Computerized systems and methods for dynamically determined temperature balancing

Abstract

Disclosed are systems and methods that provide a novel framework for temperature balancing within areas of a location. The framework provides functionality for collecting temperature sensor data throughout the location that can be leveraged by the location's thermostat to control and manage the location's climate across varying zones and location-specific temperature settings. The disclosed systems and methods provide functionality for monitoring temperatures remotely (e.g., away from the thermostat via strategically positioned sensors), and determining when to circulate the air. Accordingly, the heating and / or cooling elements of the HVAC system may not be engaged until the fan has iteratively attempted to balance the temperature. Accordingly, the disclosed HVAC system can include an air circulation feature that run a predetermined percentage of the time (e.g., 30%), whereby its runtime and speed can be based on the collected sensor data.

Description

CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the benefit of, and priority to, U.S. Provisional Patent Application No. 63 / 478,079, filed Dec. 30, 2022, its entirety of which is incorporated herein by reference.FIELD OF THE DISCLOSURE

[0002] The present disclosure is generally related to a climate-control system, and more particularly, to a decision intelligence (DI)-based computerized framework for real-time temperature balancing within a location.BACKGROUND

[0003] Conventional heating, cooling and ventilation (HVAC) systems include functionality for circulating air between zones of a location (e.g., building, home, and the like, for example). In most cases, this can involve activating (e.g., opening) an HVAC damper (or duct damper). However, this simply enables air to freely flow from one location to another location, which in some instances, may be propelled via a fan. In other cases, conventional systems can utilize multiple thermostats, so that air deviations among portions of the location can be neutralized via each thermostats' activation. Again, this does not address the underlying functional concerns of enabling an HVAC system to balance temperatures within a location.SUMMARY OF THE DISCLOSURE

[0004] According to some embodiments, the disclosed systems and methods provide a temperature balancing framework that leverages sensor-collected temperatures throughout a location, in order for a thermostat to control and manage a climate within the location, across varying zones (or areas) and settings for each specific zone and / or the location.

[0005] For example, some homes have large temperature differentials between rooms—e.g., basements can be very cold while the upstairs bedrooms remain warm even when the HVAC system is operating within specifications. This can cause pockets of air within the home to be uncomfortable to the occupants.

[0006] Conventional techniques for addressing this type of issue, among others, as discussed above, can involve damper manipulation and / or multiple thermostats for a single HVAC system. This, however, does not provide a functional improvement as to how temperature balancing can be achieved. That is, in addition to the excessive resource expenditure (e.g., electricity / energy, for example) via multiple thermostats over a single thermostat, simply moving air between areas of the location does not account for the temperature sensor data of those specific areas. Indeed, enabling dampers to be activated so that air can freely flow does not impart a functional improvement for enabling that airflow. Moreover, there currently does not exist a climate system that accounts for specifically collected temperature sensor data, as discussed herein.

[0007] Thus, in some embodiments, the disclosed systems and methods provide functionality for monitoring temperatures remotely (e.g., away from the thermostat via strategically positioned sensors, as discussed below), and determining when to circulate the air. In some embodiments, the heating and / or cooling elements of the HVAC system may not be engaged (or their execution may be held in abeyance) until the fan has attempted to balance the temperature as indicated by the sensors within the location. In some embodiments, for example, the disclosed HVAC system can include an air circulation feature (e.g., referred to as an “economic” or “eco” feature, used interchangeably) that runs a predetermined (or dynamically determined) percentage of the time (e.g., 30%), whereby its runtime and speed can be deterministically-based on the collected sensor data, as discussed herein.

[0008] According to some embodiments, a method is disclosed for real-time temperature balancing within a location. 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-transitory computer-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 real-time temperature balancing within a location.

