Dynamic sensing and control system using artificial intelligent techniques for non-uniform indoor environment

Abstract

Traditional ventilation systems have difficulty in effectively capturing the dynamic and non-uniform distribution of indoor environment, making it difficult to meet the dynamic demand of real-time indoor environment control. This results in a large amount of energy consumption, and the comfort of indoor personnel is not guaranteed. Microsensors are used to monitor indoor air quality for responding to indoor environmental conditions and providing real-time regulation of indoor ventilation system. However, the monitoring by a single microsensor cannot reflect the global non-uniform indoor environment and can easily lead to ineffective control of indoor environment and thermal discomfort for personnel. Increased number of sensors can lead to wasted monitoring resources and inconvenient installation in the room. Therefore, this study developed dynamic ventilation control system based on “limited monitoring - fast prediction - real-time control” method. The system realized online transmission and reception of indoor environment monitoring data through wireless communication technology. Combined with fast prediction model to obtain the optimal air change rate per hour (ACH) value of indoor environment, the real-time regulation and intelligent control of indoor ventilation system can be realized, further promoting a balance between energy consumption (up to 60% ventilation energy savings) and indoor environmental quality. This work can provide important strategies and technologies for the construction and implementation of intelligent ventilation control systems.