I. Introduction
The recent technological development due to IOT device serves the purpose to measure environmental factors with compactible device. Noise exposure level affects the psychological and physical health. The impact of noise level induces hearing loss, tinnitus, hypertension and other cardiovascular effects. A survey on industrial noise determines that about 75 percentage of workers in industrial location are more inclined to psychological disturbance. Around 30 to 60 percentage of workers severely affected and has nervous and hearing complications [1]. An assessment performed on domestic and free-living animals are open to biotic and abiotic stimulus exposed to industrial noise [2]. Exposure to excessive noise level has the effect of absorption infuriation. Communication disorder, sleeping ailment and similar complications. Latest world Health Organization report propose that there is no systematic monitoring device to measure noise pollution in a densely populated area [3]. Most trivial real-world parameters and monitored and analyzed using Internet of Thing (IOT). The manual way of analyzing the database in one location is minimized with smart devices with remote access [4]. The sensor data collected from one location can be transferred for remote analysis through different communication methods [5] & [6]. The relay activity through different ports and the activation of wifi enabled microcontroller for specific application is listed in [7] and [8]. Piyush Patil and Huang et.al developed a system specifically to monitor noise level at traffic signal [11] & [12]. A 2D convolution neural network with Tensor flow frame work is used to collect urban sound database [13]. M B Badruddin et.al. proposed a method to monitor the noise level on two different days in weekday and weekend[14]. The recent technological idea is to integrate the real time data collected from sensor nodes mapped with the cloud database to analyze the frequent variation of noise impact. The scope of paper is not limited with specific application and it broadly serves noise level monitoring at different environment. The rest of the paper is organized as follows: section 2 elaborates the existing the noise level monitoring system. Section 3 describes the proposed model and its function. In section 4 the analysis and results of noise level and section 5 concludes the proposed model.