  may be a stereoscopic camera and/or any other suitable device for stereo photography, stereo videography, and/or stereoscopic vision. Visual sensor  350  may be an infrared camera or any other suitable thermographic camera for forming a heat zone image. For example, visual sensor  350  may form an image by detecting and recording infrared radiation. Visual sensor  350  may also be a night vision camera or any other suitable camera that may amplify visible light and/or utilize radiation such as electromagnetic radiation. 
     Sensor array  310  may include an acoustic sensor  355 . Acoustic sensor  355  may be a microphone or any other suitable device for detecting and recording noise, vibrations, and/or any other desired noise. Acoustic sensor  355  may include for example one or more cardioid microphones, condenser microphones, omnidirectional microphones, dynamic microphones, and/or any other suitable microphone types. Acoustic sensor  355  may be integrated with and operate in conjunction with visual sensor  350 . Acoustic sensor  355  may also be an integrated part of host hardware, such as part of a device similar to user interface  320  (e.g., a mobile phone microphone). Acoustic sensor  355  may also be a separate, stand-alone sensor. 
     Sensor array  310  may include a biometric sensor  360 . Biometric sensor  360  may sense biometric information of subject  345  and/or a guardian (e.g., parent, caretaker, and/or any other suitable guardian) of subject  345 . For example, biometric sensor  360  may include one or more wearable devices worn by subject  345  and/or a guardian of subject  345 . Biometric sensor  360  may sense any suitable data such as food intake, supplement intake, medicine intake, physical activity and exercise, and/or any other health-related activity. Biometric sensor  360  may sense any desired user attribute such as blood pressure, body temperature, pulse, heartrate (e.g., a heartrate sensor), breathing (e.g., a breathing sensor), movement, weight gain, and/or any other desired characteristic of subject  345  and/or one or more guardians of subject  345 . 
     Sensor array  310  may include one or more sleep sensors  365 . Sleep sensor  365  may be integrated with biometric sensor  360  or may be a separate, stand-alone sensor. Sleep sensor  365  may be a wearable device that may be worn by subject  345  or may be disposed under a bedding sheet or on or in a mattress on which subject  345  may be sleeping. Sleep sensor  365  may also be disposed near subject  345  such as, for example, on a table or other location (e.g., in a room in which subject  345  is sleeping). Sleep sensor  365  may be any suitable sensor for sensing sleep data such as a heartrate, breathing, snoring, and/or any other desired sleep characteristics of subject  345 . For example, sleep sensor  365  may include an accelerometer and/or any other suitable sensing device for recording movement. Sleep sensor  365  may provide actigraphy data or any other suitable data that may indicate movement during sleep and/or any other suitable data for evaluating sleep patterns of subject  345 . Sleep sensor  365  may for example include an echolocation sensor that emits radio waves to measure breathing patterns and/or any other suitable sleep characteristic of subject  345 . Sleep sensor  365  may include piezoelectric sensors, motion sensors, radio frequency sensors, and/or any other suitable sensor for measuring sleep patterns. 
     Sensor array  310  may include a support sensor  370 . Support sensor  370  may be disposed on or in a support  375  (e.g., such as a crib, bed, medical treatment table, or any other suitable support that may also include support devices such as mattresses, cushions, pillows, linen, sheets, blankets, and other suitable accessories) that supports subject  345 . Support sensor  370  may sense any suitable support data such as a temperature of support  375 , moisture content of support  375 , pressure exerted by subject  345  on support  375 , and/or any other desired attribute of support  375 . Support sensor  370  may include components that may be similar to at least some of the various exemplary sensors described herein. 
     Sensor array  310  may include an ambient condition sensor  380 . Ambient condition sensor  380  may include a barometer or any other suitable device for sensing a barometric pressure (e.g., ambient pressure) of a space (e.g., room) in which subject  345  is located. Ambient condition sensor  380  may sense any suitable ambient condition data of a space in which subject  345  is located. Ambient condition sensor  380  may include any suitable sensing components for sensing temperature (e.g., an ambient temperature sensor) such as, for example, a thermocouple, a resistance temperature detector (RTD), a thermistor, and/or a semiconductor-based temperature sensing component. Ambient condition sensor  380  may also include a hygrometer or any other suitable device for sensing a relative humidity of a space in which subject  345  is located. Ambient condition sensor  380  may also sense air quality (e.g., presence and/or amount of various particles of material present in air surrounding subject  345 ) and any other desired data regarding conditions of a space (e.g., room) in which subject  345  is disposed. 
     Sensor array  310  may also include a medical sensor  385  (e.g., and/or sensor module  325  may receive data from any suitable medical, diagnostic, and/or other treatment equipment such as hospital equipment and other medical equipment). For example, medical sensor  385  may be a medical sensor that senses a biometric attribute of subject  345 . For example, medical sensor  385  may sense any suitable medical data associated with devices (e.g., data based on an operation of these exemplary devices) such as a cardiac monitor, an invasive blood pressure monitor, a ventilator, a temperature control device, a dialysis machine, an ECMO machine, and/or any other suitable medical device for treating and/or monitoring subject  345 . 
     The exemplary sensors of sensor array  310  described above may be integrated into one or more sensor arrays located in any suitable location relative to subject  345 . Sensor module  325  may communicate with, control, and/or exchange data with the exemplary sensors of sensor array  310  (e.g., as well as any other suitable device or data source that may provide data for processing to sensor module  325 ). For example in addition to data received from sensor array  310 , sensor module  325  may receive data from external databases (e.g., hospital records or other medical records, data from the literature regarding sleep hygiene and/or sleep patterns, aggregate data compiled from sleep studies and other suitable research, and/or any other suitable sleep pattern information), direct input from users of system  300 , and/or any other suitable data source (e.g., received via network  301 ). 
     As illustrated in  FIG. 3 , device array  315  may include one or more devices that may be co-located with subject  345  (e.g., in the same room, house, or building as subject  345  or in the same area of a facility such as a medical facility as subject  345 ). Device array  315  may for example include a plurality of household and/or commercial devices that may be networked together (e.g., and with other components of system  300 ) as an Internet of Things network of devices that interact and exchange data. 
     Device array  315  may include a plurality of entertainment devices  410  and  415 . Entertainment devices  410  and  415  may be for example televisions, smartboards, video game systems, speaker or sound systems (e.g., a home sound system), radios, stereos, and/or any other desired residential or commercial equipment. 
