Patent Description:
The present disclosure relates generally to fire protection, and more particularly, to de-centralized fire protection.

A fire alarm system within a building is typically a closed/local system including initiating devices and notification devices connected to an on premise fire alarm control panel. The input from the initiating devices is processed by the fire alarm control panel using pre-configured algorithms to determine whether a detected device state triggers an event such as a fire. If an event is detected, the fire alarm control panel may activate one or more notification devices accordingly. However, the fire alarm control panel is a single point of failure of such conventional fire alarm systems. For example, if the fire alarm control panel becomes unavailable or malfunctions, the initiating and notification devices are no longer operational for detecting and/or warning against fire or other critical events.

Accordingly, improvements in fire protection systems are desired. <CIT> describes a device that may receive one or more environmental measurements associated with a workplace. The device may receive one or more physiological measurements associated with a worker. The one or more physiological measurements may be different from the one or more environmental measurements. The device may generate a safety score for the worker based on the one or more environmental measurements and the one or more physiological measurements. The device may provide information regarding the worker based on the safety score.

The present disclosure provides fire protection systems, apparatuses, and methods.

In an aspect, a method of cloud-based fire protection is provided as set out in claim <NUM>.

In a further aspect, a system for cloud-based fire protection is provided as set out in claim <NUM>.

In another aspect, a non-transitory computer-readable medium is provided as set out in claim <NUM>.

In some instances, well known components may be shown in block diagram form in order to avoid obscuring such concepts.

Aspects of the present disclosure provide methods, apparatuses, and systems that allow for de-centralized cloud-based fire protection functionality. In an aspect, for example, a de-centralized cloud-based fire protection system includes initiating devices that communicate with a cloud platform independently of one another through one or more paths, for example, over the Internet. Further, the cloud platform also communicates with one or more notification devices independently of one another through one or more paths, for example, over the Internet. Accordingly, the need for a fire alarm control panel is alleviated. Further, since the devices in the present system are coupled with a cloud platform through one or more hubs, routers, gateways, or some combination thereof, the system is not dependent on a single on premise processing node such as a fire alarm control panel, and therefore there is no single point of failure. Additionally, service level agreement of a cloud provider may be configured to guarantee a certain level of system availability, for example, up to <NUM>%, for data computing and data storage, thus ensuring high reliability in a de-centralized cloud-based fire protection system.

In an aspect, for example, the output or sensor value of each initiating device in the present de-centralized cloud-based fire protection system is sent to the cloud platform and is processed in the cloud platform according to an appropriate business logic. In this aspect, the cloud platform may be flexible to provide any required computing capacity. Additionally, the cloud platform may activate one or more notification devices in the de-centralized cloud-based fire protection system if the processing of the sensor values indicates a safety event, such as a fire event.

In an aspect, the cloud platform may further provide a persistent data storage for storing the raw sensor data received from the initiating devices. In an aspect, for example, the persistent data storage may store sufficient data over time to enable characterization of the environment where the initiating devices are located within the de-centralized cloud-based fire protection system. In an aspect, for example, the stored data may be analyzed to develop new fire detection/protection algorithms, and the data may be fed back into the de-centralized cloud-based fire protection system in order to adapt the fire detection/protection algorithm in real-time using machine learning capabilities in the cloud platform.

In an aspect, an initiating or notification device may be added to the de-centralized cloud-based fire protection system by configuring a communication pathway of the device to the Internet, instead of or in addition to configuring a local fire alarm control panel. For example, in an aspect, an initiating or notification device may be added to the de-centralized cloud-based fire protection system by configuring the device to connect to one or more hubs, routers, gateways, or some combination thereof that provide a wired or wireless connection to the Internet. In an aspect, for example, the initiating or notification device may be configured to connect to one or more hubs, routers, gateways, or some combination thereof over a wired connection, for example, using an Ethernet connection. Alternatively and/or additionally, the initiating or notification device may be configured to connect wirelessly to one or more hubs, routers, gateways, or some combination thereof, for example, using a wireless fidelity (WiFi) connection. Alternatively and/or additionally, an initiating or notification device may be configured to directly connect to the Internet, for example, using a cellular connection. In some aspects, an initiating or notification device may implement multiple redundant pathways for communicating over the Internet. For example, in one non-limiting aspect, an initiating or notification device may implement both an Ethernet connection to one or more hubs, routers, gateways, or some combination thereof, and a cellular connection to directly connect to the Internet. In aspects where multiple redundant pathways are implemented, the initiating or notification device may use one pathway by default, and then later switch to an alternative pathway in case of a failure of the default pathway. For example, in an aspect, the initiating or notification device may use an Ethernet connection by default, and then switch to a cellular connection in case of a failure of the Ethernet connection.

