Adaptive sensing smart home system and method

Abstract

Described are various embodiments of an adaptive smart home sensing system and method. In some embodiments, the system comprises one or more internet of things (IoT) devices, each IoT device configured to provide one or more smart home functions and comprising at least one sensor or switch. A hub device is communicatively coupled with the IoT devices via a network, and configured to receive usage and monitoring data therefrom. The hub is configured to detect the occurrence of one or more significant events, and adapt the IoT devices to acquire and send usage and monitoring data related to the significant event. The hub may also self-diagnose IoT devices working outside of normal operating parameters and reconfigure or reorganize the sensor network.

Description

ADAPTIVE SENSING SMART HOME SYSTEM AND METHODFIELD OF THE DISCLOSURE

[0001] The present disclosure relates to home automation and monitoring, and, in particular, to an adaptive sensing smart home system and method.BACKGROUND

[0002] Smart home sensors and technology is only of benefit if it makes the life of the user easier or more convenient. There is a significant technological barrier for the adoption of smart home technology and products due to the current complexities of setting them up and having them talk to each other to perform the automations and conveniences they claim to be able to do. Utilizing smart home sensors to their full extent currently requires a lot of effort and / or a degree in programming to be able to implement. In addition, a consumer’s needs for smart home sensors often changes over time, which currently means investing in new sensors and having a stockpile of “old” hardware that isn’t being used. On the commercial side, the market lacks options for a scalable and modular platform that businesses can employ to utilize smart sensors for asset monitoring, energy management and / or aging in place while also offering conveniences that the consumer / resident can also take advantage of. Maintenance is currently reactive for homeowners and property managers.

[0003] This background information is provided to reveal information believed by the applicant to be of possible relevance. No admission is necessarily intended, nor should be construed, that any of the preceding information constitutes prior art or forms part of the general common knowledge in the relevant art.SUMMARY

[0004] The following presents a simplified summary of the general inventive concept(s) described herein to provide a basic understanding of some aspects of the disclosure. This summary is not an extensive overview of the disclosure. It is not intended to restrict key or critical elements of embodiments of the disclosure or to delineate their scope beyond that which is explicitly or implicitly described by the following description and claims.

[0005] A need exists for scalable and modular system or platform that can be employed to utilize smart sensors for asset monitoring, energy management and / or aging in place while also offering conveniences that the consumer or resident can also take advantage of, including an easyto use, intuitive application and UI that lowers the barrier to adoption and the ability to use smart sensors and devices to detect substandard, declining and / or atypical performance and initiate a service event or sensor network failover protocol.

[0006] Other aspects, features and / or advantages will become more apparent upon reading of the following non-restrictive description of specific embodiments thereof, given by way of example only with reference to the accompanying drawings.

[0007] In accordance with a first aspect, there is provided an adaptive sensing smart home system, comprising: one or more internet of things (loT) devices, each loT device configured to provide one or more smart home functions and comprising at least one sensor or switch; a hub device communicatively coupled to the loT devices via a network, and configured to receive usage and monitoring data therefrom; and detecting, via the usage and monitoring data, the occurrence of one or more significant events; and adapting the loT devices to acquire and send usage and monitoring data related to the one or more significant events.

[0008] In some embodiments, at least one of the one or more loT devices comprises a fixed housing configured to receive one or more demountable inserts, each demountable insert configured to provide the one or more smart home functions.

[0009] In some embodiments, the one or more sensors include at least one of a temperature sensor, a microphone, a humidity sensor, an air quality sensor, door contact sensor, motion sensors, a camera, or a power consumption sensor.

[0010] In some embodiments, at least one of the one or more significant events is related to one or more daily living activities of an individual.

[0011] In some embodiments, the one or more significant events include a significant acoustic event.

[0012] In some embodiments, the significant acoustic event comprises the sound of a glass breaking, a heavy object colliding, or a shout.

[0013] In some embodiments, the hub is further configured to determine if the activity level is abnormal, at least in part, by determining if one or more biometric parameters associated with the activity level is abnormal.

