IoT-Based Real-Time Monitoring and Testing of AI Applications for Analysis and Forecasting

Abstract

One of the most essential elements for the continuation of life on Earth is air. Air pollution is continuously rising due to industrial factors and the use of fossil fuels. Because these elements have an impact on health and prosperity of life on Earth, it is necessary to constantly examine the quality of the air in our surroundings. The implementation and strategy of IoT based air pollution tracking and projecting using AI techniques are presented in this study. Due to high levels of dangerous chemicals, air pollution in industrial settings, especially during the chrome coating process, puts workers' health at serious risk. The demand for effective testing and monitoring procedures to guarantee system reliability, safety, and efficiency has grown due to the quick development of automated production. A real-time tracking and assessment method for IoT-based autonomous systems is presented in this paper. The proposed system integrates IoT-enabled sensors, online information technology, and AI approaches to continuously collect, process, and evaluate real-time data from connected devices and automated settings. Since the system consistently detects possible issues long before they become serious mistakes, our results show a large rise in the early detection of abnormal trends. This study demonstrates how IoT and AI may be successfully integrated to enhance industrial management. It also emphasizes the concrete advantages of this integration process, such as the system's flexibility and ongoing learning, which guarantee its long-term efficacy.