[0009] In accordance with some 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 by at 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

[0010] 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:

[0011] 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;

[0012] FIG. 2 is a block diagram illustrating components of an exemplary system according to some embodiments of the present disclosure;

[0013] FIG. 3A and FIG. 3B illustrate an exemplary workflow according to some embodiments of the present disclosure;

[0014] FIG. 4 depicts an exemplary implementation of an architecture according to some embodiments of the present disclosure;

[0015] FIG. 5 depicts an exemplary implementation of an architecture according to some embodiments of the present disclosure; and

[0016] FIG. 6 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

[0017] The present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, which form a part 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 hardware, 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.

[0018] 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.

[0019] 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, may 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.

[0020] 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 functionality / acts involved.

[0021] 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 non-removable 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 used to tangibly store the desired information or data or instructions and which can be accessed by a computer or processor.

[0022] 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.

[0023] 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.

[0024] 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, 4th or 5th generation (2G, 3G, 4G or 5G) cellular technology, mobile edge computing (MEC), Bluetooth, 802.11b / 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.

[0025] 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.

[0026] 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 of 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.

[0027] 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.

[0028] 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.

[0029] Certain embodiments and principles will be discussed in more detail with reference to the figures. According to some embodiments, the disclosed systems and methods provides a novel framework that functions to enable real-time temperature balancing within a location, as discussed herein. In some embodiments, as discussed herein, a location can refer to any type of definable and / or confined geographic and / or physical area for which an HVAC and / or baseboard climate system can be applied, such as, not limited to, a home, office, building, garage and the like.

[0030] For purposes of this disclosure, the disclosed framework can operate in connection with a thermostat(s) associated with a HVAC, baseboard and / or any other type of known or to be known climate control system for which heating, cooling and ventilation can be effectuated for the location; therefore, for ease of explanation, reference throughout will be made pursuant to a “climate system” (or climate-control system, used interchangeably), which should be understood to refer to any type of known or to be known heating, cooling and / or ventilation system for which a climate (e.g., temperature, for example) setting can be set, maintained, controlled and / or modified.

[0031] Accordingly, while the discussion herein will be in reference to a temperature setting and temperature measurements associated with a location's climate system, it should not be construed as limiting, as any type of known or to be known setting (or attribute) associated with a location can be configured, managed and controlled according to the disclosed systems and methods without departing from the scope of the instant application. For example, such settings can be in reference to, but not limited to, humidity, lighting, energy consumption, gas usage, water usage, security settings (e.g., arm / disarm system), and the like, or some combination thereof. For example, as based on the discussion herein, a security system may be armed and / or disarmed based on whether particular users are determined to be located with a geofenced area associated with the location.

[0032] With reference to FIG. 1, system 100 is depicted which includes UE 102 (e.g., a client device, as mentioned above and discussed below in relation to FIG. 6), sensors 110, network 104, cloud system 106, database 108, balancing engine 200 and peripheral device 112. 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.

[0033] According to some embodiments, user equipment (UE) 102 can be any type of device, such as, but not limited to, a mobile phone, tablet, laptop, sensor, Internet of Things (IoT) device, autonomous machine, and any other device equipped with a cellular or wireless or wired transceiver. In some embodiments, UE 102 can be a device associated with an individual (or set of individuals) for which disclosed services are being provided. In some embodiments, UE 102 may correspond to a device of a HVAC or climate-control related entity (e.g., a HVAC provider, whereby the device can be and / or can have corresponding sensors 110, as discussed herein).

[0034] In some embodiments, peripheral device 112 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 watch), printer, speaker, sensor, and the like. In some embodiments, peripheral device 112 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, Bluetooth™, Bluetooth Low Energy (BLE), NFC, and the like.

[0035] According to some embodiments, a sensor 110 can correspond to sensors associated with a location of system 100 for which temperature measurements can be made. In some embodiments, the sensors 110 can be associated with security sensors, such as, for example, cameras, glass break detectors, motion detectors, door and window contacts, heat and smoke detectors, carbon monoxide (CO2) detectors, passive infrared (PIR) sensors, and the like. In some embodiments, the sensors 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 phones, smart watches or other wearables, tablets, personal computers, and the like, and some combination thereof. Thus, the sensors 110 can be, wholly or in part, part of an IoT sensor network. For example, the sensors 110 can include the sensors on UE 102 (e.g., smart phone) and / or peripheral device 112 (e.g., a paired smart watch).