[0014] In some embodiments, the hub is configured to before said detecting: determining if a first device of said one or more loT devices is performing outside normal operating parameters.

[0015] In some embodiments, the determining is done by estimating by the hub whether the first device has an abnormal power usage or whether a data quality received from the first device comprises outlier values.

[0016] In some embodiments, upon the hub determining that the first device is performing outside normal operating parameters, the hub operable to reconfigure one or more other devices of the plurality of loT devices to monitor, at least in part, one or more environmental parameters originally monitored by the first device.

[0017] In accordance with another aspect, there is provided a computer-implemented method for adaptive sensing, comprising the steps of acquiring, via a one or more internet of things (loT) devices, usage and monitoring data; receiving, at a hub device communicatively coupled to the loT devices via a network, the usage and monitoring data; detecting, via the usage and monitoring data, the occurrence of one or more significant events; and adapting the loT devices to acquire and send usage and monitoring data related to the one or more significant events.

[0018] In some embodiments, at least one of the one or more loT devices comprises a fixed housing configured to receive one or more demountable inserts, each demountable insert configured to provide the one or more smart home functions.

[0019] In some embodiments, the one or more sensors include at least one of a temperature sensor, a microphone, a humidity sensor, an air quality sensor, door contact sensor, motion sensors, a camera, or a power consumption sensor.

[0020] In some embodiments, at least one of the one or more significant events is related to one or more daily living activities of an individual.

[0021] In some embodiments, the one or more significant events include a significant acoustic event.

[0022] In some embodiments, the significant acoustic event comprises the sound of a glass breaking, a heavy object colliding, or a shout.

[0023] In some embodiments, the hub is further configured to determine if the activity level is abnormal, at least in part, by determining if one or more biometric parameters associated with the activity level is abnormal.

[0024] In some embodiments, the computer-implemented method further comprises the steps of, before said detecting: determining, by the hub device, if a first device of said one or more loT devices is performing outside normal operating parameters.

[0025] In some embodiments, the determining is done by estimating by the hub whether the first device has an abnormal power usage or whether a data quality received from the first device comprises outlier values.

[0026] In some embodiments, upon the hub determining that the first device is performing outside normal operating parameters, reconfiguring, by the hub device, one or more other devices of the plurality of smart devices to monitor, at least in part, one or more environmental parameters originally monitored by the first device.

[0027] In accordance with another aspect, there is provided an adaptive sensing smart home system, comprising: one or more internet of things (loT) devices, each loT device configured to provide one or more smart home functions and comprising at least one sensor or switch; a hub device communicatively coupled to the one or more loT devices via a network, and configured to: receive usage and monitoring data from the one or more loT devices; and detect, via the usage and monitoring data, whether a first device of the one or more loT devices is defective or performing suboptimally; and upon detecting the first device, the hub device configured to provide consistent or increased sensing coverage by: reconfiguring at least one of the one of the one or more loT devices; or providing a notification to a user to reconfigure, relocate or replace the first device, or another device of the one or more loT devices.

[0028] In accordance with another aspect, there is provided a computer-implemented method for adaptive sensing, comprising the steps of: acquiring, via a one or more internet of things (loT) devices, usage and monitoring data; receiving, at a hub device communicatively coupled to the one or more loT devices via a network, the usage and monitoring data; detecting, via the usage and monitoring data, whether a first device of the one or more loT devices is defective or performing suboptimally; and upon detecting the first device, providing consistent or increased sensing coverage by: reconfiguring at least one of the one of the one or more loT devices; or providing a notification to a user to reconfigure, relocate or replace the first device, or another device of the one or more loT devices.

[0029] Other aspects, features and / or advantages will become more apparent upon reading of the following non-restrictive description of specific embodiments thereof, given by way of example only with reference to the accompanying drawings.BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Several embodiments of the present disclosure will be provided, by way of examples only, with reference to the appended drawings, wherein:

[0031] FIG. l is a schematic diagram of an adaptive sensing smart home system, in accordance with one embodiment;

[0032] FIG. 2A and FIG. 2B are schematic diagrams illustrating an Internet of Things (loT) device (FIG. 2A) and one comprising removable inserts (FIG. 2B), in accordance with one embodiment;

[0033] FIG. 3 is a schematic diagram of a hub / server of the system of FIG. 1 with a user device, in accordance with one embodiment; and

[0034] FIG. 4 is a schematic diagram illustrating adaptive sensing capabilities of the system of FIG. 1, in accordance with one embodiment.