     Device array  315  may include a plurality of utility devices  420 ,  425 ,  430 ,  435 ,  440 ,  445 , and  450 . Utility devices  420 ,  425 ,  430 ,  435 ,  440 ,  445 , and  450  may be for example thermostats, lighting devices (e.g., lighting components) such as lamps and overhead lighting, doorbells, security systems, alarms such as security alarms and fire alarms, and/or kitchen or food preparation devices (e.g., such as refrigerators, ovens, microwaves, toasters, and coffee makers that may for example have alarms). For example, utility device  430  may be a lighting element disposed in a room in which subject  345  may be sleeping. Also for example, utility device  425  may be a thermostat that controls a temperature (e.g., and/or other ambient conditions) within the room in which subject  345  may be sleeping. Further for example, utility device  450  may be a soothing device such as a lighting display (e.g., a lighting display device that may emit soothing light), a soothing vibration device (e.g., a device that may vibrate to provide soothing to a baby or child), and/or a mobile activation device (e.g., a device that may provide soothing movement to a baby or child, or move an object within a field of view of a baby or child that may soothe the baby or child). For example, utility device  450  may be a soothing device that is an audio device (e.g., sound soother or similar device that may provide comforting sounds to subject  345  for example during sleep). 
     One or more user interfaces  320  may also be co-located in the exemplary space illustrated in  FIG. 3 . For example, user interfaces  320  that may be smart speaker devices (e.g., Alexa, Siri, HomeKit, and/or any other suitable smart speaker techniques) may be located in one or more rooms of an exemplary space (e.g., in the same and/or different rooms than a room in which subject  345  is located), as well as other exemplary user interfaces  320  described herein (e.g., smartphones, tablets, and/or computers). 
     User interface  320  may be any suitable user interface for receiving input and/or providing output (e.g., raw data and/or results of predictive analysis described above such as recommendations) to a user. For example, user interface  320  may be a touchscreen device (e.g., of a smartphone, a tablet, a smartboard, and/or any suitable computer device), a computer keyboard and monitor (e.g., desktop or laptop), an audio-based device for entering input and/or receiving output via sound, a tactile-based device for entering input and receiving output based on touch or feel, a dedicated user interface designed to work specifically with other components of system  300 , and/or any other suitable user interface (e.g., including components and/or configured to work with components described below regarding  FIGS. 7 and 8 ). 
     In at least some exemplary embodiments, user interface  320  may include haptic feedback components or haptics for providing information to users of system  300 . For example, user interface  320  may be configured to vibrate and/or exert predetermined pressure against a user&#39;s hand or other body part to represent a movement or condition occurring with a subject (e.g., infant or young child) being sensed by sensor array  310 . For example, user interface  320  may be a smartphone or tablet configured to vibrate and/or may include components configured to transfer haptic data to a user. User interface  320  may also include virtual reality components (e.g., virtual reality glasses, gloves, and/or other suitable equipment) that may provide a user with a virtual representation of an area in which a subject (e.g., infant, young child, or other suitable subject) is located. User interface  320  may also include augmented reality (AR) components such as visual overlays that may be displayed over image data recorded by visual sensor  350 . For example, user interface  320  may include AR visualization such as labeling hazards, providing visual warnings, providing statistics of subject  345  as overlays, and/or any other desired AR display elements. For example, a virtual representation of a room in which the subject is located may be produced based on data sensed and processed by system  300 . User interface  320  may also include haptic feedback equipment that may operate in conjunction with the virtual reality equipment that user interface  320  may include. For example based on an operation of virtual reality and haptic feedback equipment of user interface  320 , a user may virtually move close to and/or feel a chest area or other portion of the subject (e.g., to check breathing and/or heartbeat) based on data provided by sensor array  310  and processed by sensor module  325 . 
     For example, user interface  320  may include a touchscreen device of a smartphone or handheld tablet. For example as illustrated in  FIG. 4 , user interface  320  may include a display  395  (e.g., a computing device display, a touchscreen display, and/or any other suitable type of display) that may provide raw data and/or predictive analysis results to a user. For example, display  395  may include a graphical user interface to facilitate entry of input by a user and/or receiving output. For example, a user may utilize user interface  320  to query raw data results and/or enter parameters to define a set of desired output (e.g., areas identified by the user as including issues such as sleep pattern challenges to be resolved). Also for example, system  300  may provide alerts to a user (e.g., based on an operation of information module  335 ) via output transmitted to user interface  320  (e.g., alerts pushed to a user via user interface  320 ) as described herein. System  300  may also send alerts to users by alternative methods such as, for example, via text message, email, and/or recording sent by telephone. 
     In at least some exemplary embodiments, user interface  320  may include applications (e.g., that may be accessed and operated using a smartphone and/or tablet) and/or websites (e.g., that may be accessed and operated using a laptop or desktop computer) that a user may utilize to provide input to and receive output from system  300 . In at least some exemplary embodiments, user interface  320  may be or may include smart speaker components (e.g., Alexa, Siri, HomeKit, and/or any other suitable smart speaker techniques). 
     In at least some exemplary embodiments, user interface  320  may include any suitable component for conducting a conversation with a user via textual, auditory, or other suitable techniques. For example, user interface  320  may include a chatbot such as an artificial intelligence chatbot. The exemplary chatbot may communicate with a user of system  300  such as a guardian of a subject (e.g., infant, child, adult, elder person or any other suitable subject) to request feedback from the guardian, provide suggestions or recommendations to the guardian (e.g., based on processing by system  300  as described herein), ask for further details regarding waking behavior or other input, and/or request or provide any other desired information. The exemplary chatbot may for example facilitate the data exchange in a conversational manner (e.g., via auditory conversation or textual chat). 