In an aspect, the de-centralized cloud-based fire protection system may provide safety event notifications, such as fire alarms, through one or more on premise audible and/or visual fire alarm notification devices. Alternatively and/or additionally, the de-centralized cloud-based fire protection system may provide safety event notifications through other devices such as a personal computer, a personal mobile phone, etc. For example, in an aspect, the de-centralized cloud-based fire protection system may provide safety event notifications including but not be limited to e-mail, short message service (SMS), mobile application notification, web application notification, notifications on an interface dashboard of the cloud platform, etc. In an aspect, the cloud platform may provide functionality to facilitate the integration of different types of notification devices such as on premise notification devices, personal computers, personal mobile phones, etc..

In an aspect, the de-centralized cloud-based fire protection system may be configured by retrofitting a conventional fire protection system. For example, a conventional fire protection system that includes physical connections from initiating and notification devices to a fire alarm control panel may be retrofitted such that the fire alarm control panel no longer processes the business logic of the fire protection system but is instead configured as a gateway to the Internet to couple the initiating and notification devices with a cloud platform that processes the business logic.

As compared to conventional fire alarm systems in which initiating and notification devices are connected to a fire alarm control panel that does not store device input, the present de-centralized cloud-based fire protection system allows for persistent storage of device input over time and for using the stored data for further analysis. Additionally, unlike the conventional fire alarm control panels which are a single point of failure in a conventional fire protection system, each device in the present de-centralized cloud-based fire protection system may independently communicate with the cloud platform and is therefore operable irrespective of the status of other devices/components in the de-centralized cloud-based fire protection system. Further, unlike conventional fire alarm control panels that have limited processing capability, the cloud platform in the present de-centralized cloud-based fire protection system can accommodate processing of complex business logic for a large number of devices. In addition, the present de-centralized cloud-based fire protection system has reduced manufacturing and storage cost, has reduced system parts for the initiating and notification devices, is easier to install and configure, has higher visibility and ease of use for fire system operations, has reduced maintenance cost, can facilitate future device integration, and can allow for further device data analysis, e.g., by using big data functionality.

Turning now to the figures, example aspects are depicted with reference to one or more components described herein, where components in dashed lines may be optional.

Referring to <FIG>, in one non-limiting aspect, a de-centralized cloud-based fire protection system <NUM> includes a cloud platform <NUM> that receives data from one or more initiating devices <NUM>, processes the data, and depending on the outcome of the processing, sends a safety event notification to one or more notification devices <NUM> and/or one or more emergency control devices <NUM> if needed. In an aspect, the initiating devices <NUM> may include, for example, on premise fire protection devices such as smoke detectors, manual stations, waterflow switches, sprinkler supervisory switches, or any other device configured for initiating a fire or other safety alarm by detecting a safety or fire condition.

In an aspect, the notification devices <NUM> may include, for example, audible devices, visible devices, or any other on premise fire/safety alarm device configured for warning the occupants of an area in case of a detected safety event. In an alternative and/or additional aspect, the notification devices <NUM> may further include personal devices such as personal computers, personal mobile devices, etc., that are configured for warning the user of the device in case of a detected safety event. In an aspect, the emergency control devices <NUM> may include, for example, ventilation system fans and/or dampers, door locks, hold open devices, a safety/alarm device configured at a fire department, or any other device configured for providing a notification and/or taking a mitigating action in response to a detected safety event.

In an aspect, the cloud platform <NUM> may communicate with the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> over the Internet, e.g., by implementing communication according to one or more protocols in the Internet protocol suit, or transmission control protocol / internet protocol (TCP/IP). In an aspect, for example, one or more of the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> may be an Internet of Things (IoT) device capable of independently establishing communication with the cloud platform <NUM> over the Internet. Alternatively and/or additionally, one or more of the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> may connect to the Internet via one or more hubs, routers, gateways, or some combination thereof, and may thus have a wired or wireless connection to one or more hubs, routers, gateways, or some combination thereof, for example, via WiFi, Ethernet, etc. Alternatively and/or additionally, one or more of the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> may connect to the Internet via a cellular communication. Accordingly, each one of the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> may communicate with the cloud platform <NUM> over the Internet via one or more direct or indirect communication paths.

In an aspect, various network topologies may be implemented to allow for each of the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> to connect to the Internet to communicate with the cloud platform <NUM>. For example, in one non-limiting aspect, one or more of the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> may communicate with the cloud platform <NUM> in a star topology through one or more hubs, routers, gateways, or some combination thereof that provide access to the Internet. Alternatively, in another non-limiting aspect, one or more of the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> may form a mesh network to relay messages among each other and connect to the Internet.

In an aspect, the communication path between an initiating device <NUM> and the cloud platform <NUM> may allow for the transmission of sensor outputs of the initiating device <NUM> to the cloud platform <NUM>. In an aspect, the communication path between a notification device <NUM> and the cloud platform <NUM> may allow for the transmission of requests from the cloud platform <NUM> to activate the notification device <NUM>. In an aspect, each one of the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> may be associated with a physical location. In an aspect, one or more of the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> may be logically grouped together based on their respective physical location. For example, one or more of the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> may be logically grouped together at different levels of granularity, for example, by zone, building floor, building section, building, building complex, campus, etc. Accordingly, one or more of the initiating devices <NUM>, the notification devices <NUM>, and/or the emergency control devices <NUM> may communicate with the cloud platform <NUM> to collectively provide a fire alarm system associated with a geographical or logical system without the need for association with a specific local fire panel control unit.

