Systems and methods for thermostat controlled fire detection

Abstract

Disclosed are systems and methods that provide a novel framework for a multi-sensor verification framework for which thermostat integration with smoke detection systems can provide improved mechanisms for fire detection, improving both accuracy and reliability. The disclosed framework leverages the data gathered from multiple environmental sensors embedded in modern thermostats to verify fire events, reducing the likelihood of false positives and enhancing early detection. The framework builds upon a core principle of multi-sensory analysis: genuine fires are associated with distinct environmental changes that unfold in predictable ways across various physical parameters. Thus, by using thermostats as secondary sensors in conjunction with smoke detectors, the framework creates a more comprehensive and reliable fire verification mechanism.

Description

Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025SYSTEMS AND METHODS FOR THERMOSTAT CONTROLLED FIRE DETECTIONCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of, and priority to, U.S. Provisional Patent Application No. 63 / 707,919 filed October 16. 2024, the entire contents of which are incorporated herein by reference.FIELD OF THE DISCLOSURE

[0002] The present disclosure is generally related to a location monitoring and control system, and more particularly, to a decision intelligence (Dl)-based computerized framework for automatically and / or dynamically controlling and managing issuances of a fire alarm at a location based on thermostat (and / or other secondary device) confirmation / verificationSUMMARY OF THE DISCLOSURE

[0003] False alarms in fire detection systems present significant technical challenges and operational consequences that extend beyond mere inconvenience. The primary technical consideration lies in system reliability' and the subsequent impact on automated response protocols. When false alarms occur frequently, they can lead to desensitization of both automated systems and human responders, potentially compromising the effectiveness of genuine emergency responses.

[0004] From a systems engineering perspective, false alarms increase wear on mechanical components such as alarm activation mechanisms, sprinkler systems, and automated door closures, leading to premature system degradation and increased maintenance costs. The signal- to-noise ratio (SNR) in detection algorithms becomes compromised, making it more difficult to establish accurate baseline parameters for future system calibrations. Additionally, false alarms often trigger unnecessary' heating, ventilation and air conditioning (HVAC) system shutdown sequences and fire damper activations, causing disruptions to building environmental controls and potentially affecting sensitive equipment or processes.

[0005] Modem fire detection systems utilizing multiple sensor inputs (e.g., heat, smoke, carbon monoxide (CO), for example) must maintain precise threshold settings; frequent false alarms can lead to inappropriate adjustments of these thresholds, potentially compromising the system's ability to detect actual fire events.1ACTIVE 715652382v1Attorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WOElectronically Filed: October 16. 2025

[0006] From a network infrastructure perspective, false alarms generate unnecessary data traffic in building management systems and emergency response networks, potentially impacting overall system performance and response times for genuine emergencies

[0007] To that end, in addressing such technical shortcomings, among others, the disclosed systems and methods provide a multi-sensor verification framework for which thermostat integration with smoke detection systems provides novel mechanisms for performing fire detection at location, which as provided herein evidences improvements in both accuracy and reliability. According to some embodiments, as discussed herein, the advanced framework leverages data gathered from multiple environmental sensors configured in relation to modem thermostats to verify fire events, reducing the likelihood of false positives and enhancing early detection. The disclosed framework builds upon a core principle of multi-sensory analysis: genuine fires are associated with distinct environmental changes that unfold in predictable ways across various physical parameters. By using thermostats as secondary sensors in conjunction with smoke detectors, the framework creates a more comprehensive and reliable fire verification mechanism, as discussed herein.

[0008] Accordingly, as discussed herein, the disclosed systems and methods can provide novel mechanisms for use in climate control (“comfort”) systems, security systems, smoke / fire systems, and the like, for which a location (e.g., house, building, office, patio, and the like) can be equipped with to ensure its occupants comfort, security and safety.

[0009] According to embodiments of the instant disclosure, it should be understood that the discussion herein that references a location can correspond to, but not be limited to, a home, office, building and / or any other type of definable structure and / or geographic location for which a control system (e.g., comfort / climate control and / or security system, for example) can be provided.

[0010] According to some embodiments, it should be understood that while the discussion herein may focus on a fire event at a location, it should not be construed as limiting, as one of ordinary skill in the art would recognize that such event can include, either additionally or alternatively, activity at the location related to, but not limited to, CO, carbon dioxide, a security breach (e.g., glass break, unsolicited motion, door break and the like), flooding, and the like, or some combination thereof, without departing from the scope of the instant disclosure. For example, a glass break at a home, via a glass break sensor, can be audited and confirmed via the disclosed systems and methods (e.g., a security panel or another sensor or user equipment, for example) via similar protocols outlined in the instant disclosure.2ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025

[0011] According to some embodiments, a method is disclosed for a Dl-based computerized framework for automatically and / or dynamically controlling and managing issuances of a fire alarm at a location based on thermostat (and / or other secondary7device) confirmation / verification. In accordance with some embodiments, the present disclosure provides a non-transitory computer-readable storage medium for carrying out the above- mentioned technical steps of the framework’s functionality. The non-transitory7computer- readable storage medium has tangibly stored thereon, or tangibly encoded thereon, computer readable instructions that when executed by a device cause at least one processor to perform a method for automatically and / or dynamically controlling and managing issuances of a fire alarm at a location based on thermostat (and / or other secondary device) confirmation / verification.

[0012] In accordance with one or more embodiments, a system is provided that includes one or more processors and / or computing devices configured to provide functionality in accordance with such embodiments. In accordance with one or more embodiments, functionality is embodied in steps of a method performed by7at least one computing device. In accordance with one or more embodiments, program code (or program logic) executed by a processor(s) of a computing device to implement functionality in accordance with one or more such embodiments is embodied in, by and / or on a non-transitory computer-readable medium.DESCRIPTIONS OF THE DRAWINGS

[0013] The features, and advantages of the disclosure will be apparent from the following description of embodiments as illustrated in the accompanying drawings, in which reference characters refer to the same parts throughout the various views. The drawings are not necessarily^ to scale, emphasis instead being placed upon illustrating principles of the disclosure:

[0014] FIG. 1 is a block diagram of an example configuration within which the systems and methods disclosed herein could be implemented according to some embodiments of the present disclosure;

[0015] FIG. 2 is a block diagram illustrating components of an exemplary7system according to some embodiments of the present disclosure;

[0016] FIG. 3 illustrates an exemplary workflow according to some embodiments of the present disclosure;3ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WOElectronically Filed: October 16. 2025

[0017] FIG. 4 depicts a non-limiting example according to some embodiments of the present disclosure;

[0018] FIG. 5 depicts an exemplary implementation of an architecture according to some embodiments of the present disclosure;

[0019] FIG. 6 depicts an exemplary implementation of an architecture according to some embodiments of the present disclosure; and

[0020] FIG. 7 is a block diagram illustrating a computing device showing an example of a client or server device used in various embodiments of the present disclosure.DETAILED DESCRIPTION

[0021] The present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, which form apart hereof, and which show, by way of non-limiting illustration, certain example embodiments. Subject matter may, however, be embodied in a variety of different forms and, therefore, covered or claimed subject matter is intended to be construed as not being limited to any example embodiments set forth herein; example embodiments are provided merely to be illustrative. Likewise, a reasonably broad scope for claimed or covered subject matter is intended. Among other things, for example, subject matter may be embodied as methods, devices, components, or systems. Accordingly, embodiments may, for example, take the form of hardw are, software, firmware or any combination thereof (other than software per se). The following detailed description is, therefore, not intended to be taken in a limiting sense.