     The exemplary disclosed apparatus, system, and method may be used in any suitable application for monitoring sleep patterns. For example, the exemplary disclosed apparatus, system, and method may be used in any application for monitoring sleep patterns of an infant or young child. The exemplary disclosed apparatus, system, and method may be used to monitor sleep patterns of any suitable person of any desired age (e.g., infant, child, adult, or elder person). The exemplary disclosed apparatus, system, and method may be used to monitor sleep patterns of any desired animals such as, for example, mammals or other animals that may be protected in a zoo or other refuge and/or under treatment. The exemplary disclosed apparatus, system, and method may also be used for monitoring a human in any suitable medical setting such as, for example, a medical diagnostic application, in preparation for, during, and/or following medical treatment, and/or any other suitable application for monitoring sleep as part of medical treatment. The exemplary disclosed apparatus, system, and method may for example be used in a residence, a medical or psychiatric facility (e.g., an inpatient facility such as a hospital), and/or any other suitable facility or location for monitoring and/or analyzing sleep patterns or behavior. The exemplary disclosed apparatus, system, and method may also be used in any suitable application involving providing recommendations for improving sleep quality, duration, and safety of a monitored subject (e.g., infant, young child, or any other suitable subject) to a parent, guardian, and/or caregiver of that subject. 
     An exemplary operation of the exemplary disclosed apparatus, system, and method will now be described. For example,  FIG. 5  illustrates an exemplary process  500 . Process  500  starts at step  505 . At step  510 , the exemplary sensors of sensor array  310  may sense data associated with subject  345  and/or conditions of the space in which subject  345  is located, and this data may be transferred to sensor module  325 . For example, one or more visual sensors  350  may sense any suitable visual data for example as described above and transfer the data to sensor module  325 . One or more acoustic sensors  355  may sense any suitable acoustic data for example as described above and transfer the data to sensor module  325 . One or more biometric sensors  360  may sense any suitable biometric data for example as described above and transfer the data to sensor module  325 . One or more sleep sensors  365  may sense any suitable sleep data for example as described above and transfer the data to sensor module  325 . One or more support sensors  370  may sense any suitable support data for example as described above and transfer the data to sensor module  325 . One or more ambient condition sensors  380  may sense any suitable ambient condition data for example as described above and transfer the data to sensor module  325 . One or more medical sensors  385  may sense any suitable medical data for example as described above and transfer the data to sensor module  325 . Data from external databases, direct input from users of system  300 , and/or any other suitable data source as described for example above may be transferred to sensor module  325 . The exemplary data may be transferred from sensor array  310  and/or any other suitable exemplary source to subsystem  305  (e.g., sensor module  325 ) either continuously or at any desired constant or variable intervals in real-time or near real-time. 
     At step  515 , subsystem  305  (e.g., sensor module  325  and/or information module  335 ) may process the data collected and transferred at step  510  using any suitable data processing and/or artificial intelligence techniques. For example, subsystem  305  (e.g., sensor module  325  and/or information module  335 ) may analyze biometric data (e.g., and/or visual data, acoustic data, sleep data, support data, ambient condition data, or medical data) collected from observation (e.g., sensing by sensor array  310 ) of subject  345  (e.g., a sleeping infant, sleeping child, or other suitable subject). Subsystem  305  (e.g., sensor module  325  and/or information module  335 ) may use machine learning and deep learning to analyze streaming biometric input data (e.g., and/or visual data, acoustic data, sleep data, support data, ambient condition data, or medical data) transferred from sensor array  310  or other suitable exemplary sources described for example herein. Exemplary computing devices and/or neural networks of system  300  may operate using any suitable technique for data processing and/or machine learning as described for example herein. System  300  may issue alerts, control exemplary devices of device array  315  and sensor array  310 , and provide feedback and recommendations to users based on the exemplary data processing techniques and artificial intelligence operations described for example herein. 
     At step  520 , system  300  (e.g., subsystem  305 ) may determine whether to issue an alert based on the data sensed at step  510  and processed and analyzed at step  515 . System  300  may proceed to step  525  as described below if issuing an alert is appropriate based on the data sensed and analyzed at steps  510  and  515 . If issuing an alert is not appropriate, system  300  may proceed to step  530  as described below. 
     At step  525 , system  300  (e.g., subsystem  305 ) may issue an alert to users of system  300  and/or other parties such as first responders. For example, information module  335  may cause an alert to be issued based on the data sensed at step  510  and processed and analyzed at step  515 . In at least some exemplary embodiments, subsystem  305  may communicate with and send notifications and alarms to other devices such as user interface  320 . For example, subsystem  305  may cause user interface  320  (e.g., a smartphone, a wearable device, and/or a smart speaker such as Alexa and other exemplary devices described above) to issue any suitable alarm (e.g., audible alarm such as a beeping or siren, visual alarm such as a flashing light, vibrational alarm such as causing user interface  320  to vibrate, and/or any other suitable alert). Subsystem  305  may issue the exemplary alert or alarm to notify a guardian of subject  345  via an alarm emitted by user interface  320  and/or device array  315  (e.g., and/or sensor array  310 ) based on the data sensed at step  510  and processed and analyzed at step  515  (e.g., based on artificial intelligence operation of information module  335 ). In at least some exemplary embodiments, subsystem  305  may activate an emergency medical system that may for example issue an alert to security personnel and/or authorities (e.g., police, medical personnel, and/or other first responders) based on predetermined criteria and/or commands or settings provided by a user of system  300 . For example, subsystem  305  may place a call directly using 9-1-1 to report certain circumstances based on predetermined criteria or machine learning. For example, subsystem  305  may activate an emergency medical system (e.g., activate EMS) when sensor array  310  includes medical sensor  385  that may indicate a life-threatening situation to subject  345  and/or when sensor array  310  provides data (e.g., or lack of data) that may indicate a threatening situation to subject  345 . 
     At step  525  in at least some exemplary embodiments, system  300  (e.g., subsystem  305 ) may issue an alert to a guardian of subject  345  when sensed data of subject  345  is not being received from some or all of biometric sensor  360 , sleep sensor  365 , and/or medical sensor  385 . The alert may be issued when an absence of data or analysis of received data indicates that subject  345  may be experiencing a stoppage or interruption in breathing and/or other indicators of a SIDS (sudden infant death syndrome) event. System  300  may issue such a SIDS alert using some or all devices of user interface  320 , sensor array  310 , and device array  315  (e.g., visual and audio alerts emitted from entertainment devices, smartphones, flashing housing lights, audible smart speaker alarms, and/or any other suitable warning that may alert guardians of subject  345 ). Alerts may be accompanied by recommended actions to take (e.g., actions such as resuscitation and other medical or treatment actions). 
