Development and demonstration of air conditioning control methods for spaces with open sections to the outdoors using sensors for the flow of people and air

Summary

Project description

Efficient heating and cooling methods have yet to be established for underground malls with open sections to the outdoors that have larger cooling and heating loads compared to general buildings and a more complicated flow of human traffic. However, now possibilities for air conditioning control have emerged with the progression of IoT technologies in recent years. In this project, we gained insight into the environmental conditions of underground malls to predict human behavior, air and thermal environmental data, etc. Based on these results, we aim to minimize the amount of air and heat consumed through smart controls and significantly reduce CO2 emissions.
In this project, air conditioning and ventilation technologies will be developed using minimal energy by predicting areas where people will be located and the minimum amount of heat and ventilation required to air condition, as well as reusing comfortable air from the vicinity in regard to conventional uniform air conditioning. AI (artificial intelligence) will also be used to predict the flow of human traffic, air flow, and air conditioning and ventilation control.