[0022] Throughout the specification and claims, terms may have nuanced meanings suggested or implied in context beyond an explicitly stated meaning. Likewise, the phrase ‘in one embodiment” as used herein does not necessarily refer to the same embodiment and the phrase “in another embodiment” as used herein does not necessarily refer to a different embodiment. It is intended, for example, that claimed subject matter include combinations of example embodiments in whole or in part.

[0023] In general, terminology may be understood at least in part from usage in context. For example, terms, such as “and”, “or”, or “and / or,” as used herein may include a variety of meanings that may depend at least in part upon the context in which such terms are used. Typically, “or” if used to associate a list, such as A, B or C, is intended to mean A, B. and C, here used in the inclusive sense, as well as A, B or C, here used in the exclusive sense. In addition, the term “one or more” as used herein, depending at least in part upon context, may4ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025 be used to describe any feature, structure, or characteristic in a singular sense or may be used to describe combinations of features, structures or characteristics in a plural sense. Similarly, terms, such as “a,” “an,” or ‘‘the,” again, may be understood to convey a singular usage or to convey a plural usage, depending at least in part upon context. In addition, the term “based on” may be understood as not necessarily intended to convey an exclusive set of factors and may, instead, allow for existence of additional factors not necessarily expressly described, again, depending at least in part on context.

[0024] The present disclosure is described below with reference to block diagrams and operational illustrations of methods and devices. It is understood that each block of the block diagrams or operational illustrations, and combinations of blocks in the block diagrams or operational illustrations, can be implemented by means of analog or digital hardware and computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer to alter its function as detailed herein, a special purpose computer, ASIC, or other programmable data processing apparatus, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, implement the functions / acts specified in the block diagrams or operational block or blocks. In some alternate implementations, the functions / acts noted in the blocks can occur out of the order noted in the operational illustrations. For example, two blocks shown in succession can in fact be executed substantially concurrently or the blocks can sometimes be executed in the reverse order, depending upon the functional ity / acts involved.

[0025] For the purposes of this disclosure a non-transitory computer readable medium (or computer-readable storage medium / media) stores computer data, which data can include computer program code (or computer-executable instructions) that is executable by a computer, in machine readable form. By way of example, and not limitation, a computer readable medium may include computer readable storage media, for tangible or fixed storage of data, or communication media for transient interpretation of code-containing signals. Computer readable storage media, as used herein, refers to physical or tangible storage (as opposed to signals) and includes without limitation volatile and non-volatile, removable and nonremovable media implemented in any method or technology for the tangible storage of information such as computer-readable instructions, data structures, program modules or other data. Computer readable storage media includes, but is not limited to, RAM. ROM, EPROM, EEPROM, flash memory or other solid state memory technology, optical storage, cloud storage, magnetic storage devices, or any other physical or material medium which can be used5ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025 to tangibly store the desired information or data or instructions and which can be accessed by a computer or processor.

[0026] For the purposes of this disclosure the term “server’' should be understood to refer to a service point which provides processing, database, and communication facilities. By way of example, and not limitation, the term “server” can refer to a single, physical processor with associated communications and data storage and database facilities, or it can refer to a networked or clustered complex of processors and associated network and storage devices, as well as operating software and one or more database systems and application software that support the services provided by the server. Cloud servers are examples.

[0027] For the purposes of this disclosure a “network” should be understood to refer to a network that may couple devices so that communications may be exchanged, such as between a server and a client device or other types of devices, including between wireless devices coupled via a wireless network, for example. A network may also include mass storage, such as network attached storage (NAS), a storage area network (SAN), a content delivery network (CDN) or other forms of computer or machine-readable media, for example. A network may include the Internet, one or more local area networks (LANs), one or more wide area networks (WANs), wire-line type connections, wireless type connections, cellular or any combination thereof. Likewise, sub-networks, which may employ differing architectures or may be compliant or compatible with differing protocols, may interoperate within a larger network.

[0028] For purposes of this disclosure, a “wireless network” should be understood to couple client devices with a network. A wireless network may employ stand-alone ad-hoc networks, mesh networks. Wireless LAN (WLAN) networks, cellular networks, or the like. A wireless network may further employ a plurality of network access technologies, including Wi-Fi, Long Term Evolution (LTE), WLAN, Wireless Router mesh, or 2nd, 3rd, 4thor 5thgeneration (2G, 3G, 4G or 5G) cellular technology, mobile edge computing (MEC), Bluetooth, 802. 1 Ib / g / n, or the like. Network access technologies may enable wide area coverage for devices, such as client devices with varying degrees of mobility, for example.

[0029] In short, a wireless network may include virtually any type of wireless communication mechanism by which signals may be communicated between devices, such as a client device or a computing device, between or within a network, or the like.

[0030] A computing device may be capable of sending or receiving signals, such as via a wired or wireless network, or may be capable of processing or storing signals, such as in memory as physical memory' states, and may, therefore, operate as a server. Thus, devices capable of6ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025 operating as a server may include, as examples, dedicated rack-mounted servers, desktop computers, laptop computers, set top boxes, integrated devices combining various features, such as two or more features of the foregoing devices, or the like.

[0031] For purposes of this disclosure, a client (or user, entity’, subscriber or customer) device may include a computing device capable of sending or receiving signals, such as via a wired or a wireless network. A client device may, for example, include a desktop computer or a portable device, such as a cellular telephone, a smart phone, a display pager, a radio frequency (RF) device, an infrared (IR) device a Near Field Communication (NFC) device, a Personal Digital Assistant (PDA), a handheld computer, a tablet computer, a phablet, a laptop computer, a set top box, a wearable computer, smart watch, an integrated or distributed device combining various features, such as features of the forgoing devices, or the like.

