Iot based novel prediction control and monitoring algorithm for observing industrial safety measures

Abstract

Accidents occurring in most Indian industries are a source of worry for everyone. Sectors that consider natural assurance, world related safety, and security at the function are as vital as giving quality items. They, as a rule, need to have an overseeing chief, administrator, director, and officers in charge of these issues. They are called Environmental, Health, and Safety (EHS) divisions, as in EHS or HSE offices. Most of the top management in Indian industries fails to put in place adequate safety practices in their work environment. This work has aimed at finding evidence of the Environment, Health and Safety (EHS) methods located at different industries in Tamil Nadu State. Four hundred and fifty respondents from various categories like large scale industries, medium scale industries, and small scale industries have formed this sample size of the survey. Nowadays, the Internet of Things (IoT) has turned out to be a standout amongst the most potent communication ideal models of the 21st century. Demographic environment articles in our daily lives prove that their correspondence and skills are part of the Internet. Furthermore, it enhances people personal satisfaction. Therefore in this research work, an integrated hardware system with software programs is developed for EHS safety using Arduino. The Processing Packages are designed to communicate through the Internet of Things (IoT) based on the Accident Reduction Model (ARM) and Augmented Data Recognition (ADR) system. Both methods conclude by reducing the human death ratio, machine, and improving work environment safety in the Accidents by implementing wireless sensor networkbased parameters. Measurement of accuracy and safety can be achieved through these methods. The Accident Reduction Model (ARM) technique is applied to determine the particular metrics of three main criteria (Human Safety Control, machine Safety control and work environment safety control)and seventeen sub-criteria are also determined as a way of enriching the decision making process while in a dilemma. A survey was initiated in different industrial sectors to obtain reliable data for the research. The results show that the main criteria human safetyand#8223; has acquired a metric of 72.5%, while the other metrics of main criteria like machine safety and work environment safety falls to 8.9% and 18.4%. The parameter of the main criteria, human safety, indicates that the sub-criteria such as eye protection, manual lifting, material handling practices, firefighting drills, training, and safety officers are implemented to a greater extent in most of the surveyed industries. newline