     At step  525  in at least some exemplary embodiments, system  300  (e.g., subsystem  305 ) may issue a notification to a guardian of subject  345  when data sensed at step  510  and processed and analyzed at step  515  indicates that subject  345  is awake or restless. System  300  may issue notifications indicating whether subject  345  is in a deep sleep state (e.g., deep state of sleep), REM sleep, light sleep, transitioning between sleep phases (e.g., a transitional sleep state), restless state of sleep, in a waking state, or awake. System  300  may issue notifications indicating whether subject  345  is following normal sleep patterns or deviating from normal sleep patterns. System  300  may issue any desired notification based on data sensed at step  510  and processed and analyzed at step  515 . After issuing an alert or notification at step  525 , system  300  may return to step  510 . 
     At step  530 , system  300  (e.g., subsystem  305 ) may determine whether a status or information request has been received from a user or whether a user should be prompted for information based on the data sensed at step  510  and processed and analyzed at step  515 . System  300  may proceed to step  535  as described below if a status or information request is appropriate. If a status or information request is not appropriate, system  300  may proceed to step  540  as described below. 
     At step  535 , system  300  (e.g., subsystem  305 ) may receive an information request from a user of system  300  such as a guardian of subject  345 . The requesting user may input the request via any suitable technique such as by using user interface  320  (e.g., typing or making a voice request via a smartphone application, computing device, smart speaker such as Alexa, or any other suitable exemplary user interface described herein). The requesting user may request and receive a status (e.g., sleep status) of subject  345  from system  300 . The requesting user may request that system  300  may serve as a baby monitor and provide video and/or audio using sensor array  310 . The requesting user may direct system  300  to turn and/or zoom sensors of sensor array  310  to provide desired resolution and information scope (e.g., zooming or turning visual sensor  350  and/or controlling other sensors of sensor array  310 ). The requesting user may request and receive a real-time visual, audio, and/or haptic representation (e.g., breathing or heartbeat) and/or virtual reality representation of data sensed by sensor array  310  as described for example above. System  300  may provide continuous or periodic status updates of subject  345  based on predetermined criteria and/or data sensed at step  510  and processed and analyzed at step  515 . 
     Also at step  535 , system  300  may prompt a user of system  300  such as a guardian of subject  345  for information based on data sensed at step  510  and processed and analyzed at step  515 . System  300  may prompt the user for information using any suitable technique such as via user interface  320  (e.g., textually or audibly). System  300  may for example request feedback from a user or request details of a behavior of subject  345  such as a waking or restless behavior. In at least some exemplary embodiments, system  300  may also provide feedback to a guardian of subject  345  as to whether or not subject  345  is present based on data sensed by sensor array  310  at step  510 . For example, system  300  may prompt a guardian of subject  345  to answer a question such as “Did you just lay your child down for his/her nap?” based on sensing that subject  345  is not present under conditions in which subject  345  is expected to be present (e.g., during a nap). For example when subject  345  is not present during an unexpected time (e.g., not present in a crib during nap time), system  300  may prompt the guardian to check on the child and/or issue an alert to the guardian. 
     System  300  may utilize a chatbot as described for example above during data exchange with a user at step  535 . System  300  may audibly and/or visually request feedback from a user, provide suggestions to the user, and/or ask for details about subject  345  or an area in which subject  345  is located, e.g., in a conversational manner. After responding to an information request or requesting and receiving information from a user at step  535 , system  300  may return to step  510 . 
     At step  540 , system  300  (e.g., subsystem  305 ) may determine whether one or more devices of device array  315  (and/or sensor array  310 ) are to be controlled based on the data sensed at step  510  and processed and analyzed at step  515 . System  300  may proceed to step  545  as described below if controlling an exemplary device is appropriate. If controlling an exemplary device is not appropriate, system  300  may proceed to step  550  as described below. 
     At step  545 , system  300  (e.g., subsystem  305 ) may control one or more devices of device array  315  (e.g., and/or sensor array  310 ) based on the data sensed at step  510  and processed and analyzed at step  515 . For example if subject  345  is in a waking, restless, or awake state based on analysis of the sensed data, device module  330  may control device array  315  including, e.g., entertainment devices such as televisions and speakers having adjustable volume, appliances such as ovens and microwaves having adjustable timers, and/or utility devices such as doorbells to operate in a low-volume or muted mode. For example, when subject  345  is awake or at a sleep stage where waking is likely based on analysis of the sensed data (e.g., a restless state), device module  330  may instruct device array  315  (e.g., various devices in a home or other location) to operate in a quiet or silent mode until subject  345  enters a relatively deeper sleep. In addition to controlling devices to operate with lower volume, device module  330  may control lighting elements of device array  315  to be lowered or dimmed, control a temperature of thermostats to be adjusted, and/or control any other devices of device array  315  to operate in a manner that facilitates increasing probability of lulling subject  345  into a relatively deeper sleep state. Device module  330  may also control speakers, soothing devices (e.g., lighting display, vibration device, mobile activation device, and/or sound soothers as described for example above), and/or other audio devices of device array  315  to play soothing music when subject  345  is waking, awake, or restless. Device module  330  may also control devices of device array  315  (e.g., and/or sensor array  310 ) to operate normally or relatively loudly when subject  345  is in a relatively deep sleep state or when desired by a user of system  300  such as a guardian of subject  345 . Device module  330  may control one or more devices of device array  315  (e.g., and/or sensor array  310 ) to operate in any desired manner based on data sensed at step  510  and processed and analyzed at step  515  (e.g., based on an operation of information module  335 ). After control of one or more devices at step  545 , system  300  may return to step  510 . 
     At step  550 , system  300  (e.g., subsystem  305 ) may determine whether providing feedback to a user of system  300  is appropriate based on the data sensed at step  510  and processed and analyzed at step  515 . System  300  may proceed to step  555  as described below if providing feedback is appropriate. If providing feedback is not appropriate, system  300  may proceed to step  560  as described below. 
