Modernization and industrial development are disrupting the contamination 's equilibrium by releasing untreated harmful toxic elements into the atmosphere, resulting in contamination of basic ecosystem elements such as water, air, and soil, which are necessary for humans to survive. The four major types of contamination caused by industries are air contamination, water contamination, and noise contamination. This causes infections to spread through the air and water, affecting both humans and animals. As a result, controlling these pollutant characteristics is a major undertaking. The major goal of this project is to design an efficient and cost-effective industrial air, water, and sound contamination monitoring system, and the main objective of this paper is to provide an WoT-based industrial air, water, and sound contamination monitoring system. comprehensive mechanism to track the variables that are causing the problem of contamination. This project's/working system's technique is to read and track pollutant indicators, as well as to inform when any of these substances are released, contamination control authorities are notified. Contamination levels are above industrial requirements. The system looks into PH levels in industrial effluents, CO levels, and other factors.CO2, combustible gases, air humidity, and temperature During the manufacturing process, minute optical dust particles are released. as well as the sound level produced by the industry, employing PH sensor, MQ6, MQ9, temperature sensor, and other sensors Humidity, and noise sensors are all included. This system is based on the Internet of Things (WoT), which is a rapidly growing technology that combines electronics and computer science. The Internet of Things (WoT) concept allows us to obtain data from faraway locations and preserve it in a database without having to physically be present in that region.

These years, with computer science and machine learning changing into the hotspot of analysis, many appliances have emerged in every of those areas. It exists not solely as a form of educational frontier however conjointly one thing on the point of our life. during this trend, the mixture of medical aid and machine learning becomes additional and additional tighter. The proposal of its main plan conjointly greatly mitigated the prevailing scenario of unbalanced medical distribution and resources strain. This paper summarizes some application of machine learning and auxiliary growth treatment within the method of medical resource allocation, and puts forward some new strategies of application to appreciate it nearer to human life within the era of computer science and therefore the explores an honest scenario of mutual combination of medical business and industry, that is profit each.