In an aspect, an initiating device <NUM> may be a digital sensor device, for example, a manual pull station. In this case, the initiating device <NUM> may provide digital device values to the cloud platform <NUM>. In response, the cloud platform <NUM> may perform data and event processing <NUM> to aggregate and/or filter the digital device values received from the initiating device <NUM> and then send the filtered and/or aggregated digital device values to other components of the cloud platform <NUM> such as a persistent data storage <NUM>, a system control interface <NUM>, and/or for rules and logic processing <NUM>. For example, in an aspect, the rules and logic processing <NUM> performed on the output of the data and event processing <NUM> may include triggering an immediate state change associated with the initiating device <NUM>. The rules and logic processing <NUM> may then determine whether to generate a safety event. If a safety event is generated, a notification service <NUM> of the cloud platform <NUM> may send corresponding notifications to one or more notification devices <NUM> and/or emergency control devices <NUM>. For example, the cloud platform <NUM> may activate the notification functionality of one or more notification devices <NUM>, and/or may activate a safety event mitigating functionality of an emergency control devices <NUM>.

In an aspect, an initiating device <NUM> may be an analog sensor device, for example, a smoke detector or a pressure sensor. In this case, the initiating device <NUM> may provide analog device values to the cloud platform <NUM>. In response, the cloud platform <NUM> may perform data and event processing <NUM> on the analog device values received from the initiating devices <NUM>. For example, in an aspect, the data and event processing <NUM> may filter and/or aggregate the analog device values received from the initiating devices <NUM> and then send the filtered and/or aggregated analog device values to other components of the cloud platform <NUM> such as the persistent data storage <NUM>, the system control interface <NUM>, and/or for the rules and logic processing <NUM>.

For example, in an aspect, the cloud platform <NUM> may perform the rules and logic processing <NUM> on the output of the data and event processing <NUM> by comparing the analog device values against a configurable threshold range/value to trigger a state change associated with the initiating device <NUM> if the analog device values are not within an acceptable range. In an aspect, the threshold value may be configured manually or may be computed using machine learning <NUM> and configured automatically by the cloud platform <NUM>.

Alternatively and/or additionally, for example, in an aspect, the cloud platform <NUM> may perform the rules and logic processing <NUM> on the output of the data and event processing <NUM> by identifying a signal pattern of the analog device values to trigger a state change associated with the initiating device <NUM> if the signal pattern of the analog device values matches a pattern associated with a safety event. In an aspect, the signal pattern of the analog device values may be identified, for example, by applying signal processing techniques such as pattern recognition on the analog device values. In an aspect, for example, the patterns associated with safety events may be configured/stored manually or may be computed using machine learning <NUM> and configured automatically by the cloud platform <NUM> based on historical event and/or sensor data stored in the persistent data storage <NUM>.

In response to a triggered state change, the rules and logic processing <NUM> may determine whether to generate a corresponding safety event. If a safety event is generated, a notification service <NUM> of the cloud platform <NUM> may send corresponding notifications to one or more notification devices <NUM> and/or emergency control devices <NUM>.

In an alternative aspect, an initiating device <NUM> may be an intelligent analog sensor device that generates analog device values and also has processing capability to locally process the analog device values against a configurable threshold to detect a state change. In this aspect, the initiating device <NUM> may send the state change along with the analog device values to the cloud platform <NUM>. Again, the threshold value may be configured manually or may be computed using machine learning <NUM> and configured automatically by the cloud platform <NUM>.

In an aspect, the cloud platform <NUM> may generate one or more events by processing the received sensor data by performing rules and logic processing <NUM> according to business rules and logic. The rules and logic processing <NUM> may indicate which notification devices <NUM> need to be activated in case of an event, and the cloud platform <NUM> may trigger such notification devices <NUM> accordingly. In an aspect, the notification devices <NUM> may receive activation commands from the cloud platform <NUM> through similar communication path(s) used by the initiating devices <NUM>, e.g., Wi-Fi, Ethernet, cellular communication, etc. The rules and logic processing <NUM> may also trigger a cascade of actions including but not limited to sending notifications by e-mail, SMS, mobile application, and/or directly to a central monitoring station. Alternatively and/or additionally, for example, in an aspect, the rules and logic processing <NUM> may trigger the cloud platform <NUM> to send notifications/requests to other services such as fire and rescue, ambulance, etc..

