Fuzzy diagnose microcontroller based system for air quality surveillance

Current work deals with the design of a microcontroller based local unit to acquire signals from a set of sensors and locally diagnose the air quality. The local unit permits the interface with standards atmospheric and meteorological sensors, as well as the communication with a central unit by message passing protocol, via GSM. A fuzzy inference system has been developed to perform the approximate reasoning process as performed by a human, based on the perception of the environment conditions. The decision algorithm is based on a performance criterion, the one that forces the emergence of the pollution level with minimum communication and maximum environment safety. The processes running at the local unit have been modularly designed within the frame of a client/server architecture to ease its gradual growing and maintenance. The local unit bi-directionally communicates with several central units that record and visualize stationary data and acts at the reception of an emergency message. The Communication is performed either following a remotely programmed pattern, event based or under the user demand.