[0036] 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.

[0037] 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 service 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 temperature control system provider, which has associated network resources hosted on the internet or private network (e.g., network 104), which enables (via engine 200) the temperature management discussed herein.

[0038] 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 UE 102 / device 112 and the UE 102 / device 112, sensors 110, and the services and applications provided by cloud system 106 and / or balancing engine 200.

[0039] In some embodiments, for example, cloud system 106 can provide a private / proprietary climate management platform, whereby engine 200, discussed infra, corresponds to the novel functionality system 106 enables, hosts and provides to a network 104 and other devices / sensors / platforms operating thereon.

[0040] Turning to FIG. 4 and FIG. 5, 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 106 such as, but not limiting to: infrastructure a service (IaaS) 510, platform as a service (PaaS) 508, and / or software as a service (SaaS) 506 using a web browser, mobile app, thin client, terminal emulator or other endpoint 504. FIG. 4 and FIG. 5 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.

[0041] 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), a plurality of platforms, and / or UE 102 and / or sensors 110. 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.

[0042] Balancing engine 200, as discussed above and further below in more detail, can include components for the disclosed functionality. According to some embodiments, balancing engine 200 may be a special purpose machine or processor, and can be hosted by a device on network 104, within cloud system 106 and / or on UE 102 (and / or peripheral device 112). In some embodiments, engine 200 may be hosted by a server and / or set of servers associated with cloud system 106.

[0043] According to some embodiments, as discussed in more detail below, balancing engine 200 may be configured to implement and / or control a plurality of services and / or microservices, where each of the plurality of services / microservices are configured to execute a plurality of workflows associated with performing the disclosed temperature management. Non-limiting embodiments of such workflows are provided below in relation to at least FIG. 3A and FIG. 3B.

[0044] According to some embodiments, as discussed above, balancing 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 server(s), network location and / or other type of network resource associated with system 106. In some embodiments, engine 200 may function as application installed and / or executing on UE 102. 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.

[0045] As illustrated in FIG. 2, according to some embodiments, balancing engine 200 includes identification module 202, analysis module 204, determination module 206 and control 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 systems 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.

[0046] Turning to FIG. 3A and FIG. 3B, provided is Process 300 which details non-limiting example embodiments for the disclosed temperature management framework. According to some embodiments, the disclosed framework (e.g., via engine 200) operates to collect temperature sensor data throughout the location that can be leveraged by the location's thermostat to control and manage the location's climate across varying zones and location-specific temperature settings. As discussed herein, the disclosed systems and methods provide functionality for monitoring temperatures remotely (e.g., away from the thermostat via strategically positioned sensors), and determining when to circulate the air.

[0047] According to some embodiments, Steps 302-306 and Steps 316-318 of Process 300 can be performed by identification module 202 of balancing engine 200; Step 308 and 320 can be performed by analysis module 204; Steps 310-312 and Step 324 can be performed by determination module 204; and Steps 314 and 322 can be performed by control module 208.

[0048] According to some embodiments, Process 300 begins with Step 302 where engine 200 identifies a temperature setpoint for a location. In some embodiments, the setpoint can correspond to, but not be limited to, an operation mode (e.g., a scheduled heating / cooling pattern for a predetermined period of time—for example, heat the upstairs of the home from 6 AM to 8 AM to 72 degrees Fahrenheit), a setting (provided by a user or automatically determined by the system), a current temperature, an outside temperature, a “hold” temperature for the climate system, and the like, or some combination thereof.

