A Proposal of Air-Conditioning Guidance System Using Discomfort Index

Nowadays, global warming has considered a key environmental issue associated with the pursuit of sustainable societies around the world. Therefore, it appears to be critical how to achieve the best usage of an air conditioner (AC) to reduce unnecessary energy consumption. In addition, it would be beneficial to elders who tend to suffer from heatstroke in hot summers. However, the AC can be overused or underused, while the indoor temperature is adjusted without considering the outdoor condition. If the weather is cool outside, the AC should be turned off and the windows in the room should be opened. On the contrary, if the outdoor temperature is high, the AC should be turned on. In this paper, we propose an air-conditioning guidance system (AC-Guide) to optimize the use of the AC. This system periodically, 1) samples the temperature and humidity of the room with the sensor, 2) obtains the outdoor weather data from an API, 3) calculates the discomfort index (DI) for the indoor and outdoor, 4) detects the on/off state of the AC using the image, and 5) sends a message of requesting turning on/off the AC when the DI is outside/inside the comfortable range. For evaluations, we implement the AC-Guide using Raspberry Pi, and verify the effectiveness through simulations and applications in two rooms at Okayama University.