Open AccessAir Drone Pollution Monitoring System with Self Power Generation
Author(s) -
Shamsul Aizam Zulkifli,
Muhammad Hurriyatul Fikri Mohammad Shukor,
Fatin Najwa Razman,
Mohd Helmy Abd Wahab,
Syed Zulkarnain Syed Idrus
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1529/2/022103
Subject(s) - drone , air quality index , computer science , real time computing , environmental monitoring , wireless , internet of things , embedded system , telecommunications , environmental science , environmental engineering , genetics , physics , meteorology , biology
This project is to provide adequate environmental and health protection with an effective air quality monitoring system based on Internet of Things (IoT) medium. This system is simple, reliable, sensitive and low cost-effective. It used the MQ 135 sensor which a sensor that detects the surrounding Air Quality surrounding due to it compatibility and effectiveness which is easy to be used. The IoT Blynk application has been used in order to facilitate the user to control the air quality in continuously mode with easy interface structure. The best location to monitor the air quality is near to the source which is basically very high. Therefore, the drone has been used for this project and it also has been attached with the external source for increase the airborne time for the drone. At the same time, the monitoring system is to read the real air quality levels to determine the desire level of air quality to be monitored. At the meantime, time real monitoring data has been sent connected to the smartphone which is located at the ground which indicated wireless communication system has been created by using the Blynk application. This project has also combined with the forecasting techniques in order to ascertain future air quality expectations and thus enable users to know the air quality level at a particular place and time in the future. The system has been tested around the Faculty of Electrical and Electronic Engineering (FKEE) and it have prove that the monitoring can be done remotely and at the same time a simple prediction can be determined the air pollutant.