[0035] Elements in the several drawings are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be emphasized relative to other elements for facilitating understanding of the various presently disclosed embodiments. Also, common, but well-understood elements that are useful or necessary in commercially feasible embodiments are often not depicted in order to facilitate a less obstructed view of these various embodiments of the present disclosure.DETAILED DESCRIPTION

[0036] Various implementations and aspects of the specification will be described with reference to details discussed below. The following description and drawings are illustrative of the specification and are not to be construed as limiting the specification. Numerous specific details are described to provide a thorough understanding of various implementations of the present specification. However, in certain instances, well-known or conventional details are not described in order to provide a concise discussion of implementations of the present specification.

[0037] Furthermore, numerous specific details are set forth in order to provide a thorough understanding of the implementations described herein. However, it will be understood by those skilled in the relevant arts that the implementations described herein may be practiced without these specific details. In other instances, well-known methods, procedures and components have not been described in detail so as not to obscure the implementations described herein.

[0038] In this specification, elements may be described as “configured to” perform one or more functions or “configured for” such functions. In general, an element that is configured to perform or configured for performing a function is enabled to perform the function, or is suitable for performing the function, or is adapted to perform the function, or is operable to perform the function, or is otherwise capable of performing the function.

[0039] When introducing elements of aspects of the disclosure or the examples thereof, the articles “a,” “an,” “the,” and “said” are intended to mean that there are one or more of the elements. The terms “comprising,” “including,” and “having” are intended to be inclusive and mean that there may be additional elements other than the listed elements. The term “exemplary” is intended to mean “an example of.” The phrase “one or more of the following: A, B, and C” means “at least one of A and / or at least one of B and / or at least one of C.”

[0040] The present disclosure is directed, in accordance with different embodiments, to a scalable and modular system or platform employing smart sensors for asset monitoring, energy management and / or aging in place functionality. The system provides adaptive sensor networks that respond to changes in the environment, network elements and / or availability, and improved data visualization capabilities that advantageously allows to monitor, illustrate, and manage usecase specific behaviors based on the aggregation and / or fusion of both processed and unprocessed data from various sensors and / or devices. The platform, as will be made clear below, is both flexible and modular as it allows to use and combine data acquired by various Internet of Things(loT) devices, such as smart home devices or the like, to adaptively monitor a plurality of parameters and derive use-case specific behaviors from users / individuals and / or events or activities. Behaviors that case be detected include living-in-place, aging-in-place security, or energy saving / reduction related behaviors. This may include, for example, information related to sleep patterns (e.g., uninterrupted sleep), wandering, abnormal behavior, or the like. In some embodiments, the system may also be configured to detect dangerous or potentially dangerous activities or events.

[0041] The system can, in accordance with different embodiments, combine and / or fuse data provided from the various loT devices, including sensor, usage or switch data, dynamically in real-time using advanced data aggregation and / or fusion techniques with both processed and unprocessed data. The system is thus highly modular and capable to adapt to changes in the received data sources and / or data types to provide a consistent sensing capability or coverage, for example when new sensors and / or devices are added / removed, in response to a change in environment. loT device performance monitoring allows to detect devices that are defective or not performing normally. In some embodiments, the platform is configured to provide adaptive sensor management, but also dynamic power management, declining individual performance detection, preventive maintenance notification, or home automation capabilities. The modularity and adaptive capabilities further provides an improved reliability and simplified maintenance.

