Temperature, Humidity and CO2 Information Estimation of Indoor Sports Hall Environment by Using Artificial Neural Nets

In hot weather, humidity content affects adversely the human body. It causes body fatigue and slowness in metabolism by excessive sweating and increased body temperature. If the relative humidity rate is 100% , there won't be sweating and the body temperature will rise. The rise in body temperature can lead people to death. Moreover, high amounts of CO2 in the air accelerate fatigue. Reach of indoor area temperature, humidity and CO2 amounts to hazard level leads to very serious problems. In this study, totally seven features as the highest and lowest temperature of the day, the highest and lowest humidity content of the day, number of spectators, direction of wind, weather events on the day of match are obtained. During the match, a data pool is generated by taking temperature, humidity and CO2 information of the environment. Humidity and temperature values of indoor environment are taken by DHT11 temperature and humidity sensor and CO2 sensor, then they are transferred to Arduino Mega 2560. With the help of Arduino Mega 2560 card, humidity, temperature and CO2 values have been measured in real time. Using this obtained data pool and artificial neural nets, an expert system has been designed. In this expert system; these ten obtained features have been used as input data, and temperature, humidity and CO2 data have been used as output data. Through this system, temperature, humidity and CO2 information of the environment during the match to be held have been estimated at very close value. In addition, using this system, adverse conditions that may occur in indoor sports hall can be estimated and necessary measures can be taken.