Demystifying the Role of AIoT for Sustainable WASH Conditions: Analysis and Research Directions

Demystifying the Role of AIoT for Sustainable WASH Conditions: Analysis and Research Directions
  IJETT-book-cover           
  
© 2023 by IJETT Journal
Volume-71 Issue-10
Year of Publication : 2023
Author : Radhika Kotecha
DOI : 10.14445/22315381/IJETT-V71I10P224

How to Cite?

Radhika Kotecha, "Demystifying the Role of AIoT for Sustainable WASH Conditions: Analysis and Research Directions," International Journal of Engineering Trends and Technology, vol. 71, no. 10, pp. 278-287, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I10P224

Abstract
With increasing population, expanding human activities and the effects of climate change, ensuring adequate Water, Sanitation, and Hygiene (WASH) conditions are crucial for the healthcare, development and well-being of nations and their citizens. The inclusion of WASH within the Sustainable Development Goals (SDGs) reflects the need to adopt innovative approaches for providing the necessary WASH infrastructure and services. Data Analytics on the WASH indicators help monitor the progress of WASH initiatives, infrastructure availability and conditions, service levels, WASH-related behavior changes, etc. and guide the development of early warning systems. Hence, this work applies Data Analytics on the WASH records from the WHO/UNICEF Joint Monitoring Programme (JMP) to enable efficient and effective WASH analysis and interventions. Further, the advances in Artificial Intelligence (AI) and Internet of Things (IoT) technologies and their amalgamation as Artificial Intelligence of Things (AIoT) have the potential to bring transformative changes to WASH practices. This work presents various research directions for addressing the challenges in the WASH sector by implementing AI algorithms on real-time data procured by IoT devices. These AIoT research directions contribute to developing a sustainable WASH ecosystem by enhancing efficiency, identifying indicative patterns, and enabling data-driven decision-making.

Keywords
Sustainability, Artificial Intelligence, Internet of Things, AIoT, Water, Sanitation, Hygiene.

References
[1] Guy Hutton, and Claire Chase, Water Supply, Sanitation, and Hygiene, Injury Prevention and Environmental Health, 3rd Ed., The International Bank for Reconstruction and Development/The World Bank, 2017.
[Google Scholar] [Publisher Link]
[2] Global Water, Sanitation, & Hygiene (WASH), Centers for Disease Control and Prevention. [Online]. Available: https://www.cdc.gov/healthywater/global/index.html
[3] Florence Dery et al., “Understanding Empowerment in Water, Sanitation, and Hygiene (WASH): A Scoping Review,” Journal of Water, Sanitation and Hygiene for Development, vol. 10, no. 1, pp. 5-15, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Department of Economic and Social Affairs Sustainable Development, United Nations. [Online]. Available: https://sdgs.un.org/goals
[5] Emily Ying Yang Chan et al., “Narrative Review of Primary Preventive Interventions against Water-Borne Diseases: Scientific Evidence of Health-EDRM in Contexts with Inadequate Safe Drinking Water,” International Journal of Environmental Research and Public Health, vol. 18, no. 23, pp. 1-20, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[6] P. Durgaprasad, and P. Sivaram, “Good Governance and HRD: Case Studies of User Managed Safe Drinking Water and Health Projects in India,” Asia Pacific Journal of Rural Development, vol. 17, no. 1, 2007.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Bernardo Aleixo et al., “Infrastructure is a Necessary but Insufficient Condition to Eliminate Inequalities in Access to Water: Research of a Rural Community Intervention in Northeast Brazil,” Science of the Total Environment, vol. 652, pp. 1445-1455, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Edilberto Nunes de Moura, and Mario Procopiuck, “GIS-Based Spatial Analysis: Basic Sanitation Services in Parana State, Southern Brazil,” Environmental Monitoring and Assessment, vol. 192, no. 2, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Ankita Pran Dadhich, Pran N. Dadhich, and Rohit Goyal, “Synthesis of Water, Sanitation, and Hygiene (WaSH) Spatial Pattern in Rural INDIA: An Integrated Interpretation of WaSH Practices,” Environmental Science and Pollution Research, vol. 29, no. 57, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Pedi Obani, and Joyeeta Gupta, Chapter 12 Human Security and Access to Water, Sanitation, and Hygiene: Exploring the Drivers and Nexus, Handbook on Water Security, pp. 201-214, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Demetrios E. Tsesmelis et al., “Water, Sanitation and Hygiene (WASH) Index: Development and Application to Measure WASH Service Levels in European Humanitarian Camps,” Water Resources Management, vol. 34, pp. 2449-2470, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[12] The WHO/UNICEF Joint Monitoring Programme for Water Supply, Sanitation and Hygiene (JMP) has Reported Country, Regional and Global Estimates of Progress on Drinking Water, Sanitation and Hygiene (WASH) Since 1990, WHO/UNICEF Joint Monitoring Programme. [Online]. Available: https://washdata.org/
[13] Tien-Wen Sung et al., “Artificial Intelligence of Things (AIoT) Technologies and Applications,” Wireless Communications and Mobile Computing, vol. 2021, pp. 1-2, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Biju Bajracharya, and Vamsi Gondi, “Prospects of AI Enabled IoT,” International Journal of Computer Trends and Technology, vol. 68, no. 9, pp. 11-16, 2020.
[CrossRef] [Publisher Link]
[15] Ian Goodfellow, Yoshua Bengio, and Aaron Courville, Deep Learning, MIT Press, 2016.
[Google Scholar] [Publisher Link]
[16] Elaine Rich, Kevin Knight, and Shivashankar B. Nair, Artificial Intelligence, 3rd Ed., Tata McGraw-Hill Publishing Company, pp. 1-478, 2009.
[Google Scholar] [Publisher Link]
[17] Samuel Greengard, The Internet of Things, The MIT Press, 2021.
[Google Scholar] [Publisher Link]
[18] Maciej Kranz, Building the Internet of Things, John Wiley & Sons, 2017.
[Google Scholar] [Publisher Link]
[19] Amir Hamzeh Haghiabi, Ali Heidar Nasrolahi, and Abbas Parsaie, “Water Quality Prediction Using Machine Learning Methods,” Water Quality Research Journal, vol. 53, no. 1, pp. 1-11, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Klaus Schwab, The Fourth Industrial Revolution, Crown Business, 2017.
[Google Scholar] [Publisher Link]
[21] Ashish Ghosh, Debasrita Chakraborty, and Anwesha Law, “Artificial Intelligence in Internet of Things,” CAAI Transactions on Intelligence Technology, vol. 3, no. 4, pp. 208-218, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Richa Umesh Shah et al., AIoT Technologies and Applications for Smart Environments, Institution of Engineering and Technology, 2022.
[CrossRef]  [Publisher Link]