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 |
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| © 2023 by IJETT Journal | ||
| Volume-71 Issue-10 |
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| Year of Publication : 2023 | ||
| Author : Radhika Kotecha |
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| 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.
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