relation: https://khub.utp.edu.my/scholars/17438/
title: Identifying Water Pollution Sources Using Real-Time Monitoring and IoT
creator: Rosa, S.L.
creator: Kadir, E.A.
creator: Siswanto, A.
creator: Othmand, M.
creator: Daud, H.
description: Water is a natural resource essential for basic human life; however, water pollution is deteriorating in major water sources, such as rivers, seas, and lakes. This study evaluated and identified specific pollution sources owing to numerous industrial and other potential sources of pollution along the enormous length of a Siak river. A water pollution detection system was installed and deployed at river measurement stations having the potential to pollute, particularly near industrial sites releasing chemicals and wastewater. Data obtained from the system was analyzed using an algorithm to detect and assess any abnormal behavior change in the data over time. Six detection systems were deployed around the river, primarily in residential and industrial areas. As the studied river is one of the deepest in Indonesia, this research focused only on analyzing and identifying the sources of polluted water around Pekanbaru where many people, including water supply companies, utilize the river water. Water pollution sources were identified at sensor nodes two and four, which indicated through abnormal data that various types of material were present in the river and were detected using the sensors system. Several processes are required to improve the location data accuracy, e.g., improving the algorithm using training data, performing several iterations, increasing data from the sensor, and repeating the process many times to establish the source coordinate, as shown in the results. © 2022, International Journal on Advanced Science, Engineering and Information Technology. All Rights Reserved.
publisher: Insight Society
date: 2022
type: Article
type: PeerReviewed
identifier:   Rosa, S.L. and Kadir, E.A. and Siswanto, A. and Othmand, M. and Daud, H.  (2022) Identifying Water Pollution Sources Using Real-Time Monitoring and IoT.  International Journal on Advanced Science, Engineering and Information Technology, 12 (5).  pp. 2122-2131.  ISSN 20885334     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141808378&doi=10.18517%2fijaseit.12.5.16367&partnerID=40&md5=d472aff462f8d7ffc7f56913276af6dc
relation: 10.18517/ijaseit.12.5.16367
identifier: 10.18517/ijaseit.12.5.16367