In an aspect, the cloud platform <NUM> may provide a persistent data storage <NUM> for storing the raw data received from the initiating devices <NUM>. In an aspect, for example, the persistent data storage <NUM> may store sufficient data over time to enable characterization of the environment where the initiating devices <NUM> are located within the de-centralized cloud-based fire protection system <NUM>. In an aspect, the data analysis may be used to develop new fire detection/protection algorithms, and the data may be provided as feed back into the de-centralized cloud-based fire protection system <NUM> in order to adapt the fire detection/protection algorithm in real-time using machine learning <NUM> in the cloud platform <NUM>. In an aspect, the data stored in the persistent data storage <NUM> may further be used for obtaining business intelligence <NUM> about the environment that is protected by the de-centralized cloud-based fire protection system <NUM>. For example, in an aspect, the business intelligence <NUM> may provide information for making business decisions related to the environment that is protected by the de-centralized cloud-based fire protection system <NUM>.

In an aspect, the cloud platform <NUM> may continuously and/or periodically monitor the connectivity of the initiating devices <NUM> and the notification devices <NUM> to the cloud platform <NUM> and ensure that device connections are reported within an acceptable time limit. For example, in one non-limiting aspect, the cloud platform <NUM> may require that one or more of the initiating devices <NUM> or the notification devices <NUM> provide a respective connectivity report every <NUM> to <NUM> seconds. In an aspect, for example, a regulatory entity may provide rules that define the maximum allowed time limit for detecting a device communication fault that needs to be reported on premise.

In an aspect, the cloud platform <NUM> may detect a loss of connection if an initiating devices <NUM> or a notification devices <NUM> fails to provide a connectivity report within an acceptable time limit. In response to detecting a loss of connection, the cloud platform <NUM> may report the loss, for example, as a trouble/fault event transmitted to a remote annunciator <NUM> coupled with the cloud platform <NUM> via a system control interface <NUM> of the cloud platform <NUM>. In an aspect, for example, the remote annunciator <NUM> may be an on premise remote front panel annunciator configured to display system status information and/or allow for remote control of the de-centralized cloud-based fire protection system <NUM>, and the trouble/fault event may indicate that the disconnected device requires attention/maintenance. In one non-limiting aspect, for example, the remote annunciator <NUM> may include a liquid crystal display (LCD), a light-emitting diode (LED), etc., configured for providing alphanumeric status information. The remote annunciator <NUM> may also include one or more switches/buttons configured for providing system control functionality.

In an aspect, the system control interface <NUM> provides an interface for interacting with the cloud platform <NUM>. For example, in an aspect, the system control interface <NUM> may couple the cloud platform <NUM> with a web/desktop application <NUM> running in a personal computer <NUM> and/or a mobile application <NUM> running on a mobile device <NUM> such that a user may configure or monitor the de-centralized cloud-based fire protection system <NUM> via the web/desktop application <NUM> and/or the mobile application <NUM>, for example, as described below with reference to <FIG>. In one non-limiting aspect, for example, the mobile device <NUM> may be a handheld device carried by a user or a safety personnel.

Unlike conventional fire alarm systems where a device malfunction or a broken physical connection to an on premise fire alarm control panel affects the operation and reduces the quality of service of the remaining devices on the system, each initiating device <NUM> and notification device <NUM> in the present aspects operates independently and therefore a malfunction of one device does not affect the entire de-centralized cloud-based fire protection system <NUM>. More specifically, in a conventional fire alarm system, multiple devices may be configured on a physical connection ring connected to an on premise fire alarm control panel, and the integrity of communication over the ring is dependent on the integrity of each device comprising the ring. Therefore, a malfunction of a device configured on a ring may affect the operation of the other devices configured on that same ring. However, in the present de-centralized cloud-based fire protection system <NUM>, each initiating device <NUM> and notification device <NUM> may independently communicate with the cloud platform <NUM>. Therefore, a malfunction of one device does not affect the operation of a set of other devices. Further, in an aspect, each initiating device <NUM> and notification device <NUM> may be configured to use two or more different communication paths to the cloud platform <NUM> to ensure the connectivity of that device. For example, in one non-limiting aspect, a device may be configured with a default Ethernet connection and a back-up cellular connection, and in case an entire building Ethernet network malfunctions or goes down, the device may switch from the Ethernet connection to the cellular connection as a redundant communication path to the cloud platform <NUM> to ensure continued operation of the device.

Referring now to both <FIG> and <FIG>, in an aspect, the cloud platform <NUM> may be flexibly accessible and/or configurable via a user interface <NUM> including a menu <NUM> that allows for selecting a dashboard <NUM> for viewing various system status information. The menu <NUM> may further allow for selecting other options, e.g., to view/configure devices, rules and actions, maintenance, etc..

In an aspect, for example, at least a portion of the functionality of the user interface <NUM> may be accessible on a web/desktop application <NUM> executed on a personal computer <NUM>. Alternatively and/or additionally, at least a portion of the functionality of the user interface <NUM> may be accessible on a mobile application <NUM> executed on a mobile device <NUM>. Alternatively and/or additionally, at least a portion of the functionality of the user interface <NUM> may be accessible on a remote annunciator <NUM>.

