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.

An environment control system that controls an environment of a subject is provided. The environment control system includes an actuator configured to control an environment of a subject, and a controller configured to control an operation of the actuator. The environment control system includes an inference unit that includes a first learned model and a second learned model. The first learned model has been trained by associating environmental information indicating an environment of a subject with data correlating with one of sleep, excretion, movement, skin, and stress conditions of the subject. The second learned model has been trained by associating the data correlating with one of the sleep, excretion, movement, skin, and stress conditions of the subject with data correlating with a magnitude of one or more risks that may occur with respect to the subject in a future period of time. The environment control system includes an operating condition determining unit configured to, in a case in which data correlating with the magnitude of the one or more risks that may occur with respect to a subject in a future period of time is inferred based on the first and second learned model, evaluate the inferred data to determine an operating condition of the actuator.

A system includes one or more occupancy sensors, one or more environmental sensors and one or more controllable building components. A controller is configured to receive occupancy signals from the one or more occupancy sensors over a building network and to receive indoor air quality parameter signals from the one or more environmental sensors over the building network and to process the received signals to determine whether action is needed to improve one or more environmental conditions within at least some of the plurality of building spaces to reduce the likelihood of disease transmission among occupants of the building. Responsive to determining that action is needed, the controller is configured to provide control signals to one or more of the controllable building components over the building network to improve one or more environmental conditions within at least some of the plurality of building spaces.

The invention discloses a regulating system and method for multilayer shading film of plastic greenhouse with adjustable shading rate. The upper film of the sunshade is a fully transparent film, while the middle film and the lower film are printed with dots, which are interlaced. Through the measurement and comparison of the warm light in the greenhouse, the combined control of the sunshade film is realized. Not only can it adjust its light blocking rate, but it also has a heat insulating effect when there is a certain amount of air in the film.

A central energy facility (CEF) includes a plurality of powered CEF components, a battery unit, and a predictive CEF controller. The powered CEF components include a chiller unit and a cooling tower. The battery unit is configured to store electric energy from an energy grid and discharge the stored electric energy for use in powering the powered CEF components. The predictive CEF controller is configured to optimize a predictive cost function to determine an optimal amount of electric energy to purchase from the energy grid and an optimal amount of electric energy to store in the battery unit or discharge from the battery unit for use in powering the powered CEF components at each time step of an optimization period.

Disclosed is a system, method, and computer program product that employs high dynamic range (HDR) image processing and manipulation algorithms for capturing and measuring real-time sky conditions for processing into control input signals to a building's automated fenestration (AF) system, daylight harvesting (DH) system and HVAC system. The photometer comprises a color camera and a fitted fish-eye lens to capture 360-degree, hemispherical, low dynamic range (LDR) color images of the sky. Both camera and lens are housed in a sealed enclosure protecting them from environmental elements and conditions. In some embodiments the camera and processes are controlled and implemented by a back-end computer.

A machine learning apparatus determines an operation condition of a precooling operation or preheating operation of an air conditioner. The machine learning apparatus includes an acquisition unit and a learning unit. The acquisition unit acquires, as state variables, room temperature data at a time of the precooling operation or preheating operation, set temperature data, and outside air temperature data. The learning unit learns the operation condition of the precooling operation or preheating operation based on the state variables, a room temperature after start of the precooling operation or preheating operation, and a set temperature.

A smart thermostat for controlling the ambient air temperature in a first area when the smart thermostat is located in a second area. One or more desired setpoint temperatures are changed automatically by the smart thermostat based on one or more setpoint modification factors, such as the time of day, current season, location, orientation and present and future weather conditions.

In a control system, a heat load estimation unit, by referring to location information that indicates a location environment of a house H1 and to weather information that indicates a weather forecast for a certain time slot T1, estimates a heat load which depends on solar radiation to the house H1 during the time slot T1. Specifically, the heat load estimation unit checks whether or not there is a building that blocks the solar radiation to the house H1 during the time slot T1 based on the location information when the weather forecast indicated in the weather information is sunny. Further, the heat load estimation unit estimates the heat load which depends on the solar radiation to the house H1 during the time slot T1 according to a result of the check. An operation control unit controls ahead, operation of an air conditioner provided in the house H1 before the time slot T1 according to the heat load estimated by the heat load estimation unit.

Methods, systems, and apparatus for controlling an air flow are described. A monitor obtains an environmental parameter and an air deflector controls the air flow exiting an air duct. An air deflector actuator configures the air deflector, the configuration of the air deflector being based on the environmental parameter.