[0032] A client device may vary in terms of capabilities or features. Claimed subject matter is intended to cover a wide range of potential variations, such as a web-enabled client device or previously mentioned devices may include a high-resolution screen (HD or 4K for example), one or more physical or virtual keyboards, mass storage, one or more accelerometers, one or more gyroscopes, global positioning system (GPS) or other location-identifying type capability, or a display with a high degree of functionality, such as a touch-sensitive color 2D or 3D display, for example.

[0033] Certain embodiments and principles will be discussed in more detail with reference to the figures. Traditionally, smoke detectors have been the primary tool for detecting fires in homes and buildings. While smoke detection is effective, it is also prone to false alarms caused by benign sources like cooking, dust, or steam. Integrating thermostat sensors adds a level of sophistication to the fire detection process, using additional data points such as temperature, humidity, and barometric pressure to either confirm or refute the presence of a genuine fire.

[0034] One of the key features of modem thermostats is their ability to monitor and respond to changes in temperature. In the context of fire detection, this is invaluable. Fires produce rapid and often extreme changes in temperature, with the rate of increase (delta-T) following a distinctive pattern that differentiates it from normal environmental temperature fluctuations, such as those caused by HVAC systems or weather changes. Advanced thermostats can analyze not just the absolute temperature but the rate at which it rises, which serves as a powerful indicator of a fire event. For example, if a smoke detector triggers but the thermostat records no significant temperature rise or the rate of change is minimal, the framework can conclude that the alarm was likely a false positive. Conversely, a sudden, steep temperature rise that7ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025 correlates with smoke detection is a strong indicator of a genuine fire, allowing for quicker and more confident decision-making in the critical early moments of the event.

[0035] According to some embodiments, as discussed herein, humidity' changes are another important factor that integrated systems can use to verify fire events. The humidity in the air behaves in predictable ways during a fire, adding another layer of data that can be analyzed to improve detection accuracy. Initially, as combustion begins, humidity tends to spike briefly. This is because many materials release water vapor when they bum. However, as the fire grows in intensity, the heat generated by the flames dries out the air, causing a sharp drop in humidity. This drop can be dramatic and often occurs in tandem with other fire indicators like rising temperature and smoke. By monitoring these humidity fluctuations, thermostats can contribute to a more detailed and accurate picture of the environment.

[0036] Accordingly, in some embodiments, the combination of temperature and humidity data allows the framework to build a nuanced understanding of the fire event as it unfolds. For example, if a sudden rise in temperature is accompanied by a corresponding drop in humidity, the likelihood of a fire is much higher than if only one of these parameters changed. The framework can identity' the specific patterns of these changes that are characteristic of fire events, filtering out environmental noise caused by non-fire activities like cooking or normal building operations.

[0037] According to some embodiments, barometric pressure changes can also provide useful data. Fires generate thermal updrafts that can cause localized pressure differentials. While these pressure changes may be subtle, they are detectable by modem thermostats equipped with barometric sensors. For example, a rapid pressure drop in a localized area can indicate the formation of a thermal column, a characteristic sign of a fire in progress. Thus, barometric pressure readings, in conjunction with and / or in the alternative to, temperature and / or humidity' data, can enhance the framework’s ability to distinguish between fire-related events and other disturbances like ventilation system changes or external weather conditions.

[0038] Accordingly, as discussed herein, the integration of thermostats with fire detection systems offers several economic benefits. One of the most significant advantages is the reduction of false alarms, which can be costly and disruptive. False alarms often lead to unnecessary evacuations, interruptions in business operations, and unwarranted emergency response deployments, all of which can have significant financial and operational impacts. By improving the accuracy of fire detection, integrated systems can reduce these occurrences, saving both time and money.8ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCT Resideo Ref. No. R214387-WO Electronically Filed: October 16. 2025

[0039] Additionally, the detailed data collected through this integrated approach can be valuable for post-event analysis. In the case of a fire, having access to precise data on how the fire developed — such as the rate of temperature increase, the timing of humidity' changes, and the pressure differentials — can provide useful insights for fire investigators and building managers. This data can also be used to optimize future fire detection protocols, leading to continuous improvements in system performance and reliability.

[0040] As such, as discussed herein, the disclosed systems and methods provide clear improvements in the fire detection technologies. For example, as discussed herein, by combining multiple environmental data streams (e.g., temperature, humidity’ and / or pressure, for example) into a single verification system, such integrated approaches offer a more reliable and accurate method of confirming fire events. Among other benefits, this not only reduces the number of false alarms, but also enhances the speed and confidence of genuine fire detection, ensuring that emergency responses are both timely and appropriate, and provide efficient usages of resources in fire prevention and management.

[0041] With reference to FIG. 1, system 100 is depicted which includes user equipment (UE) 102 (e.g., a client device, as mentioned above and discussed below in relation to FIG. 7), network 104, cloud system 106, database 108, sensors 110 and control engine 200. It should be understood that while system 100 is depicted as including such components, it should not be construed as limiting, as one of ordinary' skill in the art would readily understand that varying numbers of UEs, peripheral devices, sensors, cloud systems, databases and networks can be utilized; however, for purposes of explanation, system 100 is discussed in relation to the example depiction in FIG. 1.

[0042] According to some embodiments, UE 102 can be any type of device, such as, but not limited to, a mobile phone, tablet, laptop, sensor, smart television (TV) Internet of Things (loT) device, autonomous machine, wearable device, and / or any other device equipped with a cellular or wireless or wired transceiver. For example, UE 102 can be a thermostat and / or security control panel.

[0043] In some embodiments, a peripheral device (not shown) can be connected to UE 102, and can be any type of peripheral device, such as, but not limited to, a wearable device (e.g., smart ring or smart watch), printer, speaker, sensor, and the like. In some embodiments, a peripheral device can be any type of device that is connectable to UE 102 via any type of known or to be known pairing mechanism, including, but not limited to, WiFi, Bluetooth™, Bluetooth Low Energy (BLE), NFC, and the like.9ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCT Resideo Ref. No. R214387-WO Electronically Filed: October 16. 2025

[0044] According to some embodiments, sensors 110 (or sensor devices 110) can correspond to any type of device, component and / or sensor associated with a location of system 100 (referred to, collectively, as “sensors”). In some embodiments, the sensors 110 can be any type of device that is capable of sensing and capturing data / metadata related to a user and / or activity of the location. For example, the sensors 110 can include, but not be limited to. cameras, motion detectors, door and window contacts, temperature, heat and smoke detectors, carbon dioxide and / or carbon monoxide detectors, passive infrared (PIR) sensors, time-of-flight (ToF) sensors, and the like. In some embodiments, the sensors 110 can be associated with devices associated with the location of system 100, such as, for example, lights, smart locks, garage doors, smart appliances (e.g., thermostat, refrigerator, television, personal assistants (e.g., Alexa®, Nest®, for example)), smart rings, smart phones, smart watches or other wearables, tablets, personal computers, and the like, and some combination thereof. For example, the sensors 110 can include the sensors on UE 102 (e.g., smart phone) and / or peripheral device (e.g., a paired smart watch).

