Abstract: The majority applications of pollution monitoring systems are in industries. The control of the parameters which causes pollution and deteriorates the industrial and natural environment pattern is a great challenge and has received interest from industries especially in Paper making industries, Water treatment industries and Sugar manufacturing industries. The main objective of our project is to design an efficient and robust system to control the parameters causing pollution and to minimize the effect of these parameters without affecting the plant or natural environment. The proposed methodology is to model a system to read and monitor pollution parameters and to inform pollution control authorities when any of these factors goes higher than industry standards. A mechanism using IoT is introduced in this proposed methodology, which will automatically monitor when there is a disturbance affecting the system. The system investigates level of pH in industry effluents, level of CO2 gas released during industry process and temperature of the machineries. The through this project we try to prove that control of pollution can be computed and the data can be transferred online. Our proposed method is more accurate to derive the desired parameter Similarly, the response to industrial impacts is also highly variable. The main reason for the assessment of the quality of the industrial environment has been, traditionally, the need to verify whether the observed industrial quality is suitable for intended uses. The use of monitoring has also evolved to determine trends in the quality of the water, air and soil environment and how they are affected by the release of contaminants, other anthropogenic activities, and/or by waste treatment operation (impact monitoring).
Keywords: Internet of Thing,
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DOI:
10.17148/IJARCCE.2021.10564