[0042] FIG. 1 schematically illustrates a modular and adaptive smart home automation and management system or platform, referred to by the numeral 118, in accordance with one embodiment. The system 118 is configured to be communicatively coupled with one or more loT devices 106, such as for example smart home devices or the like. Such devices typically comprise, as shown in FIG. 2A, a processor 202 coupled to a memory 204 and network adapter 206 and one or more “smart home” feature providing elements, including one or more sensors 210, and / or switches 216. While these may include any network connected “smart” device, such as smart cameras, smart thermostats, smart displays, smart switches, smart lights, smart appliances, or the like, the system may advantageously be also used with modular loT devices removably coupled to infrastructure such as electrical box receptacles or the like. As illustrated in FIG. 2B, in some embodiments, the loT devices 106 may take the form of one or more removable inserts 214 configured to be releasably coupled within elements of the physical infrastructure providing predetermined fixed functions such as an electrical outlet, light switch etc. In some embodiments, these may preferably include a wall receptacle 120 comprising oneor more cavities 208 configured to removably receive therein a removable insert 214. The receptacle 120 is illustrated in FIG. 2B with an electrical outlet 212, as an example only. Other examples of such inserts and receptacles that may be used include devices such as those disclosed in commonly assigned U.S. Patents 10,720,764, 11,095,106, 11646,559, or co-pending International Applications No. PCT / CA2020 / 051264 and PCT / CA2022 / 051427. However, the system and methods of the present disclosure are not limited to these devices, and may generally be configured to work with any loT devices as well, without limitation.

[0043] The loT devices 106 may each comprise one or more types of sensors known in the art. Sensors may include, without limitation, environmental sensors, medical sensors, biological sensors, chemical sensors, ambient environment sensors, position sensors, motion sensors, thermal sensors, infrared sensors, visible sensors, RFID sensors, and medical testing and diagnosis devices. A sensor may include, but not be limited to, a radon sensor, an ionizing radiation sensor, a microwave radiation sensor, an optical sensor, a camera, a motion detector, a smoke detector, an air particulate detector, a water detector, a humidity detector, a liquid level sensor, door contact sensor, a gas sensor for one or more gases including but not limited to ammonia, carbon dioxide, carbon monoxide, chlorine, chlorine dioxide, ethylene oxide, flammable gases, hydrogen, hydrogen chloride, hydrogen cyanide, hydrogen sulphide, methane, nitrogen dioxide, nitric oxide, oxygen, phosphine, propane, sulphur dioxide, one or more volatile organic compounds. A sensor may include, but not be limited to, radar, LIDAR, thermal imaging, infrared imaging, a two-dimensional (2D) optical scanner, a three-dimensional (3D) optical scanner, a microphone, an ultrasonic detector, an ultralow frequency detector, a pressure sensor, and a vibration sensor. A sensor may include a microphone.

[0044] Going back to FIG. 1, the system 118 is configured so that usage and monitoring data 402 relating to a living space or building 116 and / or a monitored individual 114 living said space, acquired by the one or more loT devices 106, is sent via a home network a central processing device, such as a hub 110. Usage data may include when and how often a device is used, its operating parameters, user-related information, or the like. Monitoring data may include any sensor acquired data. The hub 110 and / or server 104 is configured to process the usage and monitoring data 402 and provide a plurality of notifications, automated responses and / or visualization outputs to one or more user devices user device 102 for a plurality of users 112 via the internet 108.

[0045] The hub 110 is configured to, at least in part, provide advanced management and monitoring features. The hub 110 may also be configured as a router device, or be connected to one, so as to be directly or indirectly communicatively coupled to one or more servers 104 and / or to one or more user devices user device 102 of one or more users 112. It will be understood that functionalities described herein may be distributed between the hub 110 and server(s) 104, however in some embodiments the hub 110 may be configured to perform edge computing training and optimization tasks.

[0046] FIG. 3 illustrates schematically a hub / server 302 which may include the hub 110 and / or one or more servers 104, alone or in combination, which provides a number of adaptive and modular smart home management features. The hub / server 302 generally comprises one or more processors 304 coupled to a network adapter 306 and a memory 308, and is communicatively coupled to the one or more loT devices 106 for control and / or receiving usage and / or sensor information therefrom. As illustrated, memory 308 may comprise one or more modules. For example, this includes a control module 322 configured to allow a user to operate / configure the different loT devices from the user device 310, but also a machine learning module 316 implementing one or more Al or machine-learning techniques for detecting or identifying, based on the use and monitoring data, important events 324, a general activity level 330 of a monitored individual and / or one or more defective or sub-performing loT devices 326.

