A Long-Range Internet of Things-Based Advanced Vehicle Pollution Monitoring System with Node Authentication and Blockchain

【Author】 Rana, Arti; Rawat, Arvind Singh; Afifi, Ashraf; Singh, Rajesh; Rashid, Mamoon; Gehlot, Anita; Akram, Shaik Vaseem; Alshamrani, Sultan S.

【Source】APPLIED SCIENCES-BASEL

【影响因子】2.838

【Abstract】According to United Nations (UN) 2030 agenda, the pollution detection system needs to be improved for the establishment of fresh air to obtain healthy life of living things. There are many reasons for the pollution and one of the reasons for pollution is from the emissions of the vehicles. Currently digital technologies such as the Internet of Things and Long-Range are showing significant impact on establishment of smart infrastructure for achieving the sustainability. Based on this motivation, this study implemented a sensor node and gateway-based Internet of Things architecture to monitor the air quality index value from any location through Long-Range communication, and Internet connectivity. To realize the proposed system, a customization of hardware is carried out and implemented the customized hardware i.e., sensor node and gateway in real-time. The sensor node is powered with node mapping to minimize the data redundancy. In this study, the evaluation metrics such as bit rate, receiver sensitivity, and time on air are evaluated by spreading factor (SF), code rate (CR), bandwidth, number of packets, payload size, preamble, and noise figure. The real-time sensor values are logged on the cloud server through sensor node and gateway. The sensor values recorded in the cloud server is compared with optimal values and concluded that the PM10, PM2.(5) are high in the air and remaining values of NO2, O-3, CO are optimal in the air. Along with this an architecture is proposed for interfacing the hardware with blockchain network through cloud server and API for node authentication.

【Keywords】cloud server; Long-Range; Internet of Things; pollutant emissions; sensors; vehicular pollution

【发表时间】2022 AUG

【收录时间】2022-08-28

【文献类型】理论模型

【主题类别】

区块链应用-实体经济-交通领域