Implementation of an Energy Efficient Framework for Air Quality Monitoring in the Cremation Center based on Improved chacha20 Stream Cipher for Secure Data Transmission

The Internet of Things (IoT) is recognized as a predominant era of future technology and is perceived as a network of devices that can communicate and acquire data over the internet. IoT has emerged as a prominent area of impact, potential, and innovation, attracting considerable interest from a multitude of sectors. The IoT devices are resource-constrained since they have low processing capabilities, limited power, and memory. Additionally, security is also a concern because these devices are more susceptible to attacks. In this paper, the author has proposed the Portable Air Quality and Emission Monitoring System (PAQEMS) that is used to determine the air quality and detect the emission of five harmful pollutants during the cremation process namely, particulate matter 2.5, particulate matter 10, carbon monoxide (CO), ammonia (NH3), and nitrogen dioxide (NO2). As IoT devices are power-hungry, so to minimize the power consumption, we proposed a combination of hybrid models wherein the system operates in two modes, the active mode, and hibernation mode, and an adaptive sampling approach making it an ultra-low energy-efficient system. We also implemented a security system consisting of the Message Queue Telemetry Transport (MQTT) protocol for message passing and payload encryption using the proposed new stream cipher called improved ChaCha20 which is an improved version of traditional ChaCha20. The experimental results that the average emission concentration of PM2.5, PM10, NO2, NH3, and CO, increased by 35.16 %, 16.77 %, 30.24 %, 69.83 %, and 16.47 % respectively, and that the power consumption by PAQEMS per day before applying the hybrid model is 665.64 A, while the power consumption drops to 345.6 A after applying the hybrid model. The results show that the designed system is reliable and effective for alerting people living nearby cremation centers in case of high levels of air pollution.