An intelligent environmental control system based on sensors network and pattern classification.
Sensor Network. Arduino Microcontroller. Intelligent environmental control. Machine learning techniques. Measures for cluster validation.
In general, laboratories or labs are workplaces that provide controlled conditions for experiments and measurements to be performed. For this reason, controlling temperature and humidity is an important requirement that needs to be achieved in order to guarantee the reproducibility of processes carried out in labs.
Aiming to propose efficient environmental controlling mechanisms, specifically for chemical analysis laboratories, we present in this work an intelligent environmental control system based on sensors network and pattern recognition. Our prototype uses its own data generated by sensors distributed in the environment to identify a pattern of behavior. Through the use of machine learning algorithms, the system identifies the classes within the data (clustering), does the training and testing procedures (classification), so that it can generalize what was learned. Finally, the rules are created in association with previously identified classes in order to control air conditioners, both the main and the spare ones, plus the dehumidifier. In this sense, the prototype keeps temperature and humidity stable and in an effective way.