[0047] The user device user device 102 may include any personal electronic device comprising and I / O capabilities, such as an electronic or digital display 312 capable of displaying a graphical user interface (GUI 314) and input means such as keyboards (in hardware or simulated via a touch screen) or a computer mouse (not shown). Non-limiting examples of user device 102 include smart phones, desktop computers, laptops, tablets, smartwatches or the like. The user device 102 provides a graphical user interface (GUI 314) that allows to control the various loT devices 106 or advanced adaptive features related thereto (e.g., control interface 320), allows to receive notifications and alerts 318 or recommendations 328. In some embodiments, the user device 310 may rely on a dedicated application, or may access the servers 104 and / or the hub 110 via a web interface.

[0048] In some embodiments, the ML module 316 may include algorithms and processes dedicated to the aggregation and / or fusion of received data to improve overall sensing capabilities. In some embodiments, machine learning algorithms may also include trigger-based algorithms that are enabled upon detecting a sensor parameter or data value being above / belowa designated threshold value. In some embodiments, the machine learning algorithm may include more sophisticated algorithms, such as neural networks including supervised learning, unsupervised learning, cluster analysis, reinforcement learning, feature learning, sparse dictionary learning, anomaly detection, association rule learning, inductive logic programming. It may also include vector regression (SVR), K-nearest neighbor (KNN), random forest (RF), decision tree (DT), or multilayer perceptron (MLP). In some embodiments, generative artificial intelligence (Al) algorithms or methods may also be used.

[0049] As illustrated in FIG. 4, the system receives usage and monitoring data 402 from one or more data sources 404a, 404b... 404N. While typically a data source may be functionally equivalent to an loT device as described above, other sources of data may also be used, in addition to data received from loT devices, including 3rd-party data acquired by other means or received from one or more network-connected databases. The machine learning module 316 may be configured to aggregate, process, fuse, or train on these various data sources to detect a plurality of significant events 406. These events may include, as a non-limiting example only, assisted living-related events 408, such as detecting an individual wandering (410), lack of sleep / rest (414), falls or collisions (412), atypical behavior (416) or health-related events or problems (430). In can also include home monitoring and / or security related events 418 such as unauthorized or forced entry (420), changes in air quality (422), water leaks (424), abnormal power usage (426) from one or more devices, including the loT devices 106, including maintenance-related issues (428) of the loT devices 106.

[0050] In some embodiments, the system may be configured via the ML module 316 to track and monitor signs of cognitive decline, and / or physical decline. This may be useful for elderly or senior individuals requiring assisted living, living in their own personal residence or cohabitating with loved ones / care persons. In those cases, the system 118 may be configured to monitor a designated user (e.g., the elderly person), while providing information and system control to another user or individual (e.g., the caregiver) via the GUI 314. Specific needs for this type of monitored individual may include, without limitation, assistance for living at home, guidance in low-light conditions (via adaptive lighting), reminders or prompts for basic living activities, including taking medication, turning off the stove, moving to a designated location, and safeguarding against wandering, hazards, neglect or forgetfulness, or alerts when the monitored individual is hurt or falls. Caregivers, in turn, may require information or knowledge about various activities, including for example an amount of rest (e.g., uninterrupted sleep or thelike) taken by the monitored individual, and warnings or notifications of dangerous and potentially dangerous activities or events.

[0051] In some embodiments, the system 118 may be configured to identify one or more daily living activities based on the received usage and monitoring data 402. This may be done by detecting a recurring number of sensor inputs and switch activations that correlate with a designated daily living activity. Multiple activities may be correlated to happen in succession or in parallel. For example, this may include an individual taking a shower (e.g., humidity sensor, water flow sensor) followed by drinking a cup of tea (smart kettle being activated, humidity sensor). These daily activities may be recorded and deviations therefrom may also be detected. Deviations or abnormal behavior may be reported to a caretaker user via the GUI 314 for example.