For example, in an aspect, the web/desktop application <NUM> on the personal computer <NUM> may be configured with restricted accessibility for authorized personnel, and various configuration settings of the de-centralized cloud-based fire protection system <NUM> may be adjustable by a user via the user interface <NUM> on the web/desktop application <NUM> on such a personal computer <NUM> that is protected by having restricted accessibility. Alternatively and/or additionally, different mobile applications <NUM> may be available to different user types associated with the mobile device <NUM>. For example, in an aspect, a user may be provided the required access privileges to interact with the de-centralized cloud-based fire protection system <NUM> through the user interface <NUM> on a mobile application <NUM> running on a mobile device <NUM> associated with that user. Such flexible interfaces of the cloud platform <NUM> may allow for various existing and future applications to interact with the de-centralized cloud-based fire protection system <NUM> while ensuring highly secured access to the sensitive data stored on the cloud platform <NUM> to preserve data integrity.

In an aspect, the dashboard <NUM> may be accessed via one or more of the web/desktop application <NUM>, the mobile application <NUM>, or the remote annunciator <NUM> to view various system status information based on historical data trends of sensor values received by the cloud platform <NUM> from the initiating devices <NUM>, historical safety or other events generated by the cloud platform <NUM>, etc. For example, the dashboard <NUM> may provide a device location map <NUM>, a sensor value trend graph over time <NUM>, system alarms <NUM>, system key performance indicators (KPI) <NUM>, etc. For example, in an aspect, the system alarms <NUM> may provide detail information about various alarms triggered/generated by the cloud platform <NUM>, such as fire alarms, dirty detectors, etc., and the detail information for each alarm may include, for example, a corresponding rule name, severity, last incident, open occurrences, etc. Further, for example, in an aspect, the system KPI <NUM> may provide information/statistics that characterize an overall performance of the de-centralized cloud-based fire protection system <NUM>, such as top rules triggered, alarms by device type, percentage of critical alarms, etc..

In an aspect, the cloud platform <NUM> may combine data received from various initiating devices <NUM> of the de-centralized cloud-based fire protection system <NUM> with other types of available sensory input such as video camera feeds, heating, ventilation, and air conditioning (HVAC) temperature and pressure sensors, human input for validation of safety or other events, etc. For example, in one non-limiting aspect, when a fire event is triggered, the fire event may be validated/confirmed by fire personnel/authorities, for example, via the dashboard <NUM> and/or via the remote annunciator <NUM>.

For example, in one non-limiting aspect, the confirmation/validation of a triggered fire event may be performed locally on site via the remote annunciator <NUM> when the fire department responds to the event. For example, when the fire department personnel arrive on site and determine that the triggered fire event is a false alarm, the fire department personnel may reset the de-centralized cloud-based fire protection system <NUM> and also acknowledge through the remote annunciator <NUM> that the triggered fire event is a false alarm, i.e., invalidate the triggered fire event. In this case, the remote annunciator <NUM> may send the validation information back to de-centralized cloud-based fire protection system <NUM>.

In an aspect, the validation information may be stored along with other sensory inputs of the de-centralized cloud-based fire protection system <NUM> at the time of the fire event. Thereafter, the cloud platform <NUM> may process the combined stored data and validation information, for example, using machine learning <NUM>, to improve the confidence level of a corresponding predictive detection model that generated the fire event. For example, the processing may result in reduced false alarms and/or generate a new model for predictive fire detection. In an aspect, for example, the new predictive fire detection model may improve evacuation time by generating pre-emptive alarms by comparing past input data history from multiple sources of a previous fire event with current input data that indicates the inevitability of an actual fire event.

According to the invention, the cloud platform <NUM> applies machine learning <NUM> on sensory data received from various devices across different geographical locations/climates, e.g., desert, tropical, urban, etc., and may adapt the predictive detection model to the environmental conditions specific to a specific location where the de-centralized cloud-based fire protection system <NUM> is installed. According to the invention, the cloud platform <NUM> continues to obtain and analyze data from additional fire alarm systems to continually improve the predictive detection model.

According to the invention, the cloud platform <NUM> applies machine learning <NUM> on data stored in the persistent data storage <NUM> to associate certain sensor input values/trends with specific types of fire. For example, in an aspect, based on applying machine learning <NUM> on historical sensor and event data in the persistent data storage <NUM>, the cloud platform <NUM> may determine that certain sensor input is associated with a non-threatening event, such as the lighting of an e-cigarette. In response, the cloud platform <NUM> adjusts the predictive detection algorithm accordingly. For example, the cloud platform <NUM> adjusts an event detection threshold in the predictive detection model to prevent the generation of an alarm when similar sensor input is received in the future. According to the invention, the cloud platform <NUM> performs the above-noted adjustments based on applying machine learning <NUM> on aggregated data from multiple devices in multiple fire protection systems/environments to reduce false alarms.