     At step  555 , system  300  (e.g., subsystem  305  including information module  335 ) may provide any desired information and feedback to a user of system  300  based on the exemplary artificial intelligence and machine learning operations described for example herein. Information module  335  may for example provide sleep training information that may assist a user such as a parent or guardian of subject  345  to improve sleep patterns, sleep amounts, and quality of sleep of subject  345 . Information module  335  may perform data analysis (e.g., biometric data analysis and/or analysis of any of the sensed data described herein) using artificial intelligence (e.g., machine learning or deep learning) to make behavior modification recommendations to provide suggested actions to take relating to subject  345 . Information module  335  may use data of current sleep science and pediatric standards in analysis to generate the recommendations. Information module  335  may also provide recommendations regarding specific concerns, based on guardian feedback. For example, information module  335  may track sleep patterns against specific behavioral issues and/or heath concerns (e.g., ADHD, childhood anxiety or depression, autism spectrum disorders, and/or any other issue or concern). The sleep patterns may be tracked against behavior changes to provide insights and/or recommendations. Information module  335  may also be able to provide insights against performance data (e.g., academic, physical, social, and/or other desired performance data) collected from a guardian of subject  345 . Information module  335  may recommend actions to take that are age-appropriate (e.g., newborn, infants, toddlers, and any other desired stage based on user input and/or sensed data) behavior modifications relating to sleep and other suitable characteristics of subject  345 . Information module  335  may provide the recommendations via the exemplary techniques described for example above using user interface  320  or any other suitable device or technique. 
     Also at step  555  when data (e.g., a real-time or near real-time camera data stream of visual sensor  350 ) is available, information module  335  may utilize artificial intelligence processes to recognize items in an area around subject  345  (e.g., sleep area) and may recommend sleep hygiene protocols based on the recognized items. For example, information module  335  may recommend a revised placement, removal, and/or addition of one or more items. Based on visual data (e.g., data sensed by visual sensor  350 ), information module  335  may track light levels in an area at or near subject  345 , utilize the data in sleep analysis, and make recommendations for actions to take regarding lighting (e.g., adjusting overhead or lamp lighting in a room or other location in which subject  345  sleeps). Based on acoustic data (e.g., data sensed by acoustic sensor  355 ), information module  335  may track noise in an area at or near subject  345 , utilize the data in sleep analysis, and make recommendations for actions to take regarding noise (e.g., suppressing or masking noise from people, devices, animals, outside vehicles, and/or other noise sources that may be heard in a room or other location in which subject  345  sleeps). Based on ambient condition data (e.g., data sensed by ambient condition sensor  380 ) and/or support data (e.g., data sensed by support sensor  370 ), information module  335  may track room temperature and humidity and/or bedding or sleep support temperature and humidity in an area at or near subject  345 , utilize the data in sleep analysis, and make recommendations for actions to take regarding these factors (e.g., adjusting temperature, humidity, and/or bedding). 
     Further at step  555 , information module  335  may utilize artificial intelligence processes to record and present sleep-related development milestones for subject  345 . Results of analysis of information module  335  may be provided to a user as graphs and/or any other suitable visual or audio representation of a sleep cycle of subject  345  (e.g., a child&#39;s sleep cycle). Information module  335  may provide feedback congratulating a guardian of subject  345  for providing safe and effective sleep hygiene of subject  345 , based on evaluating determined performance against predetermined benchmarks (and/or based on performance criteria that may be determined based on machine learning). Subject to user authorization, system  300  may collect sleep data of subject  345  and transfer the data to outside databases via network  301  to improve learning models in the field of sleep science. When biometric data of a guardian of subject  345  is sensed as described for example above, information module  335  may use such data to map improvements for sleep cycles (e.g., of subject  345  and/or the guardian). 
     Additionally at step  555 , information module  335  may utilize artificial intelligence processes to provide up-to-date sleep science information to users of system  300 . Information module may also provide feedback and/or interactively teach guardians of subject  345  about sleep safety and to use good sleep hygiene (e.g., behaviors and actions to take regarding actions leading up to a bed time, napping, eating times and food types as they relate to sleeping times, sleeping conditions such as temperature, noise, and lighting, and/or any other suitable actions) regarding subject  345 . Information module  335  may also provide individualized feedback on sleep hygiene for subject  345  that is customized based on performing artificial intelligence operations on the data sensed at step  510 . 
     Further at step  555 , information module  335  may utilize artificial intelligence processes to track ongoing patterns (e.g., a plurality of sleep sessions) based on sensing data at step  510  and processing data at step  515  of multiple sleep sessions (e.g., system  300  may sense and process data associated with any desired time span of sleep sessions). System  300  may identify unusual patterns based on the data processed at step  515  and recommend that a guardian of subject  345  consult a medical professional. In addition to providing general (e.g., static) information regarding good sleep hygiene (e.g., age-appropriate sleep behaviors), system  300  may provide individualized recommendation based on artificial intelligence processes performed using the sensed data. System  300  may perform artificial intelligence operations to learn actual guardian and child (e.g., subject  345 ) behavior of users of system  300  and make recommendations to improve sleep hygiene based on the machine learning. System  300  may also update recommendations based on receiving current scientific research as described for example above. System  300  may provide feedback to users (e.g., a guardian of subject  345 ) at regular intervals or at any other desired times, and may prompt users to make behavioral changes (e.g., make changes to sleep hygiene practices as described for example herein). System  300  may also track and diagnose medical issues or sleep problems based on an operation of information module  335  as described for example herein. System  300  may also provide research study data (e.g., subject to authorization by users of system  300 , system  300  may provide data to external databases via network  301  for use in research studies and other activities to advance the sleep science field). After providing feedback at step  555 , system  300  may return to step  510 . 
     At step  560 , system  300  (e.g., subsystem  305 ) may determine whether system  300  should continue monitoring based on the data sensed at step  510  and processed and analyzed at step  515  and/or based on user input (e.g., input by a guardian of subject  345 ). If continuing monitoring is appropriate, system  300  may return to step  510 . If continuing monitoring is not appropriate, system  300  may proceed to step  565 , ending process  500  (e.g., ending monitoring of a sleep session). 
     Any suitable steps of process  500  may be performed simultaneously by system  300 . For example, system  300  may perform steps  510 ,  515 ,  525 ,  535 ,  545 , and/or  555  simultaneously. Also for example, system  300  may proceed directly from any of steps  520 ,  530 ,  540 , and  550  to any other one of steps  520 ,  530 ,  540 , and  550 . For example, system  300  may simultaneously sense data at step  510 , process data at step  515 , and perform any of steps  525 ,  535 ,  545 , and/or  555  in any desired order (e.g., or perform any desired steps simultaneously). 