[0052] In one example of the adaptive capabilities of the system of the present disclosure, an exemplary living space situation is described. In this example, an elderly person wakes up at night because she or he is thirsty. Upon detecting that the individual is not sleeping and moving (for example, by a combination of sensor data or usage), the system may provide adaptive lighting by turning on one or more smart lights at the correct locations. If, shortly after, the individual has a heath related issue, causing him or her to fall for example, the system 118 may be further be configured to detect abnormal acoustic signals recorded by the microphones (e.g., acoustic event) from one or more of the loT devices 106 that correlate strongly with the event (e.g., sound of glass breaking on the floor, a heavy object being dropped, or a shout, etc.). The detection may be based on a frequency / amplitude threshold trigger, or may rely on trained ML algorithms. Once detected, the system 118 may immediately send one or more notifications to the caregiver user while also notifying or alerting the authorities. It may also adaptively use sensor data from other devices to assess the evolution of the situation (e.g., no switches being activated, no other sensors recording data that correlates with normal behavior for long time, etc.).

[0053] In some embodiments, the system may use the ML module 316 to track and monitor living spaces or buildings. This may be useful for homeowners or property managers of rentals properties, such as short term rentals, single family medium (SFM) or multi-family properties. The system 118 may be configured to provide features such as security monitoring and alerting (including escalating to emergency services), detection of risks such as poor air quality (e.g., smoke detection), automation of lighting, leak detection or detection of forced entry, electricity / power consumption (including excess power draw and / or overheating) andmaintenance-related monitoring and alerting. In some embodiments, the system may further be configured to focus on energy savings. This may include providing tips and suggestions to the user, for example for ways to reduce energy consumption, automatically shut-off non-essential appliances when not in use, monitoring essential appliances to ensure they are not shut off (e.g., fridge, freezer, heater, A / C, etc.), monitoring electricity consumption, etc.

[0054] In some embodiments, the system 118 is also configured to self-diagnose and dynamically detect loT devices 106 performing outside of normal operating parameters. This may include, for example, detecting abnormal power usage of loT devices 106, such as when an loT device is battery-powered or becomes disconnected from the wired power connection. It can include when power usage increases abnormally over expected values. In some embodiments, the system 118 can learn and store a measured power usage profile of a given loT device (hourly, daily, weekly, etc.) to generate one or more baseline values or profiles and detect when then power usage differs significantly from the known baseline (higher or lower), which may indicate that the device is faulty and in need of maintenance. Power usage values may be in some cases provided by the loT device itself, while in other cases a distinct loT power monitoring device may be used.

[0055] In some embodiments, loT devices 106 performing outside of normal operating parameters may also be detected by monitoring a data quality received from those devices. For example, digital images received from a loT camera device may indicate one or more bad / lost pixels, or CO2 measurement data from a CO2 sensor may indicate an erratic output or values. In some embodiments, detection may be done by generating one or more data quality baseline values or trends and training the system to identify or detect when the data differs significantly from those baseline values in ways that correlate with malfunctioning equipment (e.g., outlier values).

[0056] In some embodiments, upon detecting that one or more loT devices 106 are performing in a suboptimal fashion, the system 118 may provide means to reconfigure how it receives and processes the loT data in a dynamical fashion. In some embodiments, this may include providing one or more notifications via the GUI 314 that one or more loT devices loT device 106 are faulty or in need of maintenance. This may also include providing one or more suggestions on how best to replace the malfunctioning device, including suggesting one or more replacement devices. For example, if the loT device is an insert module used with a receptacle body, then the system 118 may further suggest changing location of different removable inserts 214 to increase sensor coverage. In some embodiments, the system 118 may be configured to detect that areas of themonitored space are not properly covered. For example, this may include detecting certain individuals outside a camera field of view in a repetitive fashion.

