Abstract: The invention provides a non-contact indoor thermal environment control system and a method based on reinforcement learning, which adopts a non-contact measurement mode to collect the video information of indoor personnel and judge the hot/cold state of the personnel through the processing of the video information. It can reduce the intrusiveness caused by the use of measuring equipment. At the same time, the invention adopts the reinforcement learning method to train and obtain the optimal thermal environment control strategy according to the environmental information, the hot and cold state of the personnel and the previous regulation strategy, which not only considers the difference of individual thermal comfort, but also satisfies the dynamic thermal comfort of personnel, improves the regulation efficiency of indoor thermal environment. At the same time, it can reduce the energy consumption of HVAC, achieve a sustainable state of energy saving and environmental protection.

Abstract: The invention relates to an unmanned inspection system and method for HVAC room based on artificial intelligence, which comprises a patrol robot, a motion unit, a mechanical room inspection unit, a fault diagnosis unit, a fault alarm unit and a terminal report unit. The motion unit is used to realize the automatic driving. The mechanical room inspection unit is used to detect the environmental information and the running status of the equipment in the HVAC room. The fault diagnosis unit is used to receive the environmental information and equipment running status and compare the received information with the preset conditions. According to the comparison results, it is judged whether there is a fault. If there is a fault, the fault alarm unit alert the fault information. The invention can realize unmanned automatic inspection, lighten the workload of personnel, and improve the efficiency and accuracy of patrol work.

Abstract: Sunshading louver control system and method based on gesture recognition are provided. Indoor images are collected in real time. Based on the indoor images, an action region of gesture motion is positioned and feature extraction is performed thereon to obtain hand motion parameters. The hand motion parameters are analyzed to obtain gesture information. The gesture information is compared with preset gesture information. When the preset gesture information contains the gesture information, corresponding adjustment is performed on a sunshading louver according to a preset operation logic corresponding to the gesture information. When the preset gesture information does not contain the gesture information, the gesture information is determined to be invalid.

Abstract: Sunshading louver control system and method based on gesture recognition are provided. Indoor images are collected in real time. Based on the indoor images, an action region of gesture motion is positioned and feature extraction is performed thereon to obtain hand motion parameters. The hand motion parameters are analyzed to obtain gesture information. The gesture information is compared with preset gesture information. When the preset gesture information contains the gesture information, corresponding adjustment is performed on a sunshading louver according to a preset operation logic corresponding to the gesture information. When the preset gesture information does not contain the gesture information, the gesture information is determined to be invalid.

Abstract: A control system and a control method of refrigeration in a closed space based on computer vision are provided. An image of a food, temperature and humidity information in the closed space are collected, and a type of the food is identified according to the image. The image is processed through Euler video amplification when food is not packaged to obtain surface color distribution information of the food, a state of the food is determined according to the surface color distribution information and a historical learning result, and a state prompt corresponding to the state of the food is provided to a user. Temperature and humidity in the closed space are regulated according to the state of the food. The state of the food is determined according to storage time and a known quality guarantee period when the food is packaged, and another state prompt is provided to the user.