Referring to <FIG>, a computing device <NUM> may implement all or a portion of the functionality described in <FIG> and <FIG> above or described in <FIG> below. For example, the computing device <NUM> may be or may include at least a portion of the initiating devices <NUM>, the cloud platform <NUM>, the notification devices <NUM>, the emergency control devices <NUM>, the personal computer <NUM>, the remote annunciator <NUM>, the mobile device <NUM>, or any other component described herein with reference to <FIG> above. The computing device <NUM> includes a processor <NUM> which may be configured to execute or implement software, hardware, and/or firmware modules that perform any functionality described herein with reference to <FIG> and <FIG> above or with reference to <FIG> below. For example, the processor <NUM> may be configured to execute or implement software, hardware, and/or firmware modules that perform any functionality described herein with reference to the initiating devices <NUM>, the cloud platform <NUM>, the notification devices <NUM>, the emergency control devices <NUM>, the personal computer <NUM>, the remote annunciator <NUM>, the mobile device <NUM>, or any other component/system/device described herein with reference to <FIG> and <FIG> above.

The processor <NUM> may be a micro-controller, an application-specific integrated circuit (ASIC), or a field-programmable gate array (FPGA), and/or may include a single or multiple set of processors or multi-core processors. Moreover, the processor <NUM> may be implemented as an integrated processing system and/or a distributed processing system. The computing device <NUM> may further include a memory <NUM>, such as for storing local versions of applications being executed by the processor <NUM>, related instructions, parameters, etc. The memory <NUM> may include a type of memory usable by a computer, such as random access memory (RAM), read only memory (ROM), tapes, magnetic discs, optical discs, volatile memory, non-volatile memory, and any combination thereof. Additionally, the processor <NUM> and the memory <NUM> may include and execute an operating system executing on the processor <NUM>, one or more applications, display drivers, etc., and/or other components of the computing device <NUM>.

Further, the computing device <NUM> may include a communications component <NUM> that provides for establishing and maintaining communications with one or more other devices, parties, entities, etc. utilizing hardware, software, and services. The communications component <NUM> may carry communications between components on the computing device <NUM>, as well as between the computing device <NUM> and external devices, such as devices located across a communications network and/or devices serially or locally coupled with the computing device <NUM>. In an aspect, for example, the communications component <NUM> may include one or more buses, and may further include transmit chain components and receive chain components associated with a wireless or wired transmitter and receiver, respectively, operable for interfacing with external devices.

Additionally, the computing device <NUM> may include a data store <NUM>, which can be any suitable combination of hardware and/or software, that provides for mass storage of information, databases, and programs. For example, the data store <NUM> may be or may include a data repository for applications and/or related parameters not currently being executed by processor <NUM>. In addition, the data store <NUM> may be a data repository for an operating system, application, display driver, etc., executing on the processor <NUM>, and/or one or more other components of the computing device <NUM>.

The computing device <NUM> may also include a user interface component <NUM> operable to receive inputs from a user of the computing device <NUM> and further operable to generate outputs for presentation to the user (e.g., via a display interface to a display device). The user interface component <NUM> may include one or more input devices, including but not limited to a keyboard, a number pad, a mouse, a touch-sensitive display, a navigation key, a function key, a microphone, a voice recognition component, or any other mechanism capable of receiving an input from a user, or any combination thereof. Further, the user interface component <NUM> may include one or more output devices, including but not limited to a display interface, a speaker, a haptic feedback mechanism, a printer, any other mechanism capable of presenting an output to a user, or any combination thereof.

<FIG> is a flowchart of a method <NUM> of operation of the computing device <NUM>. The method <NUM> may implement the functionality described herein with reference to <FIG> above, and may be performed by one or more components of the computing device <NUM> or any device/component described herein with reference to <FIG> above.

At <NUM> the method <NUM> includes receiving, by a cloud platform, data from one or more initiating devices. For example, in an aspect, the cloud platform <NUM> receives data from one or more of the initiating devices <NUM>. According to the invention, the one or more initiating devices includes one or more on premise fire protection devices, such as smoke detectors. Optionally, in an aspect, for example, the one or more initiating devices <NUM> may communicate with the cloud platform <NUM> over the Internet.

Optionally, in an aspect, for example, the cloud platform <NUM> may receive raw sensor data from the one or more initiating devices <NUM>. For example, the initiating device <NUM> may be a digital sensor device such as a manual pull station, and the cloud platform <NUM> may receive digital device values from the digital initiating device <NUM>.

Optionally, in an aspect, for example, the initiating device <NUM> may be an analog sensor device such as a smoke detector. In this case, the cloud platform <NUM> may also receive processed data generated by processing the raw sensor data by the initiating device <NUM> or by one or more hubs, routers, gateways, or some combination thereof that couple the one or more initiating devices <NUM> with the cloud platform <NUM>.