[0045] In some embodiments, as discussed herein, sensor 1 10 can be a smoke detector.

[0046] In some embodiments, network 104 can be any type of network, such as, but not limited to, a wireless network, cellular network, the Internet, and the like (as discussed above). Network 104 facilitates connectivity of the components of system 100, as illustrated in FIG. 1.

[0047] According to some embodiments, cloud system 106 may be any type of cloud operating platform and / or network based system upon which applications, operations, and / or other forms of network resources may be located. For example, system 106 may be a sen-ice provider and / or network provider from where services and / or applications may be accessed, sourced or executed from. For example, system 106 can represent the cloud-based architecture associated with a location monitoring and control system provider (e.g., climate and / or security system provided by Resideo®), which has associated network resources hosted on the internet or private network (e.g., network 104), which enables (via engine 200) the location management discussed herein.

[0048] In some embodiments, cloud system 106 may include a server(s) and / or a database of information which is accessible over network 104. In some embodiments, a database 108 of cloud system 106 may store a dataset of data and metadata associated with local and / or network information related to a user(s) of the components of system 100 and / or each of the components of system 100 (e.g., UE 102, sensors 110, and the services and applications provided by cloud system 106 and / or control engine 200).10ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCT Resideo Ref. No. R214387-WO Electronically Filed: October 16. 2025

[0049] In some embodiments, for example, cloud system 106 can provide a private / proprietary management platform, whereby engine 200, discussed infra, corresponds to the novel functionality7system 106 enables, hosts and provides to a network 104 and other devices / platforms operating thereon.

[0050] Turning to FIG. 5 and FIG. 6. in some embodiments, the exemplary computer-based systems / platforms, the exemplary computer-based devices, and / or the exemplary computer- based components of the present disclosure may be specifically configured to operate in a cloud computing / architecture 120 such as, but not limiting to: infrastructure as a service (laaS) 610, platform as a service (PaaS) 608, and / or software as a service (SaaS) 606 using a web browser, mobile app, thin client, terminal emulator or other endpoint 604. FIG. 5 and FIG. 6 illustrate schematics of non-limiting implementations of the cloud computing / architecture(s) in which the exemplary computer-based systems for administrative customizations and control of network-hosted application program interfaces (APIs) of the present disclosure may be specifically configured to operate.

[0051] Turning back to FIG. 1, according to some embodiments, database 108 may correspond to a data storage for a platform (e.g., a network hosted platform, such as cloud system 106, as discussed supra) or a plurality of platforms. Database 108 may receive storage instructions / requests from, for example, engine 200 (and associated microservices), which may be in any type of known or to be known format, such as, for example, standard query language (SQL). According to some embodiments, database 108 may correspond to any type of known or to be known storage, for example, a memory or memory stack of a device, a distributed ledger of a distributed network (e.g., blockchain, for example), a look-up table (LUT), and / or any other type of secure data repository.

[0052] Control engine 200, as discussed above and further below in more detail, can include components for the disclosed functionality7. According to some embodiments, control engine 200 may be a special purpose machine or processor, and can be hosted by a device on network 104, within cloud system 106. on UE 102 and / or sensor(s) 110. In some embodiments, engine 200 may be hosted by a server and / or set of servers associated with cloud system 106.

[0053] According to some embodiments, as discussed in more detail below, control engine 200 may be configured to implement and / or control a plurality of services and / or microser ices, where each of the plurality of services / microservices are configured to execute a plurality7of workflows associated with performing the disclosed device management. Non-limiting embodiments of such workflows are provided below.11ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025

[0054] According to some embodiments, as discussed above, control engine 200 may function as an application provided by cloud system 106. In some embodiments, engine 200 may function as an application installed on a scrvcr(s). network location and / or other type of network resource associated with system 106. In some embodiments, engine 200 may function as an application installed and / or executing on UE 102 and / or sensors 110. In some embodiments, such application may be a web-based application accessed by UE 102 and / or devices associated with sensors 110 over network 104 from cloud system 106. In some embodiments, engine 200 may be configured and / or installed as an augmenting script, program or application (e.g., a plug-in or extension) to another application or program provided by cloud system 106 and / or executing on UE 102 and / or sensors 110.

[0055] As illustrated in FIG. 2, according to some embodiments, control engine 200 includes identification module 202, analysis module 204, determination module 206 and output module 208. It should be understood that the engine(s) and modules discussed herein are non- exhaustive, as additional or fewer engines and / or modules (or sub-modules) may be applicable to the embodiments of the frameworks and methods discussed. More detail of the operations, configurations and functionalities of engine 200 and each of its modules, and their role within embodiments of the present disclosure will be discussed below.

[0056] Turning to FIG. 3. Process 300 provides non-limiting example embodiments for the disclosed safety management framework. According to some embodiments, Process 300 provides non-limiting embodiments for automatically and / or dynamically controlling and managing issuances of a fire alarm at a location based on thermostat (and / or other secondary device) confirmation / verification.

[0057] According to some embodiments, as discussed herein, the integration of thermostats with smoke detection systems provides a novel approach to fire event verification, which provides enhanced accuracy, faster responses and the ability to significantly reduce false alarms. As one of skill in the art w ould recognize, the disclosed Process 300 is not just related to detecting fire or smoke, but also involves analyzing various environmental data points such as, not limited to, temperature, humidity and barometric pressure to differentiate genuine fire events from false positives.

[0058] According to some embodiments, Steps 302 and 308 of Process 300 can be performed by identification module 202 of control engine 200; Steps 304 and 310 can be performed by analysis module 204; Steps 306 and 312 can be performed by determination module 204; and Steps 314-318 can be performed by output module 208.12ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCT Resideo Ref. No. R214387-WO Electronically Filed: October 16. 2025

[0059] According to some embodiments, Process 300 begins with Step 302 where engine 200 can monitor a location (e.g., home, for example) and detect indication of an event (e.g., a fire, for example). As discussed herein, smoke detectors (e.g., sensors 110) can serve as the primary' tool for fire detection (e.g., detection of heat, smoke, and / or other particles in the air that correspond to a fire (at a threshold level), for example).

[0060] Accordingly, in Step 302, in some embodiments, engine 200, via a smoke detector at the location, can monitor (e.g., continuously and / or according to a criteria or periodically) check for the presence of airborne particles that can indicate combustion. In some embodiments, engine 200 can evaluate such sensors’ data (e.g., in real-time), analyzing and checking for any signs that can signal a fire, such as a rapid rise in temperature, sudden changes in humidity', or drops in barometric pressure. In some embodiments, when / if any of these indicators are detected, engine 200 can flag the event as a potential fire and proceed to the next steps, discussed infra.