[0049] In some embodiments, Step 302 can also involve identifying a temperature differential, which as discussed in more detail below, can be a value or range that is utilized to determine whether temperature balancing functions via eco-mode operations are required, are to be executed, and / or are to be requested. For example, a temperature differential can include information related to, but not limited to, a difference value between the temperature within the location (e.g., in a specific room, in a zone, and the like, for example), a different value between temperature readings from adjacent and / or remotely located sensors in the location, and the like. In some embodiments, the computed values can correspond to current temperature values, values from a range of time periods and / or an average for a predetermined period of time.

[0050] In Step 304, engine 200 can monitor the location. In some embodiments, the monitoring performed by engine 200 can be performed to determine if there are temperature imbalances within the location. In some embodiments, such monitoring can involve collecting temperature sensor data from each of the sensors at the location (e.g., sensors 110, as discussed above, for example).

[0051] Accordingly, in the some embodiments, the sensor data can include, but is not limited to, a position (or sub-location) within the location (e.g., data for the basement, living room and kitchen, for example), and a temperature measurement (e.g., in Fahrenheit, Celsius, or any other type of temperature measurement value).

[0052] In some embodiments, engine 200 can monitor the location continuously, and / or according to a predetermined time interval. Such monitoring of the location can be performed via the location's sensors, as discussed above. In some embodiments, the monitoring can involve periodically pinging each or a portion of the sensors at the location, and awaiting a reply. In some embodiments, the monitoring can involve push and / or fetch protocols to collect sensor data from each sensor.

[0053] In Step 306, based on the monitoring of Step 304, engine 200 can determine a first temperature for each sensor (or sub-location within the location). For example, engine 200 can determine, based on the sensors in each room of a house, the current temperature in the master bedroom and the basement.

[0054] In Step 308, engine 200 can determine whether the first current temperature (from Step 308) exceeds the temperature setpoint. That is, in some embodiments, for example, Step 308 can involve engine 200 determining whether the current temperature values of the master bedroom and basement are outside the temperature differential value from the temperature setpoint. For example, the temperature setpoint (from Step 302) is 72 degrees Fahrenheit (° F.), and the master bedroom temperature value is 73° F. and the basement is 68° F.; and the temperature differential is 3° F. Thus, according to Step 308, engine 200 can determine that the temperature value for the basement exceeds the temperature setpoint via the temperature differential.

[0055] In some embodiments, engine 200 can perform Steps 306-308 by translating the temperature sensor readings to n-dimensional vectors, whereby the vectors of the first temperatures can be computationally compared against vectors of the setpoint and temperature differential. In some embodiments, the nodes on the temperature vectors can correspond to temperature values, and each edge can indicate a time period and / or sub-location (or area or zone within the location) between each collected temperature reading (as per a monitoring, via Step 304, time period).

[0056] Accordingly, in some embodiments, Step 308 (and in some embodiments, Step 306) can involve engine 200 analyzing the collected temperature sensor data via any type of known or to be known computational analysis technique, algorithm, mechanism or technology. In some embodiments, engine 200 may include a specific trained artificial intelligence / machine learning model (AI / ML), a particular machine learning model 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.

[0057] 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.

[0058] According to some embodiments and, optionally, in combination of any embodiment described above or below, a neutral 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:

[0059] a. define Neural Network architecture / model,

[0060] b. transfer the input data to the neural network model,

[0061] c. train the model incrementally,

[0062] d. determine the accuracy for a specific number of timesteps,

[0063] e. apply the trained model to process the newly-received input data,

[0064] f. optionally and in parallel, continue to train the trained model with a predetermined periodicity.

[0065] 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 topology, 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.

[0066] Thus, engine 200 can determine whether first temperature values need to be balanced or adjusted. According to some embodiments, information related to the determination of Step 308 can be stored in database 108, which can include, but not be limited to, an identifier (ID) of the sensor for which a temperature was determined, the determined first temperature, setpoint value, temperature differential value, time, date, and the like.

[0067] In some embodiments, when the first temperature for a location is determined to not exceed the temperature setpoint (e.g., not be a temperature measurement value that is outside + / −the range of the temperature setpoint), engine 200 can proceed from Step 308 to Step 310, where engine 200 can continue the monitoring of Step 304 for that sub-location.