       FIG. 6  illustrates another exemplary process of the exemplary disclosed apparatus, system, and method. Process  600  starts at step  605 . Steps  610  and  615  may be similar, respectively, to steps  510  and  515 . Steps  620  and  625  may be similar, respectively, to steps  520  and  525 . Steps  630  and  635  may be similar, respectively, to steps  540  and  545 . Steps  640  and  645  may be similar, respectively, to steps  560  and  565 . 
       FIGS. 5 and 6  illustrate different exemplary modes of operation of system  300 . For example, process  500  may be a first mode of operation during which guardians of subject  345  are awake. For example, process  500  may be a mode of operation used during daytime naptimes of subject  345  and/or morning or evening times when guardians are awake. Process  600  may be a mode of operation used during late night or early morning periods when guardians of subject  345  are asleep and/or otherwise desire system  300  to operate in a mode consistent with process  600 . For example, when guardians of subject  345  are awake (e.g., during an operation of process  500 ), system  300  may issue alerts at step  525 , provide updates at step  535 , control devices at step  545 , and/or provide feedback at step  555 . When guardians of subject  345  are asleep or desire system  300  to operate in a modified mode (e.g., an operation of process  600 ), system  300  may issue alerts at step  625  and control devices at step  635 , but may not provide updates and/or provide feedback (e.g., but may provide such updates and/or feedback based on data sensed and processed during steps  610  and  615  once system  300  has changed its operation back to process  500 ). 
     System  300  may switch between a mode of operation of process  500  and a mode of operation of process  600  based on input by a guardian, predetermined time periods during the day, and/or based on data processing by system  300 . For example, system  300  may switch between modes of operation (e.g., between process  500  and  600 ) based on biometric data of a guardian of subject  345  as described for example above. For example, when system  300  determines that a guardian has gone to sleep based on processing sensed biometric data of the guardian, system  300  may switch from process  500  to process  600 . 
     In at least some exemplary embodiments, the exemplary disclosed system may include a sleep pattern module, comprising computer-executable code stored in non-volatile memory, a processor, a sensor array (e.g., sensor array  310 ) and a device array (e.g., device array  315 ). The sleep pattern module, the processor, the sensor array, and the device array may be configured to sense data of a sleep subject using the sensor array, process the sensed data, issue an alert to a guardian of the sleep subject based on the processed data, control the device array based on the processed data, and provide sleep pattern modification recommendations to the guardian of the sleep subject based on the processed data. The sensor array may include one or more sensors selected from the group consisting of a camera, a microphone, a biometric sensor, a support sensor, an ambient condition sensor, and a medical sensor. The sensor array may include a video camera, a microphone, a heartrate sensor, and a breathing sensor. The sensor array may include a hygrometer and an ambient temperature sensor. The sensor array may include a medical sensor that senses a biometric attribute of the sleep subject. The device array may include one or more devices selected from the group consisting of a soothing device (e.g., a sound soother and/or a soother using vibration, motion and/or lighting effects), a lighting device, a thermostat, a television, a sound system, a doorbell, and a microwave. The device array may include a soothing device (e.g., a sound soother) that provides sound (e.g., and/or a soothing device that provides soothing lighting, vibration, and/or motion) in a sleep area in which the sleep subject is located, a lighting device that provides light in the sleep area, and a thermostat that controls a temperature in the sleep area and/or in bedding material itself (e.g., a heating or cooling mattress or blanket). The exemplary disclosed system may include a user interface configured to be controlled by the guardian of the sleep subject, wherein the user interface is selected from the group consisting of a smartphone, a smart speaker, and a tablet. The sleep subject may be a child, and the sleep pattern modification recommendations may be recommendations selected from the group consisting of a visual representation of the child&#39;s sleep cycle, the child&#39;s sleep-related development milestones, and recommended sleep pattern actions for the guardian of the child to take for the child&#39;s sleep hygiene. Processing the sensed data may include artificial intelligence operations that produce the sleep pattern modification recommendations. The sleep pattern module, the processor, the sensor array, and the device array may be configured to provide status information including the processed data to the guardian, and prompt the guardian to provide input based on the artificial intelligence operations. 
     In at least some exemplary embodiments, the exemplary disclosed method may include sensing data of a sleep subject using a sensor array, processing the sensed data, the processed data indicating whether the sleep subject is in a restless state or a deep sleep state, issuing an alert to a guardian of the sleep subject based on the processed data; and controlling a device array based on the processed data, the device array including a soothing device and a lighting device. The exemplary disclosed method may also include providing sleep pattern modification recommendations to the guardian of the sleep subject based on the processed data, activating the soothing device when the sleep subject is in the restless state, and varying a brightness of the lighting device when the sleep subject is in the deep sleep state. For example, a brightness of the lighting device may be increased to provide additional light for a visual device (e.g., camera) to record image data (e.g., higher resolution image data) while the sleep subject is sleeping. The device array may include a thermostat, a television, and a doorbell. The exemplary disclosed method may also include controlling the thermostat to be set at a first temperature when the sleep subject is in the restless state and controlling the thermostat to be at a second temperature that is different from the first temperature when the sleep subject is in the deep sleep state. The exemplary disclosed method may further include reducing an emitting volume of the television and the doorbell when the sleep subject is in the restless state. The exemplary disclosed system may additionally include activating an emergency medical system based on the processed data. 
     In at least some exemplary embodiments, the exemplary disclosed system may include a sleep pattern module, comprising computer-executable code stored in non-volatile memory, a processor, a sensor array, a device array, and a user interface. The sleep pattern module, the processor, the sensor array, and the device array may be configured to sense data of a sleep subject using the sensor array, process the sensed data, issue an alert to a guardian of the sleep subject based on the processed data, control the device array based on the processed data, and provide sleep pattern modification recommendations via the user interface to the guardian of the sleep subject based on the processed data. The sensor array may include a camera, a microphone, and a breathing sensor. The device array may include a soothing device, a lighting device, and a thermostat. The user interface may be selected from the group consisting of a smartphone, a smart speaker, and a tablet. The user interface may include an artificial intelligence chatbot. Processing the sensed data may include artificial intelligence operations that produce the sleep pattern modification recommendations. The sleep subject may be a child, and the sleep pattern modification recommendations may be recommendations selected from the group consisting of a visual representation of the child&#39;s sleep cycle, the child&#39;s sleep-related development milestones, and recommended sleep pattern actions for the guardian of the child to take for the child&#39;s sleep hygiene. 