[0061] Upon such detection, in some embodiments, engine 200 can proceed to Step 304, where engine 200 can analyze the event information related to the detected occurrence. In some embodiments, as discussed herein, engine 200 can perform a computational analysis by parsing and analyzing the event information associated with the detected event via complex algorithms to determine the severity of the event and whether it correlates with patterns commonly associated with fires.

[0062] By way of example, if / when a smoke detector senses smoke, engine 200 can analyze the collected combustion information provided by such sensor (e.g., the sensor relays the information to engine 200, in some embodiments, and / or, in some embodiments, engine 200 can be integrated in such sensor, as discussed supra in FIG. 1, such that the engine 200 can perform such analysis upon its collection. Should the contaminants in the air be at or above a threshold, engine 200 can detect the fire event, which can include, but not be limited to, the position within the location (e.g., where within the home), the severity of the fire, the time the fire was detected, and the like, or some combination thereof.

[0063] In some embodiments, the analysis in Step 304 can include engine 200 analyzing the collected sensor data, by implementing any ty pe of known or to be known computational analysis technique, algorithm, mechanism or technology to analyze the collected sensor data from Step 306.

[0064] In some embodiments, engine 200 may execute and / or include a specific trained artificial intelligence / machine learning model (AI / ML), a particular machine learning model13ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025 architecture, a particular machine learning model type (e.g., convolutional neural network (CNN), recurrent neural network (RNN), autoencoder, support vector machine (SVM), and the like), or any other suitable definition of a machine learning model or any suitable combination thereof.

[0065] In some embodiments, engine 200 may leverage a large language model (LLM). whether known or to be known. An LLM is a type of Al system designed to understand and generate human-like text based on the input it receives. The LLM can implement technology' that involves deep learning, training data, statistical language models (SLMs) and natural language processing (NLP). As discussed herein, such known or to be known SLMs and / or NLPs can be utilized for, but not limited to, machine translation, speech recognition, text / speech generation, sentiment analysis, conversational dialog, and the like, or some combination thereof, as is capable with LLMs. Large language models are built using deep learning techniques, specifically using a type of neural network called a transformer. These networks have many layers and millions or even billions of parameters. LLMs can be trained on vast amounts of text data from the internet, books, articles, and other sources to learn grammar, facts, and reasoning abilities. The training data helps them understand context and language patterns. LLMs can use NLP techniques to process and understand text. This includes tasks like tokenization. part-of-speech tagging, and named entity recognition.

[0066] LLMs can include functionality related to, but not limited to, text generation, language translation, text summarization, question answering, conversational Al, text classification, language understanding, content generation, and the like. Accordingly, LLMs can generate, comprehend, analyze and output human-like outputs (e.g., text, speech, audio, video, and the like) based on a given input, prompt or context. Accordingly, LLMs, which can be characterized as transformer-based LLMs, involve deep learning architectures that utilizes self-attention mechanisms and massive-scale pre-training on input data to achieve NLP understanding and generation. Such current and to-be-developed models can aid Al systems in handling human language and human interactions therefrom.

[0067] In some embodiments, engine 200 may be configured to utilize one or more AI / ML techniques chosen from, but not limited to, computer vision, feature vector analysis, decision trees, boosting, support-vector machines, neural networks, nearest neighbor algorithms, Naive Bayes, bagging, random forests, logistic regression, and the like. By way of a non-limiting example, engine 200 can implement an XGBoost algorithm for regression and / or classification to analyze the sensor data, as discussed herein.14ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025

[0068] In some embodiments and, optionally, in combination of any embodiment described above or below, a neural network technique may be one of, without limitation, feedforward neural network, radial basis function network, recurrent neural network, convolutional network (e.g., U-net) or other suitable network. In some embodiments and, optionally, in combination of any embodiment described above or below, an implementation of Neural Network may be executed as follows: a. define Neural Network architecture / model, b. transfer the input data to the neural network model, c. train the model incrementally, d. determine the accuracy for a specific number of timesteps, e. apply the trained model to process the newly -received input data, f. optionally and in parallel, continue to train the trained model with a predetermined periodicity.

[0069] In some embodiments and, optionally, in combination of any embodiment described above or below, the trained neural network model may specify a neural network by at least a neural network topology7, a series of activation functions, and connection weights. For example, the topology of a neural network may include a configuration of nodes of the neural network and connections between such nodes. In some embodiments and, optionally, in combination of any embodiment described above or below, the trained neural network model may also be specified to include other parameters, including but not limited to, bias values / functions and / or aggregation functions. For example, an activation function of a node may be a step function, sine function, continuous or piecewise linear function, sigmoid function, hyperbolic tangent function, or other type of mathematical function that represents a threshold at which the node is activated. In some embodiments and, optionally, in combination of any embodiment described above or below, the aggregation function may be a mathematical function that combines (e.g.. sum, product, and the like) input signals to the node. In some embodiments and, optionally, in combination of any embodiment described above or below, an output of the aggregation function may be used as input to the activation function. In some embodiments and, optionally, in combination of any embodiment described above or below, the bias may be a constant value or function that may be used by the aggregation function and / or the activation function to make the node more or less likely to be activated.

[0070] In Step 306, based on the analysis from Step 304, engine 200 can determine to issue an initial warning related to the event, which can be caused to be output upon such determination.15ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025In some embodiments, the initial warning may not be a full alarm, but rather a “soff ’ warning that indicates the potential of a fire event. For example, such warning can include, but not be limited to, an in-app notification, display on a thermostat, electronic message (e.g., SMS or email) to an account of a user, electronic message to a user device, an alert to other sensors, an audible, visible and / or haptic alert provided by the detecting sensor or other sensors at the location, and the like, or some combination thereof.

[0071] For example, if burning is detected in the kitchen by the smoke detector located proximate to and / or in the kitchen, engine 200 can issue a warning that a fire may be occurring in the kitchen. As provided below, this initial warning, rather than a "full-blow n" alert via the smoke alarm (and to first responders), as discussed infra, can issue a warning to check whether this is a legitimate safety event (e.g., in the case the burning is related to toast burning in the kitchen for example). Thus, for example, such warning can be sent to, but not limited to, building occupants, facility managers, remote monitoring services, and the like, informing them of the event and allowing for further verification, as discussed herein.

[0072] Turning to Step 308, engine 200 can perform the operations related to such processing upon completion of Step 306. In some embodiments, engine 200 may additionally or alternatively proceed to Step 308 from Step 302, which can be a ‘‘fail-safe'’ step to expedite processing of confirming the detected event is a legitimate safety event. For example, from Step 302, engine 200 can proceed simultaneously (e.g., execute the steps of) to Step 304 and Step 308.

