Agent Based Noise Detection Using Real Time Data Analysis Towards Green Environment

The authors propose an agent-based noise detection system based on Internet of Things (IOT) for handling abnormality in sound levels of a specified zone and further analysis of data received. Our research work is important for managing different noise levels and to control fully automated emergency response unlike existing mechanism. Increased requirement of safety and security of typical organizations triggers the idea of IOT based framework creating safer zone for highly secured data and/or substances. Agents are to be considered for producing a particular effect based on external noise values. In this article, the authors have used noise agents to identify noise levels in enclosed spaces. The safety of any zone or organization should be monitored having live noise data generated by sensors situated in specific locations of users' interests at any time instance. Generated live data is sent for further analysis for identifying noise patterns. These noise patterns determine intensity of abnormality in real environments. Their predefined set of values identifies the intensity and helps system to respond appropriately. Based on specific values of noise, distinct thresholds are decided for different enclosed zones. An alert system is based on distinct thresholds. Noise sensors have been used at sender's side and receiver's side for smooth transmission of data. New theory based on data sent, data received and dependency of noise of an agent on weightage factors has been proposed in this paper.