     The exemplary disclosed apparatus, system, and method may provide sleep hygiene and safety information to a guardian of an infant or child that may be individualized to that infant or child. For example, the exemplary disclosed apparatus, system, and method may provide feedback and guidance to a parent or guardian of an infant or young child. The exemplary disclosed apparatus, system, and method may help improve a sleep duration, a timing of sleep, and/or sleep of children in order to improve the lives of both the children and the guardians of the children. The exemplary disclosed apparatus, system, and method may provide a low cost and high availability technique for providing feedback of a child&#39;s sleep cycle, which may be used by any user having for example a smartphone or similar computing device. 
     An illustrative representation of a computing device appropriate for use with embodiments of the system of the present disclosure is shown in  FIG. 7 . The computing device  100  can generally be comprised of a Central Processing Unit (CPU,  101 ), optional further processing units including a graphics processing unit (GPU), a Random Access Memory (RAM,  102 ), a mother board  103 , or alternatively/additionally a storage medium (e.g., hard disk drive, solid state drive, flash memory, cloud storage), an operating system (OS,  104 ), one or more application software  105 , a display element  106 , and one or more input/output devices/means  107 , including one or more communication interfaces (e.g., RS232, Ethernet, Wifi, Bluetooth, USB). Useful examples include, but are not limited to, personal computers, smart phones, laptops, mobile computing devices, tablet PCs, touch boards, and servers. Multiple computing devices can be operably linked to form a computer network in a manner as to distribute and share one or more resources, such as clustered computing devices and server banks/farms. 
     Various examples of such general-purpose multi-unit computer networks suitable for embodiments of the disclosure, their typical configuration and many standardized communication links are well known to one skilled in the art, as explained in more detail and illustrated by  FIG. 8 , which is discussed herein-below. 
     According to an exemplary embodiment of the present disclosure, data may be transferred to the system, stored by the system and/or transferred by the system to users of the system across local area networks (LANs) (e.g., office networks, home networks) or wide area networks (WANs) (e.g., the Internet). In accordance with the previous embodiment, the system may be comprised of numerous servers communicatively connected across one or more LANs and/or WANs. One of ordinary skill in the art would appreciate that there are numerous manners in which the system could be configured and embodiments of the present disclosure are contemplated for use with any configuration. 
     In general, the system and methods provided herein may be employed by a user of a computing device whether connected to a network or not. Similarly, some steps of the methods provided herein may be performed by components and modules of the system whether connected or not. While such components/modules are offline, and the data they generated will then be transmitted to the relevant other parts of the system once the offline component/module comes again online with the rest of the network (or a relevant part thereof). According to an embodiment of the present disclosure, some of the applications of the present disclosure may not be accessible when not connected to a network, however a user or a module/component of the system itself may be able to compose data offline from the remainder of the system that will be consumed by the system or its other components when the user/offline system component or module is later connected to the system network. 
     Referring to  FIG. 8 , a schematic overview of a system in accordance with an embodiment of the present disclosure is shown. The system is comprised of one or more application servers  203  for electronically storing information used by the system. Applications in the server  203  may retrieve and manipulate information in storage devices and exchange information through a WAN  201  (e.g., the Internet). Applications in server  203  may also be used to manipulate information stored remotely and process and analyze data stored remotely across a WAN  201  (e.g., the Internet). 
     According to an exemplary embodiment, as shown in  FIG. 8 , exchange of information through the WAN  201  or other network may occur through one or more high speed connections. In some cases, high speed connections may be over-the-air (OTA), passed through networked systems, directly connected to one or more WANs  201  or directed through one or more routers  202 . Router(s)  202  are completely optional and other embodiments in accordance with the present disclosure may or may not utilize one or more routers  202 . One of ordinary skill in the art would appreciate that there are numerous ways server  203  may connect to WAN  201  for the exchange of information, and embodiments of the present disclosure are contemplated for use with any method for connecting to networks for the purpose of exchanging information. Further, while this application refers to high speed connections, embodiments of the present disclosure may be utilized with connections of any speed. 
     Components or modules of the system may connect to server  203  via WAN  201  or other network in numerous ways. For instance, a component or module may connect to the system i) through a computing device  212  directly connected to the WAN  201 , ii) through a computing device  205 ,  206  connected to the WAN  201  through a routing device  204 , iii) through a computing device  208 ,  209 ,  210  connected to a wireless access point  207  or iv) through a computing device  211  via a wireless connection (e.g., CDMA, GMS, 3G, 4G) to the WAN  201 . One of ordinary skill in the art will appreciate that there are numerous ways that a component or module may connect to server  203  via WAN  201  or other network, and embodiments of the present disclosure are contemplated for use with any method for connecting to server  203  via WAN  201  or other network. Furthermore, server  203  could be comprised of a personal computing device, such as a smartphone, acting as a host for other computing devices to connect to. 
     The communications means of the system may be any means for communicating data, including image and video, over one or more networks or to one or more peripheral devices attached to the system, or to a system module or component. Appropriate communications means may include, but are not limited to, wireless connections, wired connections, cellular connections, data port connections, Bluetooth® connections, near field communications (NFC) connections, or any combination thereof. One of ordinary skill in the art will appreciate that there are numerous communications means that may be utilized with embodiments of the present disclosure, and embodiments of the present disclosure are contemplated for use with any communications means. 
     Traditionally, a computer program includes a finite sequence of computational instructions or program instructions. It will be appreciated that a programmable apparatus or computing device can receive such a computer program and, by processing the computational instructions thereof, produce a technical effect. 
     A programmable apparatus or computing device includes one or more microprocessors, microcontrollers, embedded microcontrollers, programmable digital signal processors, programmable devices, programmable gate arrays, programmable array logic, memory devices, application specific integrated circuits, or the like, which can be suitably employed or configured to process computer program instructions, execute computer logic, store computer data, and so on. Throughout this disclosure and elsewhere a computing device can include any and all suitable combinations of at least one general purpose computer, special-purpose computer, programmable data processing apparatus, processor, processor architecture, and so on. It will be understood that a computing device can include a computer-readable storage medium and that this medium may be internal or external, removable and replaceable, or fixed. It will also be understood that a computing device can include a Basic Input/Output System (BIOS), firmware, an operating system, a database, or the like that can include, interface with, or support the software and hardware described herein. 
