Heating and cooling systems at various geographical locations are controlled by a central energy management service unit to maintain comfortable indoor temperatures. In some weather conditions, people may intuitively prefer a slightly warmer or cooler indoor temperature. In systems equipped with environmental learning capabilities, an apparent outdoor temperature is determined based on the geographic location itself, the season at the geographic location, the forecasted actual temperature, and one or more seasonal weather factors such as wind velocity or humidity. The apparent temperature and a trained machine learning system are used to select an automated schedule for the geographic location to be directly transmitted to devices at the location. The automated schedule can vary from typical schedules by causing the heating and cooling systems to maintain a temperature that is slightly warmer or cooler than typical indoor temperatures.

A method and system of activating a fan for an air conditioning system is disclosed. Upon the sensing of rain in the proximity of the air conditioning system, such as a condenser, a fan is activated. The fan is configured to drive air and rain through the condenser. The fan can be configured to operate periodically or for a pre-set amount of time while rain is being sensed.

The present disclosure relates to a technology for Sensor Networks, Machine to Machine (M2M), Machine Type Communication (MTC), and Internet of Things (IoT). The present disclosure may be used for an intelligent service (smart home, smart building, smart city, smart car or connected car, health care, digital education, retail business, security and safety-related service, etc.) that is based on the above technologies. The present invention, with respect to a set temperature control method, is characterized by comprising the steps of: setting a control section which is a time section for controlling a set temperature in a certain space; collecting user set temperature information according to weather information for each control section, and predicted weather information; determining set temperature control information for each of the control sections on the basis of the collected set temperature information; and controlling the set temperature in the certain space on the basis of the set temperature control information determined for each of the control sections and the predicted weather information.

A method of and system for automatically adjusting airflow and sensors for use therewith are disclosed. A sensor assembly includes a first face on an opposite side of the sensor assembly relative to a second face. The assembly includes an electrical plug on the first face and an electrical outlet on the second face. The electrical outlet is of a same type that is complimentary to the electrical plug on the first face. The assembly includes a sensor for sensing a value of an environmental variable in a space and a sensor communication system for transmitting and receiving information. A sensor system includes a plurality of sensor assemblies disposed in a building. Each sensor assembly includes a sensor for sensing a value of an environmental variable of the space within which the sensor is placed. The system determines gradient values for the sensed environmental variable.

Methods and systems are described for generating weather related notices using features of a home automation system. According to at least one embodiment, an apparatus for generating weather related notices with a home automation system includes a processor, a memory in electronic communication with the processor, and instructions stored in the memory. The instructions are executable by the processor to receive weather data about current weather conditions, receive status information about at least one barrier of a property monitored by the home automation system, and generate at least one notice based at least in part on the weather data and the status information.

Provided is a server that communicates, via a network, with at least one air conditioner that executes a normal operation or a loosening operation includes a determination unit that determines a heat exposure period for each air conditioning target space, the indoor solar irradiance information indicating a transition of solar irradiance, and the heat exposure period being a time duration in which an environment in the air conditioning target space is likely to be influenced by solar radiation, a generation unit that generates operation plan information of designating a loosening operation period, the loosening operation period being a time duration in which the air conditioner is caused to execute the loosening operation, and a supply unit that supplies the operation plan information to the air conditioner via the network to cause the air conditioner to execute the loosening operation in the loosening operation period.

A method includes determining control setpoints for equipment based on a time-varying availability of green energy and revenue from an incentive program of an energy provider. The method also includes controlling the equipment using the control setpoints.

An artificial intelligence (AI) based apparatus and method for forecasting energy usage receives a request for providing power usage forecasting information of a first period including a current month with respect to an electronic apparatus of a user, divides a use period of the electronic apparatus into first to third sections, loads, from a memory, power actual-use data of a user or a plurality of users during the use period or a predetermined second period before the current month, calculates a daily forecasting weight given a weight based on weather or holiday information of the first period, and generates the power usage forecasting information based on the power actual-use data.

During an initial period of time, an HVAC controller receives an indoor humidity and an outdoor humidity. A record of an energy demand of the HVAC system is stored for each indoor humidity and outdoor humidity. For a future time period, an anticipated energy demand of the HVAC system is determined. The controller then recursively determines, for each of a plurality of time points within the future time period, an anticipated indoor humidity value using the anticipated energy demand and the record of the energy demand. The HVAC system is operated based at least in part on the anticipated indoor humidity value.