[0068] By way of a non-limiting example, continuing with the above example, in some embodiments, since the master bedroom is within a + / −range according to the temperature differential to the temperature setpoint, engine 200 can determine that a temperature balancing for the sensor / zone associated with the master bedroom need not be performed, and the temperature values for that room can continue to be monitored.

[0069] To the contrary, continuing with the non-limiting example, the temperature value of the basement needs to be balanced. Therefore, according to some embodiments, engine 200 can proceed from Step 308 to Step 312 for the basement, whereby a runtime and speed for a fan at the location can be determined.

[0070] Accordingly, Step 312 can be performed for areas (or sub-locations) within the location where there is a temperature imbalance (e.g., a current first temperature being a value above / below the temperature setpoint beyond the temperature differential). Here, according to the disclosed example, the basement's first temperature is 4 degrees (e.g., +1 degree) outside the temperature differential of the temperature setpoint.

[0071] Accordingly, Step 312 can analyze the attributes of the area / sub-location, and determine the runtime and / or speed of the fan for which temperature balancing can be performed. In some embodiments, engine 200 can further analyze the collected sensor data, as discussed above, which can be leveraged to discern, determine or otherwise identity fan values for execution. In some embodiments, engine 200 can execute to collect further sensor data.

[0072] In some embodiments, therefore, the sensor data leveraged to determine the runtime and / or speed of the fan can include, but is not limited to, ID of sensor, position within the home (e.g., below ground, on the first floor, second floor, front of house, side of house, back of house, time, date,—outside temperature, temperature setpoint, temperature differential, + / −value of the first temperature beyond the temperature differential, and the like, or some combination thereof.

[0073] According to some embodiments, engine 200 can utilize any of the known or to be known ML / AI algorithms or mechanisms discussed above to analyze the sensor data to determine the fan's executable values. For example, engine 200 can analyze the basement's sensor data, and via a neural network algorithm, determine that the fan needs to run for 45 minutes at a speed setting of “high” (as compared to speeds of “low” and “medium”).

[0074] In some embodiments, Step 312 can involve engine 200 identifying which fan to utilize, and which sub-location of the home to utilize to circulate the air. For example, if the kitchen's first temperature is 76° F. (as determined from the aforementioned steps of Process 300, discussed supra), engine 200 can determine that since there is a −4 ° F. (of the basement) to +4° F. (of the kitchen) ratio to the temperature setpoint, a fan associated with air ducts between the kitchen and basement can be utilized to circulate air between these regions.

[0075] Accordingly, in Step 314, the determined information from Step 312 can be compiled into executable instructions, and provided to the thermostat, whereby the thermostat can execute the fan control provided therein. In some embodiments, such information as associated with the instructions can be stored in database 108, as discussed above.

[0076] In some embodiments, the execution of the fan, as per Step 314's execution by engine 200, can be performed independent of heating and cooling operations of the thermostat / HVAC system. That is, the fan operates while the heating and cooling elements of the HVAC system (at least for the regions of the location for which circulation is being performed) remain in an “off status.”

[0077] Accordingly, upon executing Step 314, the fan can execute at the determined speed for the determined runtime. At the conclusion of its runtime, engine 200 can perform monitoring of the location, as per Step 316, which can be performed in a similar manner as discussed above at least in relation to Step 304.

[0078] In some embodiments, such monitoring can be for the area of the location for which temperature balancing was performed (via Steps 312-314, as discussed supra). In some embodiments, an entirety of the location can be monitored and / or a varying subset of each sub-location within the home. Accordingly, Step 316 can involve collecting a new version of sensor data from the temperature sensors at the location.

[0079] In some embodiments, Step 314 can involve turning the fan to “on” and only turning it off upon the temperature differential range to the temperature setpoint being met. This can, therefore, involve performing the monitoring of Step 316 while the fan is operating. Thus, in some embodiments, Step 314 can involve executing the fan until an “off” instruction is received due to the real-time, dynamic monitoring and temperature sensor collection, as discussed above.

