Project information

Vehicle Detection and Counting for Determining the Relationship between Numbers of Vehicles and the CO Emission : Case Study in St.Nicolas School, Phitsanulok, Thailand

Objective of project

To develop a method for estimation of the vehicle density in a traffic area from video recorded by a drone. , To determine the relationship between densities of vehicles (in terms of cars and motorcycles) and the level of CO concentration in air at the traffic area and To create a prediction model of the level of CO concentration in air from the densities of cars and motorcycles ‌in the traffic.

Carbon monoxide (CO) from vehicle emission is one of the major air pollutants . Exposure to CO can cause serious health problems . CO can be fatal if exposed to 130 ppm CO for 8 hours or 150 ppm CO for 4 hours . Vehicle emission control has been regulated for different types of vehicles in many countries. Thailand follows the Euro standards for acceptable limit of exhaust emissions and also the test procedure , e.g., Euro IV for light-duty vehicles, motorcycles and heavy-duty vehicles. Even though the regulations have been imposed to limit the level of CO emissions from vehicles; the density of vehicles might cause the CO concentration exceed the safety limit for humans. For example, traffic congestion in some areas might generate health problems to the pedestrians and the local communities. In this project, we were interested to correlate the vehicle density and the CO concentration in a traffic area. Video footages of the traffic vehicles were recorded from an unmanned aerial vehicle (UAV), or drone, and simultaneously the CO concentrations in air at the ground area were measured using a gas sensor. The collected data of traffic video were analyzed using object detection and machine learning to count the numbers of cars and motorcycles in the traffic on each frame in order to estimate the car and the motorcycle densities in a particular time. With these densities and the measured CO concentrations, their relationship could be found using a linear regression . This model could be used to predict the CO concentration in air in order to raise the alarm if the safety level was exceeded. If the data from many sites could be collected, this model could identify the effectiveness of the vehicle emission control regulations at those sites, whether they rigorously follow the regulations. Moreover, the method could be simply applied to other pollutants from vehicle emissions.

This project categories of Software and presentation style is Oral and poster . This Project Create by Phasin Aumwong, Witchayut Gerdchai, Wiroon Somphaothong, They are students form Princess Chulabhorn Science High School Phitsanulok Organization. Teaching by Putthapond In-On,

Documents

Document	Downloaded(times)	Last update
Abstract (.docx)	2	2019-10-31 14:34:17 by Witchayut
Abstract (.pdf)	2	2019-10-31 14:34:45 by Witchayut
Full paper (.docx)	1	2019-10-31 15:04:33 by Witchayut
Full paper (.pdf)	1	2019-10-31 15:04:43 by Witchayut

Project Last Update time : 2019-11-08 14:16:59 IP Address : 61.19.23.150 Data recorder : Witchayut

Project information

Vehicle Detection and Counting for Determining the Relationship between Numbers of Vehicles and the CO Emission : Case Study in St.Nicolas School, Phitsanulok, Thailand

Objective of project

This project categories of Software and presentation style is Oral and poster . This Project Create by Phasin Aumwong, Witchayut Gerdchai, Wiroon Somphaothong, They are students form Princess Chulabhorn Science High School Phitsanulok Organization. Teaching by Putthapond In-On,

Documents

TJ-SIF 2019 SECRETARIAT

Princess Chulabhorn Science High School Mukdahan

281 Moo 6 BangSaiYai Mueng, Mukdahan 49000 Thailand