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IoT Enabled Toxic Gas Detection and Safety Recommendation System
Environmental pollution is a major concern in developing countries. Ever since industrialisation has begun, the percentage of toxic gases in air has increased tenfolds. There is a constant need for monitoring the increase in toxic gas concentration and take certain steps to combat the threat to environment. The existing systems are restricted to hardware components which only deals with toxic gas detection and also do not have a mobile persepective. This paper proposes an architecture that includes a hardware device for detection of toxic gases as well as a software system. This paper explains the use of two data mining algorithms ,namely, Bayes Theorem and K-Nearest Neighbor for providing a safety recommendation solution to the user. Experimental results show that the proposed system is efficient and feasible in real time environment.
Keywords
IoT, Sensor Devices, On-Chip Sensors, Bayesian Process, K Nearest Neighbor, Human Interface Design.
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