[0080] In Step 318, engine 200 can determine a second current temperature for the location and / or each of the sub-locations. For example, at the conclusion of the runtime of the fan (in Step 314), engine 200 can determine a current temperature of the basement, which provides an indication of how effective the fan's execution was in balancing the temperatures between the basement and kitchen (among other areas of the location respective to the temperature setpoint). Accordingly, the temperature determination of Step 318 can be performed in a similar manner as discussed above at least in relation to Step 306, discussed supra.

[0081] In Step 320, engine 200 can determine whether the second current temperature corresponds to the temperature setpoint (e.g., within the temperature differential range). In other words, engine 200 can determine whether the adjusted temperature (via Step 314) comports with the temperature differential range around the temperature setpoint.

[0082] For example, engine 200 can determine whether the adjusted temperature of the basement is within a 3 degree range of the 72° F. setpoint.

[0083] According to some embodiments, when the second current temperature (from Step 318) is not within the range, processing can proceed from Step 320 to Step 322 where engine 200 can turn-on the climate system. For example, if the basement temperature did not raise at least 1 degree from 68° F. via the fan's runtime execution, then engine 200 can turn on the heating elements of the HVAC for at least the basement zone / area. Thus, Step 322 can involve determining which element (e.g., heating or cooling) to perform based on the second current temperature's relationship to the temperature setpoint.

[0084] According to some embodiments, when the second current temperature (from Step 318) is within range of the temperature setpoint according to the temperature setpoint value, engine 200 can perform Step 324, whereby engine 200 can continue monitoring of the location, as discussed above. Accordingly, Step 324 can be performed when it is determined that the fan-based temperature balancing was successful in balancing the temperature, which as discussed herein, enables the temperature balancing without execution (e.g., independent) of the heating / cooling elements of the climate system.

[0085] According to some embodiments, during the processing of Process 300, as discussed above, status notifications of the operational status of the climate system can be displayed and / or provided to a user, and updated according to specific modes of the thermostat (e.g., fan execution, monitoring modes and / or heating / cooling modes, as discussed supra). In some embodiments, the status can be provided via any type of known or to be known message that can be displayed on a user device, within an interface of an application, a display of the climate system, on a webpage, and the like, or some combination thereof. In some embodiments, such messages can be, but are not limited to, application notifications, emails, SMS message, and the like.

[0086] In some embodiments, such messages can enable a viewing user capabilities to manage, modify and / or request specific tasks related to the temperature balancing discussed above. For example, a user can approve the execution of a fan to balance the temperature related to a specific zone. In another example, a user can provide feedback that adjusts how the long the fan may run. In another example, a user can decline and / or “snooze” execution of a fan (as per Step 314) and / or execution of the climate system (as per Step 322).

[0087] FIG. 6 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 600 may include many more or less components than those shown in FIG. 6. However, the components shown are sufficient to disclose an illustrative embodiment for implementing the present disclosure. Client device 600 may represent, for example, UE 102 discussed above at least in relation to FIG. 1.

[0088] As shown in the figure, in some embodiments, Client device 600 includes a processing unit (CPU) 622 in communication with a mass memory 630 via a bus 624. Client device 600 also includes a power supply 626, one or more network interfaces 650, an audio interface 652, a display 654, a keypad 656, an illuminator 658, an input / output interface 660, a haptic interface 662, an optional global positioning systems (GPS) receiver 664 and a camera(s) or other optical, thermal or electromagnetic sensors 666. Device 600 can include one camera / sensor 666, or a plurality of cameras / sensors 666, as understood by those of skill in the art. Power supply 626 provides power to Client device 600.

[0089] Client device 600 may optionally communicate with a base station (not shown), or directly with another computing device. In some embodiments, network interface 650 is sometimes known as a transceiver, transceiving device, or network interface card (NIC).

