Indoor Temperature Data Collection for Machine Learning Climate Control

This dataset presents a comprehensive collection of the indoor temperature data collection procedure, meticulously designed to develop a robust dataset. The primary purpose of this dataset is to train a sophisticated machine learning algorithm capable of dynamically controlling the climate within indoor environments. The data is gathered in the A-block hostel room block on the 13th floor of VIT University Chennai, from April 15th to April 22nd, 2024. Utilizing the precise DS18B20 Temperature sensor, temperature readings are recorded at ten-minute intervals, ensuring a rich and granular dataset. To accurately reflect the room’s varying thermal conditions, the sensor’s location was alternated between two predefined points every twelve hours. This strategic approach guarantees a diverse and representative collection of temperature data, pivotal for the algorithm’s success in achieving optimal climate control.