[0057] In some embodiments, the system 118 may be configured to derive, via the machine learning module 316 based on the usage and monitoring data 402, one or more biometric parameters of an individual. This may include, for example, heart rate detection, pressure, breathing, corporeal temperature and the like.

[0058] Many of the functional units described in this specification have been labeled as “modules” in order to more particularly emphasize their implementation independence. For example, a module may be implemented as a hardware circuit comprising custom VLSI circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. An engine may also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices or the like.

[0059] A module may also be implemented in software for execution by various types of processors. An identified engine of executable code may, for instance, comprise one or more physical or logical blocks of computer instructions which may, for instance, be organized as an object, procedure, or function. Nevertheless, the executables of an identified engine need not be physically located together, but may comprise disparate instructions stored in different locations which, when joined logically together, comprise the engine or module and achieve the stated purpose for the module.

[0060] Indeed, a module of executable code may be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data may be identified and illustrated herein within engines, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices, and may exist, at least partially, merely as electronic signals on a system or network. Where a module or portions of a module is implemented in software, the software portions are stored on one or more computer readable storage media.

[0061] The term “memory”, “machine-readable storage medium” or “computer readable medium” as used herein refers to any medium or media that participates in providing instructions to a processor for execution. Such a medium may take many forms, including, but not limited to,non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical or magnetic disks, such as data storage devices. Volatile media include dynamic memory, such as random access memory (RAM). Common forms of machine-readable media include, for example, floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH EPROM, any other memory chip or cartridge, or any other medium from which a computer can read. The machine-readable storage medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of matter effecting a machine-readable propagated signal, or a combination of one or more of them.

[0062] The term “processor” includes general-purpose microprocessors, microcontrollers, a Digital Signal Processors (DSP), Application Specific Integrated Circuits (ASIC), Field Programmable Gate Arrays (FPGA), Programmable Logic Devices (PLD), discrete hardware components, or any other suitable entity that can perform calculations or other manipulations of information. One or more processors in a multi-processing arrangement may also be employed to execute the sequences of instructions contained in a memory. In alternative aspects, hardwired circuitry may be used in place of or in combination with software instructions to implement various aspects of the present disclosure. Thus, aspects of the present disclosure are not limited to any specific combination of hardware circuitry and software.

[0063] Various aspects of the subject matter described in this specification can be implemented in a computing system that includes a back end component, e.g., such as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described in this specification, or any combination of one or more such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. The communication network can include, for example, any one or more of a LAN, a WAN, the Internet, and the like. Further, the communication network can include, but is not limited to, for example, any one or more of the following network topologies, including a bus network, a star network, a ring network, a mesh network, a star-bus network, tree or hierarchical network, or the like. The communications modules can be, for example, modems or Ethernet cards.

[0064] Indeed, a module of executable code may be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data may be identified and illustrated herein within modules, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices, and may exist, at least partially, merely as electronic signals on a system or network. Where a module or portions of a module are implemented in software, the software portions are stored on one or more computer readable storage media.

[0065] While the present disclosure describes various embodiments for illustrative purposes, such description is not intended to be limited to such embodiments. On the contrary, the applicant's teachings described and illustrated herein encompass various alternatives, modifications, and equivalents, without departing from the embodiments, the general scope of which is defined in the appended claims. Information as herein shown and described in detail is fully capable of attaining the above-described object of the present disclosure, the presently preferred embodiment of the present disclosure, and is, thus, representative of the subject matter which is broadly contemplated by the present disclosure.

Claims

CLAIMSWhat is claimed is:

1. An adaptive sensing smart home system, comprising: one or more internet of things (loT) devices, each loT device configured to provide one or more smart home functions and comprising at least one sensor or switch; a hub device communicatively coupled to the one or more loT devices via a network, and configured to: receive usage and monitoring data from the one or more loT devices; and detect, via the usage and monitoring data, whether a first device of the one or more loT devices is defective or performing suboptimally; and upon detecting the first device, the hub device configured to provide consistent or increased sensing coverage by: reconfiguring at least one of the one of the one or more loT devices; or providing a notification to a user to reconfigure, relocate or replace the first device, or another device of the one or more loT devices.