[0090] Audio interface 652 is arranged to produce and receive audio signals such as the sound of a human voice in some embodiments. Display 654 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 654 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.

[0091] Keypad 656 may include any input device arranged to receive input from a user. Illuminator 658 may provide a status indication and / or provide light.

[0092] Client device 600 also includes input / output interface 660 for communicating with external. Input / output interface 660 can utilize one or more communication technologies, such as USB, infrared, Bluetooth™, or the like in some embodiments. Haptic interface 662 is arranged to provide tactile feedback to a user of the client device.

[0093] Optional GPS transceiver 664 can determine the physical coordinates of Client device 600 on the surface of the Earth, which typically outputs a location as latitude and longitude values. GPS transceiver 664 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 600 on the surface of the Earth. In one embodiment, however, Client device 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.

[0094] Mass memory 630 includes a RAM 632, a ROM 634, and other storage means. Mass memory 630 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 630 stores a basic input / output system (“BIOS”) 640 for controlling low-level operation of Client device 600. The mass memory also stores an operating system 641 for controlling the operation of Client device 600.

[0095] Memory 630 further includes one or more data stores, which can be utilized by Client device 600 to store, among other things, applications 642 and / or other information or data. For example, data stores may be employed to store information that describes various capabilities of Client device 600. 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 600.

[0096] Applications 642 may include computer executable instructions which, when executed by Client device 600, transmit, receive, and / or otherwise process audio, video, images, and enable telecommunication with a server and / or another user of another client device. Applications 642 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.

[0097] 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).

[0098] 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.

[0099] 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, 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.

[0100] For the purposes of this disclosure a module is a software, hardware, or firmware (or combinations thereof) system, process or functionality, or component thereof, that 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.

[0101] 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).

[0102] For example, exemplary software specifically programmed in accordance with one or more principles of the present disclosure may be downloadable 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.

[0103] 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 browser 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 software applications at either the client level 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.

[0104] 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.

[0105] 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.

[0106] 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.

Claims

1. A method comprising:identifying, by a device, a temperature setpoint for a location, the temperature setpoint corresponding to a predetermined temperature a climate system is to maintain at the location;determining, by the device, at the location, a first current temperature for the location;comparing, by the device, the first current temperature to the temperature setpoint;determining, by the device, that the first current temperature exceeds the temperature setpoint by at least a threshold amount of degrees;automatically communicating, by the device, a message to a fan associated with the location, the message comprising machine-executable instructions causing the fan to run at a speed and for a time period, wherein the fan runs for the time period separate from any operation mode of the climate system;determining, by the device, at the conclusion of the time period, a second current temperature; anddetermining, by the device, whether the second current temperature corresponds to the temperature setpoint in accordance with the threshold amount of degrees,when the second current temperature is determined to still exceed the temperature setpoint, causing the climate system to turn on, andwhen the second current temperate is determined to correspond to the temperature setpoint, continue monitoring temperatures at the location according to the temperature setpoint.

2. The method of claim 1, further comprising:determining, prior to the conclusion of the time period, that the second current temperature corresponds to the temperature setpoint; andupdating the time period to a time that corresponds to the determination that the second current temperature corresponds to the temperature setpoint.

3. The method of claim 2, wherein the updated time period is used for a basis for running the fan during a next cycle.

4. The method of claim 1, wherein the time period for the fan to run is a time until the second current temperature is determined to correspond to the temperature setpoint.

5. The method of claim 1, wherein the fan executes by circulating air between at least two sub-locations within the location, wherein at least one sub-location corresponds to the first current temperature.

6. The method of claim 1, further comprising:receiving, from a plurality of temperature sensors at the location, temperature sensor data;analyzing the temperature sensor data; anddetermining, for at least one sub-location within the location, the first current temperature.

7. The method of claim 6, wherein the location comprises a thermostat.

8. The method of claim 1, wherein when the first current temperate is determined to correspond to the temperature setpoint, continue monitoring temperatures at the location according to the temperature setpoint.

