Water Demand Forecasting using Deep Learning in IoT Enabled Water Distribution Network

DL-Water Demand Forecasting for Water Distribution Design


Most of the water losses occur during water distribution in pipelines during transportation. In order to eradicate the losses, an “IoT based water distribution system” integrated with “Fog and Cloud Computing" proposed for water distribution and underground health monitoring of pipes. For developing an effective water distribution system based on Internet of Things (IoT), the demand of the consumer should be analysed. So, towards predicting the water demand for consumers, Deep learning methodology called Long Short-Term Memory (LSTM) is compared with traditional Time Series methodology called Auto Regressive Integrated Moving Average (ARIMA) in terms of error and accuracy. Now based on demand prediction with higher accuracy, an IoT integrated “Water Distribution Network (WDN)” is designed using hydraulic engineering. This WDN design will ensure minimal losses during transportation and quality of water to the consumers. This will lead to development of a smart system for water distribution.

Author Biographies

Lakshmi Kanthan Narayanan, Chennai Institute of Technology
Lakshmi Kanthan holds Phd degree from SRM Instiute of science and Technology (Deemed University), Chennai,India in 2020 and currently working as Asst.Professor in Department of Computer Science, Chennai Institute ofTechnology, Chennai, India. He possess Master’s degree in VLSI from Anna University, Chennai, India in 2013.He is a member of International Water Association (IWA), UK. His research interest include Internet of Things,Machine learning, Real time Systems and Software Agents
Prof.(Dr) Suresh. Sankaranarayanan holds a PhD degree (2006) in Electrical Engineering with specialization in Networking from the University of South Australia with Postdoctoral Research Experience in Next Generation Telecommunication Networks and Data Mining from the University of Technology, Sydney and University of Sydney, Australia respectively during 2006-2007.   He possesses 14 years of Academic and research Experience working in Universities in Australia, Jamaica and Brunei. Currently he is a Full Professor in Department of Information Technology, SRM Institute of Science and Technology, Kattankulathur Campus since June 2020 promoted based on academic and research excellence. Prior to that he was serving as Assoc.Professor in the Department of Information Technology, SRM Institute of Science and Technology, Kattankulathur Campus between June 2015 to June 2020.   He was also awarded Best Research & publication award for 2010, 2015, 2017 in University of West Indies, Jamaica, SRM Institute of Science and Technology respectively. He is also Senior Member of IEEE computer Society and Computer Society of India too. Also, in the current organisation he received two time for best Research award during 2016 and 2017.   He has supervised more than 30 research students leading to M.Sc, ME, M.Phil, M.S and many   Honours  Project degrees respectively in Jamaica, Brunei and now in India. Also graduated 3 phd students in the SRMIST in Internet of Things, Edge Computing and Machine learning.   He has got to his credit, as on date, more 100 fully refereed research papers published in the high impact SCIE indexed journals, Web of Science and Scopus indexed journals, Proceedings of major IEEE international conferences, Book Chapters. His current Google Scholar citation is 824 with H-index of 14 & Scopus citation of 307 with a H-index of 9              He also got 10 patents to his credit published in Indian patent office in the area of Internet of things, Edge Computing and Deep learning applied to Agriculture, energy, Water.   During 2019-2020, I have collaborated on two Research projects pertaining to IoT-Fog towards smart Energy, water with Federal University of Piauí (UFPI), Teresina - PI, Brazil & Instituto de Telecomunicações, Portugal, and University of Haute Alsace Colmar France supported and funded by FCT/MCTES and the Brazilian National Council for Research and Development (CNPq).   Also during 2019-2020, I have collaborated on Research project pertaining to Edge Computing Intelligence for Big Data with Federal University of Piauí (UFPI), Teresina - PI, Brazil & Instituto de Telecomunicações, Portugal, Oakland University, USA and ITMO University, Russia funded by FCT/MCTES,  Government of the Russian Federation; and the Brazilian National Council for Research and Development (CNPq).   During 2018-2019, I have collaborated on Research project pertaining to RPL protocol in 6lowpan network for IoT-Fog based power distribution with Federal University of Piauí (UFPI), Teresina - PI, Brazil & Instituto de Telecomunicações, Portugal funded by FCT- Fundação Para a Ciência e a Tecnologia of  Brazilian National Council for Scientific and Technological Development (CNPq)   He has also successfully completed collaborative research in health care with Oakland University, USA during 2008-2010 in University of West Indies, Jamaica. In addition, he also has completed two funded research project- One in Mobile Health care during 2009-2010 and another in Wireless Prepaid Energy Meter during 2014-2015 as Principal Investigator in Jamaica and Brunei respectively.         Now currently supervising 3 more Phd research students in the area of Internet of Things, Edge Computing, Machine learning in the current organisation.    He is also a Reviewer and Technical Committee member for a number of IEEE Conferences and Journals. He has conducted many tutorials, workshops and also given Guest Lectures in networking in various Universities and Colleges.   His current research interests are mainly towards Internet of Things, Edge/Fog Computing, Machine learning, Deep learning, Intelligent Agents, Wireless Networking.
Joel J P C Rodrigues, Federal University of Piaui (UFPI), Brazil, Instituto de Telecomunicações, Portugal & ITMO University, Russia
Joel J. P. C. Rodrigues is a professor at the Federal University of Piauí (UFPI), Brazil; and senior researcher at theInstituto de Telecomunicações, Portugal. He received the academic title of Aggregated Professor in informaticsengineering from UBI, the habilitation in computer science and engineering from the University of Haute Alsace,France, a PhD degree in informatics engineering and an MSc degree from the UBI, and a five-year BSc degree(licentiate) in informatics engineering from the University of Coimbra, Portugal. His main research interests includee-health, sensor networks and IoT, vehicular communications, and mobile and ubiquitous computing. Prof. Rodriguesis the leader of the Next Generation Networks and Applications research group (CNPq), IEEE Distinguished Lecturer[2018-2021], Director for Conference Development - IEEE ComSoc Board of Governors [2018-2019], TechnicalActivities Committee Chair of the IEEE ComSoc Latin America Region Board [2018-2019], the President of thescientific council at ParkUrbis – Covilhã Science and Technology Park, a Past-Chair of the IEEE ComSoc TechnicalCommittee on eHealth, a Past-chair of the IEEE ComSoc Technical Committee on Communications Software,Steering Committee member of the IEEE Life Sciences Technical Community and Publications co-Chair, andMember Representative of the IEEE Communications Society on the IEEE Biometrics Council. He is the editor-inchiefof the International Journal on E-Health and Medical Communications and editorial board member of severalhigh-reputed journals. He has been general chair and TPC Chair of many international conferences, includingIEEE ICC, IEEE GLOBECOM, IEEE HEALTHCOM, and IEEE LATINCOM. He is a member of many internationalTPCs and participated in several international conferences organization. He has authored or coauthored over 800papers in refereed international journals and conferences, 3 books, 2 patents, and 1 ITU-T Recommendation. Hehad been awarded several Outstanding Leadership and Outstanding Service Awards by IEEE CommunicationsSociety and several best papers awards. Prof. Rodrigues is a licensed professional engineer (as senior member),member of the Internet Society, a senior member of ACM, and an IEEE Fellow


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How to Cite
NARAYANAN, Lakshmi Kanthan et al. Water Demand Forecasting using Deep Learning in IoT Enabled Water Distribution Network. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 15, n. 6, nov. 2020. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/3977>. Date accessed: 30 nov. 2020. doi: https://doi.org/10.15837/ijccc.2020.6.3977.