Monitoring of Toxic Gas and Dust from Motorized Vehicles on The Highway Using Internet of Things and Blob Detection

Abstract

This study aims to determine and analyze the effect of gas and dust on the number of motorized vehicles using wireless sensor network technology and linear regression. The data used are both primary and secondary data. Primary data were obtained by the results of monitoring using sensor devices, and secondary data obtained from documentation such as video recordings of motorized vehicles on the highway. A total number of samples were 17 videos. As a result, Blob Detection can determine and calculate moving objects on the highway by making pixel comparisons between empty roads and roads containing vehicles with a success rate of 81.25%. The study simultaneously shows that the variable number of vehicles together affects the gas and dust variables positively and significantly: 85.8%, and 76.7% respectively(p=0.05) using simple linear regression.