9. The method of claim 1, wherein the first current temperature exceeds the temperature setpoint by being at least the threshold amount of degrees below or above the temperature setpoint.

10. The method of claim 1, wherein the climate system is a heating, ventilation and air conditioning (HVAC) system.

11. A device comprising:a processor configured to:identify a temperature setpoint for a location, the temperature setpoint corresponding to a predetermined temperature a climate system is to maintain at the location;determine at the location, a first current temperature for the location;compare the first current temperature to the temperature setpoint;determine that the first current temperature exceeds the temperature setpoint by at least a threshold amount of degrees;automatically communicate a message to a fan associated with the location, the message comprising machine-executable instructions causing the fan to run at a speed and for a time period, wherein the fan runs for the time period separate from any operation mode of the climate system;determine at the conclusion of the time period, a second current temperature; anddetermine whether the second current temperature corresponds to the temperature setpoint in accordance with the threshold amount of degrees,when the second current temperature is determined to still exceed the temperature setpoint, cause the climate system to turn on, andwhen the second current temperate is determined to correspond to the temperature setpoint, continue monitoring temperatures at the location according to the temperature setpoint.

12. The device of claim 11, wherein the processor is further configured to:determine, prior to the conclusion of the time period, that the second current temperature corresponds to the temperature setpoint; andupdate the time period to a time that corresponds to the determination that the second current temperature corresponds to the temperature setpoint.

13. The device of claim 11, wherein the processor is further configured to:receive, from a plurality of temperature sensors at the location, temperature sensor data;analyze the temperature sensor data; anddetermine, for at least one sub-location within the location, the first current temperature.

14. A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions that when executed by a device, perform a method comprising:identifying, by the device, a temperature setpoint for a location, the temperature setpoint corresponding to a predetermined temperature a climate system is to maintain at the location;determining, by the device, at the location, a first current temperature for the location;comparing, by the device, the first current temperature to the temperature setpoint;determining, by the device, that the first current temperature exceeds the temperature setpoint by at least a threshold amount of degrees;automatically communicating, by the device, a message to a fan associated with the location, the message comprising machine-executable instructions causing the fan to run at a speed and for a time period, wherein the fan runs for the time period separate from any operation mode of the climate system;determining, by the device, at the conclusion of the time period, a second current temperature; anddetermining, by the device, whether the second current temperature corresponds to the temperature setpoint in accordance with the threshold amount of degrees,when the second current temperature is determined to still exceed the temperature setpoint, causing the climate system to turn on, andwhen the second current temperate is determined to correspond to the temperature setpoint, continue monitoring temperatures at the location according to the temperature setpoint.

15. The non-transitory computer-readable storage medium of claim 14, further comprising:determining, prior to the conclusion of the time period, that the second current temperature corresponds to the temperature setpoint; andupdating the time period to a time that corresponds to the determination that the second current temperature corresponds to the temperature setpoint, wherein the updated time period is used for a basis for running the fan during a next cycle.

16. The non-transitory computer-readable storage medium of claim 14, wherein the time period for the fan to run is a time until the second current temperature is determined to correspond to the temperature setpoint.

17. The non-transitory computer-readable storage medium of claim 14, wherein the fan executes by circulating air between at least two sub-locations within the location, wherein at least one sub-location corresponds to the first current temperature.

18. The non-transitory computer-readable storage medium of claim 14, further comprising:receiving, from a plurality of temperature sensors at the location, temperature sensor data;analyzing the temperature sensor data; anddetermining, for at least one sub-location within the location, the first current temperature.

19. The non-transitory computer-readable storage medium of claim 14, wherein when the first current temperate is determined to correspond to the temperature setpoint, continue monitoring temperatures at the location according to the temperature setpoint.

20. The non-transitory computer-readable storage medium of claim 14, wherein the first current temperature exceeds the temperature setpoint by being at least the threshold amount of degrees below or above the temperature setpoint.

Images