2. The system of claim 1, wherein detecting whether the first device is performing suboptimally comprises detecting that an area of a monitored space is not properly covered by said first device.

3. The system of claim 1 or claim 2, wherein the hub is further configured to detect the first device being defective or performing suboptimally by: generating one or more data quality baseline values; and identifying one or more outlier data values in the usage and monitoring data received from the first device compared to the one or more data quality baseline values.

4. The system of any one of claims 1 to 3, wherein said providing the notification to replace the first device comprises providing a suggestion of one or more replacement devices.

5. The system of any one of claims 1 to 4, wherein the first device is demountable insert configured to be removably inserted into a fixed receptacle body coupled to a physical infrastructure; andwherein said providing the notification to the user to relocate the first device comprises providing a location of another fixed receptacle body to relocate the demountable insert therein.

6. The system of any one of claims 1 to 5, wherein the one or more sensors include at least one of: a temperature sensor, a microphone, a humidity sensor, an air quality sensor, door contact sensor, motion sensors, a camera, or a power consumption sensor.

7. The system of any one of claims 1 to 6, wherein the hub is further configured to monitor, from the usage and monitoring data, one or more significant events related to daily living activities of an individual.

8. The system of claim 7, wherein the one or more significant events include a significant acoustic event.

9. The system of any one of claims 1 to 8, wherein said detecting whether the first device is defective is done by, at least in part, detecting by the hub an abnormal power usage by the first device.

10. The system of any one of claims 1 to 9, wherein the hub is further configured to, upon detecting the first device, reconfigure one or more other devices of the one or more loT devices to monitor, at least in part, one or more environmental parameters originally monitored by the first device.

11. A computer-implemented method for adaptive sensing, comprising the steps of: acquiring, via a one or more internet of things (loT) devices, usage and monitoring data; receiving, at a hub device communicatively coupled to the one or more loT devices via a network, the usage and monitoring data; detecting, via the usage and monitoring data, whether a first device of the one or more loT devices is defective or performing suboptimally; and upon detecting the first device, providing consistent or increased sensing coverage by: reconfiguring at least one of the one of the one or more loT devices; or providing a notification to a user to reconfigure, relocate or replace the first device, or another device of the one or more loT devices.

12. The computer-implemented method of claim 11, wherein detecting whether the first device is performing suboptimally comprises detecting that an area of a monitored space is not properly covered by said first device.

13. The computer-implemented method of claim 11 or claim 12, wherein detecting the first device being defective or performing suboptimally comprises the steps of: generating one or more data quality baseline values; and identifying one or more outlier data values in the usage and monitoring data received from the first device compared to the one or more data quality baseline values.

14. The computer-implemented method of any one of claims 11 to 13, wherein said providing the notification to replace the first device comprises providing a suggestion of one or more replacement devices.

15. The computer-implemented method of any one of claims 11 to 14, wherein the first device is a demountable insert configured to be removably inserted into a fixed receptacle body coupled to a physical infrastructure; and wherein said providing the notification to the user to relocate the first device comprises providing a location of another fixed receptacle body to relocate the demountable insert therein.

16. The computer-implemented method of any one of claims 11 to 15, wherein the one or more sensors include at least one of: a temperature sensor, a microphone, a humidity sensor, an air quality sensor, door contact sensor, motion sensors, a camera, or a power consumption sensor.

17. The computer-implemented method of any one of claims 11 to 16, wherein the usage and monitoring data is used to monitor one or more significant events related to daily living activities of an individual.

18. The computer-implemented method of claim 17, wherein the one or more significant events include a significant acoustic event.

19. The computer-implemented method of any one of claims 11 to 18, wherein said detecting whether the first device is defective is done by, at least in part, detecting by the hub an abnormal power usage by the first device.

20. The computer-implemented method of any one of claims 11 to 19, wherein upon the hub detecting the first device, the method further comprising the step of reconfiguring, by the hub device, one or more other devices of the one or more loT devices to monitor, at least in part, one or more environmental parameters originally monitored by the first device.

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