Disclosed herein are a method of controlling operations of an air conditioner by analyzing a user's behavior pattern, and an air conditioner, the present disclosure according to an embodiment includes an air blower configured to discharge air, a camera configured to acquire images of a space in which an indoor unit of the air conditioner is disposed, and a control unit configured to extract features from the image acquired by the camera, to generate image descriptions, and to control the air conditioner using parameters generated in response to the image descriptions.

Sensing and control apparatus for a building HVAC system includes interior and boundary sensors, such as cameras and thermal sensors, generating sensor signals conveying occupancy-related features for an area. A controller uses the sensor signals to produce an occupancy estimate and to generate equipment-control signals to cause the HVAC system to supply conditioned air to the area based on the occupancy estimate. The controller includes fusion systems collectively generating the occupancy estimate by corresponding fusion calculations, the fusion systems producing a boundary occupancy-count change based on sensor signals from the boundary sensors, an interior occupancy count based on sensor signals from the interior sensors, and the overall occupancy estimate. Fusion may be of one or multiple types including cross-modality fusion across different sensor types, within-modality fusion across different instances of same-type sensors, and cross-algorithm fusion using different algorithms for the same sensor(s).

A multipurpose distributed building automation device, also known as a “smart home device”, and a method for implementing a distributed building automation network are provided. The devices according to the disclosure are used for controlling devices and building services technology in the context of building automation. The device according to the disclosure has a housing and a display and comprises the following components: at least one sensor, at least one actuator and at least one computing unit, wherein the components are arranged in the housing and thus combined in one device and the device is functional without a connection to a central gateway or network device and the device is embodied for installation in a flush-mounting box or as a replacement device for a wall thermostat and has a power supply unit or voltage converter.

The framework herein may be called outcome-based ventilation (OBV) for evaluating ventilation rates (VR) in commercial buildings and using a system to make informed control decisions based on the resultant indoor air quality (IAQ) and energy consumption outcomes. A ventilation control system includes a ventilation system that provides air circulation to a building and a controller that controls the ventilation system based on input that include a current ventilation rate. The system also includes an optimization system that drives the controller based on factors like building and pollution transport models, scientific estimates of ventilation impacts on productivity, sick leave, and health, user preference parameters, and weather, pollution, and price forecasts.

A method can include obtaining a set of images of a set of occupants located in an interior environment. The interior environment can have a first temperature. The method can include identifying, based on the set of images, a set of occupant characteristics corresponding to the set of occupants. The method can include obtaining a second temperature of an external environment. The method can include generating, by comparing the set of occupant characteristics to the second temperature, a discrepancy factor. The method can include determining that the discrepancy factor exceeds a threshold. The method can include initiating, in response to the determining that the discrepancy factor exceeds the threshold, a modification of the first temperature.

An air conditioning system includes an air conditioner, a detector, a transmitter, and a control unit. The air conditioner includes an indoor unit. The detector detects a user action toward the indoor unit. The transmitter transmits first information on the indoor unit to a terminal of the user. The control unit causes the transmitter to transmit the first information to the terminal when the detector detects the user action.

Disclosed is an electronic apparatus capable of managing cooling or heating and a controlling method thereof capable of operating even in the Internet of Things environment through a 5G communication network, and the electronic apparatus of the present disclosure can intensively control cooling or heating in an area where users are dense. The electronic apparatus capable of managing cooling or heating of the present disclosure can acquire a space where the user is located as a 3D structure, learn a distribution of the user distributed in the acquired 3D structure, and then control cooling or heating intensively in the area where the user can be distributed, thereby enabling efficient cooling or heating based on an area requiring the cooling or heating.

A method for detecting air-conditioning instructions, a control device and an air-conditioning system are provided. According to the method, first position information of a preset user relative to an indoor unit is acquired, second position information of the preset user relative to a line control device of the indoor unit according to the first position information is determined, and detection parameters of a voice module in the line control device according to the second position information is determined. The control device has a memory and a processor. The memory stores an air-conditioning instruction detection program. The program is executable by the processor to implement the method. The air-conditioning system has the control device.

An air conditioning system includes one or more cameras, one or more air conditioning operation units, and an air conditioner control unit that obtains, via the one or more cameras, images of a surrounding environment of the air conditioning operation units, and determines a first set of factors, including a layout of the surrounding environment, based on analysis of the images through predefined machine learning models. The control unit, in accordance with the first set of factors that has been determined based on the analysis of the images through the predefined machine learning models, selects a first operation profile from a plurality of predefined operation profiles to control the air conditioning operation units.

Various embodiments include a site controller comprising: a processor; a memory storing a parametrized model for control of a HVAC system; a sensor interface connected to a first sensor; an actuator interface connected to a first actuator; and a cloud interface connected to a remote controller. The processor is configured to: read a first set of sensor signals from the first sensor; process the first set of signals into a set of measured values; transmit the measured values to the remote controller; in response, receive a set of model parameters from the remote controller; read the parametrized model from the memory; read an additional sensor signal from the first sensor; compute an actuator setting signal from the additional signal using the parametrized model and the set of model parameters; and transmit the actuator setting signal to the first actuator.