At <NUM> the method <NUM> includes storing the data in a persistent data storage of the cloud platform over a period of time. For example, in an aspect, the cloud platform <NUM> may store the data received from the initiating devices <NUM> in the persistent data storage <NUM> over a period of time.

At <NUM> the method <NUM> includes applying machine learning to the data to build or adjust a predictive detection model. For example, in an aspect, the cloud platform <NUM> may apply machine learning <NUM> to the data stored in the persistent data storage <NUM> to build or adjust a predictive detection model used to implement fire protection functionality in the de-centralized cloud-based fire protection system <NUM>.

In one aspect, for example, the machine learning <NUM> may further receive human input regarding validation/invalidation of a safety event, for example, via the dashboard <NUM> and/or via the remote annunciator <NUM>. In response, the machine learning <NUM> may be trained in order to adjust the predictive detection model based on the available sensor and/or validation data and/or other historical data stored in the persistent data storage <NUM>. In an aspect, for example, the machine learning <NUM> may implement a feedback loop where absence of human input/validation is considered a true event while an invalidation by human input is considered a false event, and the machine learning <NUM> may use the feedback loop to adjust the predictive detection model accordingly.

Optionally, in an aspect, for example, the cloud platform <NUM> may apply machine learning to the data received from the initiating devices <NUM> and to other data received from other devices configured in a different geographical or logical system than the initiating devices <NUM>. For example, in an aspect, the cloud platform <NUM> may apply machine learning <NUM> to a combination of data received from the initiating devices <NUM> associated with a geographical or logical system, such as the de-centralized cloud-based fire protection system <NUM>, as well as data received from other devices configured in a different geographical or logical system, a different floor, zone, building, etc., as compared to the initiating devices <NUM>.

Optionally, in an aspect, for example, the cloud platform <NUM> may apply machine learning to extract a pattern indicative of a type of fire, and then adjust a fire event detection threshold of the predictive detection model based on the pattern. For example, in an aspect, the cloud platform <NUM> may apply machine learning <NUM> on the data accumulated in the persistent data storage <NUM> over time to extract a pattern indicative of a type of fire, and then adjust a corresponding fire event detection threshold of the predictive detection model based on the pattern. For example, in an aspect, based on applying machine learning <NUM> on historical sensor and event data in the persistent data storage <NUM>, the cloud platform <NUM> may determine that certain sensor input is associated with a non-threatening event, such as the lighting of an e-cigarette. In response, the cloud platform <NUM> may adjust an event detection threshold in the predictive detection model to prevent the generation of a fire alarm when similar sensor input is received in the future. Accordingly, the cloud platform <NUM> may reduce the likelihood of generating a false alarm.

At <NUM> the method <NUM> includes processing, by computing resources of the cloud platform, the data using the predictive detection model to determine an existence of a safety event. For example, in an aspect, the computing resources of the cloud platform <NUM> may be used to process the data received from the initiating devices <NUM> using the machine learning-trained predictive detection model to determine an existence of a safety event such as a fire event. For example, in an aspect, the computing resources of the cloud platform <NUM> may be used to implement data and event processing <NUM> and/or rules and logic processing <NUM> to process the data using the predictive detection model to determine an existence of a safety event such as a fire event.

Optionally, in an aspect, for example, the cloud platform <NUM> may process the data by comparing the data against an event threshold or identifying a signal pattern of the data, and determining the existence of the safety event in response to the comparing or the identifying. For example, in an aspect, the cloud platform <NUM> may perform rules and logic processing <NUM> on analog device values received from an analog initiating device <NUM> and compare the analog device values against a configurable threshold range to trigger a state change associated with the initiating device <NUM> if the analog device values are not within an acceptable range. In an aspect, the threshold value may be configured manually or may be computed using machine learning <NUM> and configured automatically by the cloud platform <NUM>. Alternatively and/or additionally, for example, in an aspect, the rules and logic processing <NUM> may identify a signal pattern of the analog device values to trigger a state change associated with the initiating device <NUM> if the signal pattern of the analog device values matches a pattern associated with a safety event. In response to a triggered state change based on comparing the analog device values with a threshold and/or based on identifying a pattern in the analog signal values, the rules and logic processing <NUM> may determine whether to generate a corresponding safety event.

At <NUM> the method <NUM> includes transmitting, to at least one notification device, an event notification in response to the existence of the safety event. For example, in an aspect, the cloud platform <NUM> may transmit, to at least one notification device <NUM>, an event notification in response to the existence of the safety event. Optionally, in an aspect, for example, the cloud platform <NUM> may communicate with the notification device(s) <NUM> over the Internet. Optionally, in an aspect, for example, the cloud platform <NUM> may transmit the event notification to a remote annunciator <NUM>. Alternatively and/or additionally, for example, in another optional aspect, the cloud platform <NUM> may transmit the event notification to a personal computer or a personal mobile device. Optionally, in an aspect, for example, the event notification may include one or more of an email, a text message, a mobile push notification, etc..

