Abstract

Air pollution is one of the pollutions that release harmful chemicals and if not controlled, it will affect the human respiratory system. Currently, there are two Air Pollution Monitoring system located in Kuantan district to record the pollution’s reading once it detects the air pollutant however, the origin of the pollution cannot be detected by the system. As a solution, a Smart Environment Monitoring System for Air Pollution Using Internet of Things (IoTs) is developed to overcome the weaknesses. This project involved both hardware and software developments, in which hardware development includes the Arduino Uno, Carbon Monoxide (MQ 7), smoke/gas (MQ 135) sensors, a buzzer and LCD display. This system is design so that the current reading can be viewed by admin in a real-time value. Besides, they can also view the data for every 8 hours. These data can be printed in PDF format. In addition, when the reading reached unhealthy value, it will warn the community via its alarm system embedded in this system. However, this system is subject to limitation especially on data delays from sensors to database. As only one existing monitoring system that located at Beserah, thus this new feature will add a sub-sensor that located at the designated area which potentially expose to the air pollution.

Details

Title
IoT-Based Smart Environment Monitoring System for Air Pollutant Detection in Kuantan, Pahang, Malaysia
Author
Nor Saradatul Akmar Zulkifli 1 ; Satrial, Mohammad Ridwan 1 ; Mohd Zamri Osman 1 ; Nor Syahidatul Nadiah Ismail 2 ; Muhammad Rusydi Muhammad Razif 3 

 Soft Computing & Intelligent System (SPINT), Faculty of Computing, Universiti Malaysia Pahang, 26300 Gambang, Kuantan, Pahang, Malaysia 
 Systems Network & Security (SYSnet), Faculty of Computing, Universiti Malaysia Pahang, 26300 Gambang, Kuantan, Pahang, Malaysia 
 Cybernatics Research Group, Faculty of Engineering Technology, Universiti Tun Hussein Onn Malaysia, Hab Pendidikan Tinggi Pagoh, KM 1, Jalan Panchor, 84600 Panchor, Johor, Malaysia 
Publication year
2020
Publication date
Feb 2020
Publisher
IOP Publishing
ISSN
17578981
e-ISSN
1757899X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2562153976
Copyright
© 2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.