[0073] In Step 308, engine 200 can collect metrics from a location-based sensor(s). Such sensor(s) can be another sensor, which can be, but is not limited to. a temperature sensor, humidity sensor, air pressure (barometric) sensor, CO sensor, and the like, or some combination thereof. In some embodiments, the thermostat may function to collect such data to determine the likelihood of such event being legitimate.

[0074] Thus, in some embodiments, the collected metrics can correspond to, but not be related to, values related to. temperature, humidity, air pressure, smoke quantities, and / or any other known or to be known relevant climate data collectable from a location that corresponds to whether a fire is at a location. Such metrics, in some embodiments, can further include data related to, but not limited to, rate of change of such values, an initial value and time of such value, a current value and such current time, and the like.

[0075] In Step 310, engine 200 can perform a computational analysis of the collected metrics / values based at least in part on the event information (from Steps 302-304).16ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCT Resideo Ref. No. R214387-WO Electronically Filed: October 16. 2025Accordingly, in some embodiments, engine 200 can compile the event information (from Steps 302-304) and the collected metrics / values (from Step 308) as an input into an AI / ML and / or LLM model, for which such model(s) can execute in a similar manner as discussed above.

[0076] For example, in some embodiments, engine 200 can perform an analysis to determine and / or track changes over time of the temperature, humidity and / or air pressure values, which in some embodiments, can involve an attentive analysis related to a rate of change in which such values are changing (e.g., rising temperature as a delta-T, decreasing humidity as a delta- id, changes in air pressure, and the like, or some combination thereof).

[0077] In Step 312, based on the analysis in Step 310, engine 200 can determine whether o issue a full alarm (e.g., fire alarm). Such determination enables engine 200 to either confirm the initial suspicion of a fire or rule it out.

[0078] By way of a non-limiting example, a genuine fire would typically cause a rapid rise in temperature, a characteristic drop in humidity’ after an initial spike, and potentially a shift in barometric pressure. Normal building operations or environmental conditions (e.g., HVAC fluctuations or weather changes) would not follow this pattern as consistently. Thus, engine 200’ s operation can consider such changes to confirm the legitimacy of the detected event (from Step 302).

[0079] In some embodiments, such determination can be based on one or more of the values collected in Step 308 - for example, metrics / values and / or rates of change related to temperature, humidity and / or air pressure can be utilized by engine 200 to confirm the event as a fire. Indeed, fire events tend to cause a specific sequence of environmental shifts within short time frames; therefore, if / when engine 200 detects, for example, a temperature rise without a corresponding drop in humidity within a certain window of time, a determination in Step 312 may indicate the fire event detected in Step 302 as a “false positive.”

[0080] Thus, in some embodiments, if / when the determination indicates that the event (e.g., via the data collected in Step 308) is not a fire (e.g., not strong enough evidence, in that, temperature, humidity and / or air pressure values and / or rates of change do not satisfy a respective threshold(s), for example), processing can proceed from Step 312 to Step 314.

[0081] In Step 314, engine 200 can refrain from issuing the full alarm, thereby avoiding unnecessary panic or resource deployment. This can cause the metrics and event information, as well as the information related to the determinations resulting in such decision, to be stored in database 108, and utilized to further train the AI / ML and / or LLM model(s) utilized for the processing discussed herein.17ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCT Resideo Ref. No. R214387-WO Electronically Filed: October 16. 2025

[0082] Moreover, in Step 314, in some embodiments, engine 200 can issue a false alarm warning. Such alert can be sent to building management or emergency services, letting them know that the initial warning was a false positive and no further action is required. This operation can help to prevent unnecessary evacuations or fire department responses.

[0083] In some embodiments, Step 314 can further involve engine 200 silencing the initial warning output in Step 306.

[0084] Turning back to Step 312, when engine 200 determines that the metrics indicate values and / or rates of change that correspond with an actual fire event, as per the analysis in Step 310, engine 200 can proceed to Step 316. This can involve escalating the event to a full alarm. Thus, in some embodiments, when engine 200 determines that the collected metrics indicate a fire (e.g., a rapid temperature rise, a drop in humidity, air pressure changes, and / or smoke detection, at or above threshold levels), engine 200 can issue a full alarm. Such alarm triggers emergencyprotocols, such as notifying the fire department, initiating evacuation procedures, and sounding loud alarms throughout the location.

[0085] In some embodiments, such full alarm can involve, but is not limited to, sounding lights, audible outputs, haptic outputs and / or electronic messages sent to user devices, accounts, other sensors, the thermostat / control panel, and the like, or some combination thereof.

[0086] According to some embodiments, upon completion of Step 316 (and upon completion of Step 314, discussed supra), engine 200 can recursively revert back to Step 302 such that continued monitoring of the location can proceed. Such recursive monitoring can continue upon the detection of the event (in Step 302), which can occur in the backend via the smoke detector(s) and / or other sensors and / or UE at the location, such that related and / or other events can be tracked and confirmed via the processing discussed herein.

[0087] And in Step 318, engine 200 communicate all the relevant information to the event (e.g., event information, determination in Step 306, collected metrics / values in Step 308, determinations in Step 312, and the like) to the cloud or remote monitoring system, which can effectuate storing of such information and / or further training of the AI / ML and / or LLM model(s), as discussed above.

[0088] Turning to FIG. 4, by way of non-limiting example, depicted is an example user interface (UI) displayed on a thermostat’s display, where input can be provided and / or relayed to a viewing user as to whether an alarm event is a verified alarm or a false alarm, as discussed herein. The example depicts a non-limiting example of a fire detected in the kitchen of a home. Thus, for example, as per Step 314 above, a “false alarm” icon can be displayed, which can be18ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025 interactive which can enable a user to confirm such determination. In some embodiments, a “call fire department” icon can additionally and / or alternatively be displayed at such step, which can enable a user to trigger an alarm despite the false positive determination. And, in some embodiments, as per Step 316, the thermostat can be caused to display such icons, which can enable further confirmation or action by a user to act on a full alarm and / or override the framework’s determination.

[0089] Accordingly, as discussed herein, the disclosed integration of thermostats with smoke detection systems creates a powerful, multi-layered approach to fire detection that offers improved accuracy, reduces false alarms and improves early fire event verification. The disclosed framework’s operation, which operates from, for example, initial monitoring and event detection, through / to detailed analysis and verification, to the final alarm activation and cloud communication, provides a comprehensive fire safety7solution that benefits both residential and commercial settings. Thus, by incorporating temperature, humidity and / or pressure data, inter alia, into the detection process, the disclosed systems and methods provide a next generation of fire safety, ensuring more reliable detection and faster, more appropriate responses.