     Embodiments of the system as described herein are not limited to applications involving conventional computer programs or programmable apparatuses that run them. It is contemplated, for example, that embodiments of the disclosure as claimed herein could include an optical computer, quantum computer, analog computer, or the like. 
     Regardless of the type of computer program or computing device involved, a computer program can be loaded onto a computing device to produce a particular machine that can perform any and all of the depicted functions. This particular machine (or networked configuration thereof) provides a technique for carrying out any and all of the depicted functions. 
     Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Illustrative examples of the computer readable storage medium may include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. 
     A data store may be comprised of one or more of a database, file storage system, relational data storage system or any other data system or structure configured to store data. The data store may be a relational database, working in conjunction with a relational database management system (RDBMS) for receiving, processing and storing data. A data store may comprise one or more databases for storing information related to the processing of moving information and estimate information as well one or more databases configured for storage and retrieval of moving information and estimate information. 
     Computer program instructions can be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner. The instructions stored in the computer-readable memory constitute an article of manufacture including computer-readable instructions for implementing any and all of the depicted functions. 
     A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. 
     Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing. 
     The elements depicted in flowchart illustrations and block diagrams throughout the figures imply logical boundaries between the elements. However, according to software or hardware engineering practices, the depicted elements and the functions thereof may be implemented as parts of a monolithic software structure, as standalone software components or modules, or as components or modules that employ external routines, code, services, and so forth, or any combination of these. All such implementations are within the scope of the present disclosure. In view of the foregoing, it will be appreciated that elements of the block diagrams and flowchart illustrations support combinations of means for performing the specified functions, combinations of steps for performing the specified functions, program instruction technique for performing the specified functions, and so on. 
     It will be appreciated that computer program instructions may include computer executable code. A variety of languages for expressing computer program instructions are possible, including without limitation C, C++, Java, JavaScript, assembly language, Lisp, HTML, Perl, and so on. Such languages may include assembly languages, hardware description languages, database programming languages, functional programming languages, imperative programming languages, and so on. In some embodiments, computer program instructions can be stored, compiled, or interpreted to run on a computing device, a programmable data processing apparatus, a heterogeneous combination of processors or processor architectures, and so on. Without limitation, embodiments of the system as described herein can take the form of web-based computer software, which includes client/server software, software-as-a-service, peer-to-peer software, or the like. 
     In some embodiments, a computing device enables execution of computer program instructions including multiple programs or threads. The multiple programs or threads may be processed more or less simultaneously to enhance utilization of the processor and to facilitate substantially simultaneous functions. By way of implementation, any and all methods, program codes, program instructions, and the like described herein may be implemented in one or more thread. The thread can spawn other threads, which can themselves have assigned priorities associated with them. In some embodiments, a computing device can process these threads based on priority or any other order based on instructions provided in the program code. 
     Unless explicitly stated or otherwise clear from the context, the verbs “process” and “execute” are used interchangeably to indicate execute, process, interpret, compile, assemble, link, load, any and all combinations of the foregoing, or the like. Therefore, embodiments that process computer program instructions, computer-executable code, or the like can suitably act upon the instructions or code in any and all of the ways just described. 
     The functions and operations presented herein are not inherently related to any particular computing device or other apparatus. Various general-purpose systems may also be used with programs in accordance with the teachings herein, or it may prove convenient to construct more specialized apparatus to perform the required method steps. The required structure for a variety of these systems will be apparent to those of ordinary skill in the art, along with equivalent variations. In addition, embodiments of the disclosure are not described with reference to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the present teachings as described herein, and any references to specific languages are provided for disclosure of enablement and best mode of embodiments of the disclosure. Embodiments of the disclosure are well suited to a wide variety of computer network systems over numerous topologies. Within this field, the configuration and management of large networks include storage devices and computing devices that are communicatively coupled to dissimilar computing and storage devices over a network, such as the Internet, also referred to as “web” or “world wide web”. 
     Throughout this disclosure and elsewhere, block diagrams and flowchart illustrations depict methods, apparatuses (e.g., systems), and computer program products. Each element of the block diagrams and flowchart illustrations, as well as each respective combination of elements in the block diagrams and flowchart illustrations, illustrates a function of the methods, apparatuses, and computer program products. Any and all such functions (“depicted functions”) can be implemented by computer program instructions; by special-purpose, hardware-based computer systems; by combinations of special purpose hardware and computer instructions; by combinations of general purpose hardware and computer instructions; and so on—any and all of which may be generally referred to herein as a “component”, “module,” or “system.” 
     While the foregoing drawings and description set forth functional aspects of the disclosed systems, no particular arrangement of software for implementing these functional aspects should be inferred from these descriptions unless explicitly stated or otherwise clear from the context. 
     Each element in flowchart illustrations may depict a step, or group of steps, of a computer-implemented method. Further, each step may contain one or more sub-steps. For the purpose of illustration, these steps (as well as any and all other steps identified and described above) are presented in order. It will be understood that an embodiment can contain an alternate order of the steps adapted to a particular application of a technique disclosed herein. All such variations and modifications are intended to fall within the scope of this disclosure. The depiction and description of steps in any particular order is not intended to exclude embodiments having the steps in a different order, unless required by a particular application, explicitly stated, or otherwise clear from the context. 
     The functions, systems and methods herein described could be utilized and presented in a multitude of languages. Individual systems may be presented in one or more languages and the language may be changed with ease at any point in the process or methods described above. One of ordinary skill in the art would appreciate that there are numerous languages the system could be provided in, and embodiments of the present disclosure are contemplated for use with any language. 
     It should be noted that the features illustrated in the drawings are not necessarily drawn to scale, and features of one embodiment may be employed with other embodiments as the skilled artisan would recognize, even if not explicitly stated herein. Descriptions of well-known components and processing techniques may be omitted so as to not unnecessarily obscure the embodiments. 
     It will be apparent to those skilled in the art that various modifications and variations can be made to the disclosed apparatus, system, and method. Other embodiments will be apparent to those skilled in the art from consideration of the specification and practice of the disclosed method and apparatus. It is intended that the specification and examples be considered as exemplary only, with a true scope being indicated by the following claims.