Optionally, in an aspect, for example, the method <NUM> may further include receiving, via an interface of the cloud platform, a user input indicating an invalidation of the safety event, and adjusting a corresponding event detection threshold in the predictive detection model in response to the invalidation. For example, in an aspect, a safety event generated by the cloud platform <NUM> may be identified by a user/supervisor as being a false alarm. In this case, the user/supervisor may use the dashboard <NUM> to invalidate the safety event and indicate the safety event to be a false alarm. In response, the cloud platform <NUM> may adjust a corresponding threshold in the predictive detection model to reduce the likelihood of generating a similar false alarm in the future.

Optionally, in an aspect, for example, the method <NUM> may further include monitoring a connectivity of the one or more initiating devices and the at least one notification device with the cloud platform, and generating a lost connectivity indication when the connectivity is lost. For example, in an aspect, the cloud platform <NUM> may monitor a connectivity of the initiating devices <NUM> and the notification devices <NUM> with the cloud platform <NUM>, and may generate a lost connectivity indication when the connectivity is lost. Optionally, in an aspect, for example, the lost connectivity indication may include one or more of an audible alarm, a visual alarm, a text message, an email, etc. For example, the cloud platform <NUM> may generate a lost connectivity indication by activating an audible or visual on premise fire alarm notification device <NUM>, by causing an audible, visual, and/or textual alarm on the dashboard <NUM> (<FIG>), or by sending an email or text message to a personal notification device <NUM> such as a mobile or other personal device. Alternatively and/or additionally, the cloud platform <NUM> may generate a lost connectivity indication by transmitting a trouble event to a remote annunciator <NUM> coupled with the cloud platform <NUM> via the system control interface <NUM>.

Accordingly, for example, in an aspect, the cloud platform <NUM> may warn the user and/or the safety personnel by causing an audible, visual, and/or textual alarm on the dashboard <NUM> (<FIG>) provided on the remote annunciator <NUM>, the personal computer <NUM>, or the mobile device <NUM> carried by and/or otherwise accessible by the user/safety personnel. Alternatively and/or additionally, the cloud platform <NUM> may warn the user and/or the safety personnel by sending an email or text message to a personal notification device <NUM> such as a mobile or other personal device of the user and/or the safety personnel.

Optionally, in an aspect, for example, the cloud platform <NUM> may determine the connectivity based on a regularity of reception of the data from the one or more initiating devices <NUM>. For example, in an aspect, an initiating device <NUM> may be configured/expected to send periodic/regular sensor data to the cloud platform <NUM>. In this case, the cloud platform <NUM> may monitor the connectivity of the initiating device <NUM> based on a regularity/periodicity of the reception of the sensor data from the initiating device <NUM>, and may determine that connectivity with the initiating device <NUM> is lost when the initiating device <NUM> fails to send regular/periodic sensor data to the cloud platform <NUM>.

Optionally, in an aspect, for example, the cloud platform <NUM> may determine the connectivity based on a periodic status report from the one or more initiating devices <NUM> or from the at least one notification device <NUM>. For example, in an aspect, an initiating device <NUM> or a notification device <NUM> may be configured/expected to send periodic/regular operational status updates to the cloud platform <NUM>. In an aspect, the operational status update may indicate an operational status of the initiating device <NUM> or the notification device <NUM>, e.g., whether device self-tests have been successful. Alternatively and/or additionally, the status update may be dedicated for connectivity reporting of the initiating device <NUM> or the notification device <NUM>. In either case, the cloud platform <NUM> may monitor the connectivity of the initiating device <NUM> or the notification device <NUM> based on a periodicity/regularity of the reception of the status updates from the initiating device <NUM> or from the notification device <NUM>. In an aspect, the cloud platform <NUM> may determine that connectivity with the initiating device <NUM> or the notification device <NUM> is lost when the initiating device <NUM> or the notification device <NUM> fails to timely send the periodic/regular status updates to the cloud platform <NUM>.

Claim 1:
A method of cloud-based fire protection, comprising:
receiving, by a cloud platform (<NUM>), data from one or more on premises fire protection devices (<NUM>);
storing the data in a persistent data storage (<NUM>) of the cloud platform over a period of time;
applying machine learning (<NUM>) to the data received from the one or more on premises fire protection devices and to other data received from other on premises fire protection devices configured in a different geographical or logical system than the one or more on premises fire protection devices, to build or adjust a predictive detection model;
extracting a pattern indicative of a type of fire based on the data and the other data;
adjusting a fire event detection threshold of the predictive detection model based on the pattern;
processing, by computing resources of the cloud platform, the data using the predictive detection model to determine an existence of a safety event; and
transmitting, to at least one notification device (<NUM>, <NUM>, <NUM>, <NUM>), an event notification in response to the existence of the safety event.