[Data Science Case] Optimizing Indoor Environment and Reducing Power Consumption with Air Conditioning Control AI

Challenges of creating a suitable indoor environment and energy conservation! A case study on the development of control AI that achieves temperature maintenance.

We will introduce a case study of optimizing indoor environments and reducing power consumption using air conditioning control AI in the manufacturing industry. In environments where temperature management is essential, such as food factories, the challenge was to automatically control air conditioning through AI's autonomous learning to achieve an appropriate indoor environment and energy savings. We adopted a policy to train AI that simultaneously achieves room temperature maintenance and power consumption reduction through reinforcement learning in a simulation environment, aiming for the rapid development of control AI that can be transferred to actual equipment. By using a simulation environment, we successfully accelerated the development of control AI to be 1000 times faster compared to reality. 【Case Overview】 ■Industry: Manufacturing ■Business: Operational Optimization ■Challenges: Operational Optimization, Autonomous Control, Cost Reduction ■Analytics and AI Solutions - Adopted a policy to aim for the rapid development of control AI that can be transferred to actual equipment - Conducted AI development focused solely on maintaining room temperature as a Proof of Concept (PoC) *For more details, please refer to the PDF document or feel free to contact us.

Temperature and Humidity Control