[0090] FIG. 7 is a schematic diagram illustrating a client device showing an example embodiment of a client device that may be used within the present disclosure. Client device 700 may include many more or less components than those shown in FIG. 7. However, the components shown are sufficient to disclose an illustrative embodiment for implementing the present disclosure. Client device 700 may represent, for example, UE 102 discussed above at least in relation to FIG. 1.

[0091] As shown in the figure, in some embodiments, Client device 700 includes a processing unit (CPU) 722 in communication with a mass memory 730 via a bus 724. Client device 700 also includes a pow er supply 726, one or more network interfaces 750, an audio interface 752, a display 754, a keypad 756, an illuminator 758, an input / output interface 760, ahaptic interface 762, an optional global positioning systems (GPS) receiver 764 and a camera(s) or other optical, thermal or electromagnetic sensors 766. Device 700 can include one camera / sensor 766, or a plurality7of cameras / sensors 766, as understood by those of skill in the art. Pow er supply 726 provides pow er to Client device 700.

[0092] Client device 700 may7optionally communicate with a base station (not shown), or directly with another computing device. In some embodiments, network interface 750 is sometimes known as a transceiver, transceiving device, or netw ork interface card (NIC).19ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCT Resideo Ref. No. R214387-WO Electronically Filed: October 16. 2025

[0093] Audio interface 752 is arranged to produce and receive audio signals such as the sound of a human voice in some embodiments. Display 754 may be a liquid crystal display (LCD), gas plasma, light emitting diode (LED), or any other type of display used with a computing device. Display 754 may also include a touch sensitive screen arranged to receive input from an object such as a stylus or a digit from a human hand.

[0094] Keypad 756 may include any input device arranged to receive input from a user. Illuminator 758 may provide a status indication and / or provide light.

[0095] Client device 700 also includes input / output interface 760 for communicating with external. Input / output interface 760 can utilize one or more communication technologies, such as USB, infrared, Bluetooth™, or the like in some embodiments. Haptic interface 762 is arranged to provide tactile feedback to a user of the client device.

[0096] Optional GPS transceiver 764 can determine the physical coordinates of Client device 700 on the surface of the Earth, which typically outputs a location as latitude and longitude values. GPS transceiver 764 can also employ other geo-positioning mechanisms, including, but not limited to, triangulation, assisted GPS (AGPS), E-OTD, CI, SAI, ETA, BSS or the like, to further determine the physical location of client device 700 on the surface of the Earth. In one embodiment, however, Client device 700 may through other components, provide other information that may be employed to determine a physical location of the device, including for example, a MAC address, Internet Protocol (IP) address, or the like.

[0097] Mass memory 730 includes a RAM 732, a ROM 734, and other storage means. Mass memory' 730 illustrates another example of computer storage media for storage of information such as computer readable instructions, data structures, program modules or other data. Mass memory 730 stores a basic input / output system (‘’BIOS”) 740 for controlling low-level operation of Client device 700. The mass memory also stores an operating system 741 for controlling the operation of Client device 700.

[0098] Memory 730 further includes one or more data stores, which can be utilized by Client device 700 to store, among other things, applications 742 and / or other information or data. For example, data stores may be employed to store information that describes various capabilities of Client device 700. The information may then be provided to another device based on any of a variety of events, including being sent as part of a header (e.g., index file of the HLS stream) during a communication, sent upon request, or the like. At least a portion of the capability information may also be stored on a disk drive or other storage medium (not shown) within Client device 700.20ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025

[0099] Applications 742 may include computer executable instructions which, when executed by Client device 700, transmit, receive, and / or otherwise process audio, video, images, and enable telecommunication with a server and / or another user of another client device. Applications 742 may further include a client that is configured to send, to receive, and / or to otherwise process gaming, goods / services and / or other forms of data, messages and content hosted and provided by the platform associated with engine 200 and its affiliates.

[0100] As used herein, the terms “computer engine” and “engine” identify at least one software component and / or a combination of at least one software component and at least one hardware component which are designed / programmed / configured to manage / control other software and / or hardware components (such as the libraries, software development kits (SDKs), objects, and the like).

[0101] Examples of hardware elements may include processors, microprocessors, circuits, circuit elements (e.g., transistors, resistors, capacitors, inductors, and so forth), integrated circuits, application specific integrated circuits (ASIC), programmable logic devices (PLD), digital signal processors (DSP), field programmable gate array (FPGA), logic gates, registers, semiconductor device, chips, microchips, chip sets, and so forth. In some embodiments, the one or more processors may be implemented as a Complex Instruction Set Computer (CISC) or Reduced Instruction Set Computer (RISC) processors; x86 instruction set compatible processors, multi-core, or any other microprocessor or central processing unit (CPU). In various implementations, the one or more processors may be dual-core processor(s), dual-core mobile processor(s), and so forth.

[0102] Computer-related systems, computer systems, and systems, as used herein, include any combination of hardware and software. Examples of software may include software components, programs, applications, operating system software, middleware, firmware, software modules, routines, subroutines, functions, methods, procedures, software interfaces, application program interfaces (API), instruction sets, computer code, computer code segments, words, values, symbols, or any combination thereof. Determining whether an embodiment is implemented using hardware elements and / or software elements may vary in accordance with any number of factors, such as desired computational rate, power levels, heat tolerances, processing cycle budget, input data rates, output data rates, memory resources, data bus speeds and other design or performance constraints.

[0103] For the purposes of this disclosure a module is a software, hardware, or firmware (or combinations thereof) system, process or functionality, or component thereof, that21ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCT Resideo Ref. No. R214387-WO Electronically Filed: October 16. 2025 performs or facilitates the processes, features, and / or functions described herein (with or without human interaction or augmentation). A module can include sub-modules. Software components of a module may be stored on a computer readable medium for execution by a processor. Modules may be integral to one or more servers, or be loaded and executed by one or more servers. One or more modules may be grouped into an engine or an application.

[0104] One or more aspects of at least one embodiment may be implemented by representative instructions stored on a machine-readable medium which represents various logic within the processor, which when read by a machine causes the machine to fabricate logic to perform the techniques described herein. Such representations, known as “IP cores,” may be stored on a tangible, machine readable medium and supplied to various customers or manufacturing facilities to load into the fabrication machines that make the logic or processor. Of note, various embodiments described herein may, of course, be implemented using any appropriate hardware and / or computing software languages (e.g., C++. Objective-C, Swift, Java, JavaScript, Python, Perl, QT, and the like).

[0105] For example, exemplary software specifically programmed in accordance with one or more principles of the present disclosure may be dow nloadable from a network, for example, a website, as a stand-alone product or as an add-in package for installation in an existing software application. For example, exemplary software specifically programmed in accordance with one or more principles of the present disclosure may also be available as a client-server software application, or as a web-enabled software application. For example, exemplary software specifically programmed in accordance with one or more principles of the present disclosure may also be embodied as a software package installed on a hardware device.

[0106] For the purposes of this disclosure the term “user”, “subscriber” “consumer” or “customer” should be understood to refer to a user of an application or applications as described herein and / or a consumer of data supplied by a data provider. By way of example, and not limitation, the term “user” or “subscriber” can refer to a person who receives data provided by the data or service provider over the Internet in a brow ser session, or can refer to an automated software application which receives the data and stores or processes the data. Those skilled in the art will recognize that the methods and systems of the present disclosure may be implemented in many manners and as such are not to be limited by the foregoing exemplary embodiments and examples. In other words, functional elements being performed by single or multiple components, in various combinations of hardware and software or firmware, and individual functions, may be distributed among softw are applications at either the client level22ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025 or server level or both. In this regard, any number of the features of the different embodiments described herein may be combined into single or multiple embodiments, and alternate embodiments having fewer than, or more than, all of the features described herein are possible.

[0107] Functionality may also be, in whole or in part, distributed among multiple components, in manners now known or to become known. Thus, myriad software / hardware / firmware combinations are possible in achieving the functions, features, interfaces and preferences described herein. Moreover, the scope of the present disclosure covers conventionally known manners for carrying out the described features and functions and interfaces, as well as those variations and modifications that may be made to the hardware or software or firmware components described herein as would be understood by those skilled in the art now and hereafter.

[0108] Furthermore, the embodiments of methods presented and described as flowcharts in this disclosure are provided by way of example in order to provide a more complete understanding of the technology. The disclosed methods are not limited to the operations and logical flow presented herein. Alternative embodiments are contemplated in which the order of the various operations is altered and in which sub-operations described as being part of a larger operation are performed independently.

[0109] While various embodiments have been described for purposes of this disclosure, such embodiments should not be deemed to limit the teaching of this disclosure to those embodiments. Various changes and modifications may be made to the elements and operations described above to obtain a result that remains within the scope of the systems and processes described in this disclosure.23ACTIVE 715652382v1

Claims

Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WOElectronically Filed: October 16. 2025CLAIMSWhat is claimed is:

1. A method comprising: receiving, by a second device, an indication that a first device at a location has detected an event, the event detection corresponding to a threshold amount of data being collected by the first device, the indication comprising information related to the collected data, the first device and second device being communicatively connected over a network at the location; causing, by the second device, output at the location of a preliminary warning; and analyzing, by the second device, the indication, and determining whether the event corresponds to an emergency event, wherein: when the determination of the event indicates the event is not the emergency event, issuing a false alarm notification and silencing the preliminary warning; and when the determination of the event indicates the event is the emergency event, outputting an indication that causes an emergency alarm at the location and to corresponding first responders.

2. The method of claim 1 , further comprising: determining that the collected data indicates a change in at least one environmental condition at the location; and determining that the event is an emergency event.

3. The method of claim 2, further comprising the change corresponding to a change in temperature at or above a threshold value, the threshold value corresponds to a temperature or a rate of change of temperature.

4. The method of claim 2, further comprising the change corresponding to a change in humidity at or above a threshold value, the threshold value corresponds to a humidity or a rate of change of humidity.

5. The method of claim 2, further comprising the change corresponding to a change in air pressure at or above a threshold value, the threshold value corresponds to air pressure or a rate of change of air pressure.24ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 20256. The method of claim 1, further comprising the analysis of the indication being based on a climate mode at the location.

7. The method of claim 1. further comprising: upon receiving the indication, communicating a notification to a user device of an occupant at the location, the notification enabling control of an alarm at the location by the first device.

8. The method of claim 1, further comprising the first device being a smoke detector, such that the data collected by the first device corresponds to smoke particles that correspond to a fire.

9. The method of claim 1 , further comprising the second device being a thermostat.

10. The method of claim 1, further comprising the second device being associated with a cloud service, such that the second device communicates instructions to a thermostat enabling control at the location.

11. The method of claim 1 , further comprising the event being a fire at the location.

12. A device comprising: a processor configured to: receive an indication that a first device at a location has detected an event, the event detection corresponding to a threshold amount of data being collected by the first device, the indication comprising information related to the collected data; cause output at the location of a preliminary warning; and analyze the indication, and determining whether the event corresponds to an emergency event, wherein: when the determination of the event indicates the event is not the emergency event, issue a false alarm notification and silencing the preliminary warning; and25ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025 when the determination of the event indicates the event is the emergency event, output an indication that causes an emergency alarm at the location and to corresponding first responders.

13. The device of claim 12, wherein the processor is further configured to: determine that the collected data indicates a change in at least one environmental condition at the location; and determine that the event is an emergency event.

14. The device of claim 13, wherein the processor is further configured such that the change corresponds to a change in temperature at or above a threshold value, the threshold value corresponds to a temperature or a rate of change of temperature.

15. The device of claim 13, wherein the processor is further configured such that the change corresponds to a change in humidity at or above a threshold value, the threshold value corresponds to a humidity or a rate of change of humidity7.

16. The device of claim 13, wherein the processor is further configured such that the change corresponds to a change in air pressure at or above a threshold value, the threshold value corresponds to air pressure or a rate of change of air pressure.

17. The device of claim 12, wherein the processor is further configured such that the analysis of the indication is based on a climate mode at the location.

18. The device of claim 12, wherein the processor is further configured to: upon receiving the indication, communicate a notification to a user device of an occupant at the location, the notification enabling control of an alarm at the location by the first device.

19. The device of claim 12, wherein the processor is further configured such that the first device is a smoke detector, such that the data collected by7the first device corresponds to smoke particles that correspond to a fire, and the device is a thermostat or another device26ACTIVE 715652382v1Atorney Docket No. 203863-017901 / PCTResideo Ref. No. R214387-WO Electronically Filed: October 16. 2025 associated with a cloud service, such that the other device communicates instructions to the thermostat enabling control at the location.

20. A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions that when executed by a second device, perform a method comprising: receiving, by the second device, an indication that a first device at a location has detected an event, the event detection corresponding to a threshold amount of data being collected by the first device, the indication comprising information related to the collected data, the first device and second device being communicatively connected over a network at the location; causing, by the second device, output at the location of a preliminary warning; and analyzing, by the second device, the indication, and determining whether the event corresponds to an emergency event, wherein: when the determination of the event indicates the event is not the emergency event, issuing a false alarm notification and silencing the preliminary warning; and when the determination of the event indicates the event is the emergency event, outputting an indication that causes an emergency alarm at the location and to corresponding first responders.27ACTIVE 715652382v1

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