Solutions and the Role of Artificial Intelligence with Its Contribution to Solving Water Problems to Achieve Sustainable Development in Iraq
Water scarcity has become of Iraq’s top and most serious challenges stemming from climate change, population increase and crumbling infrastructure. Sustainable development, in this context, can only be possible if new solutions are provided and among them recently Artificial Intelligence–AI, is one of the promising tools to deal with various water-related issues. This paper addresses the significance of artificial intelligence (AI) in solving the water challenges facing Iraq and scaling efforts towards achieving Sustainable Development Goal (SDG) number 6 on clean water and sanitation. Artificial intelligence technologies are used to store and analyze large datasets in order to optimize water resource management, improve irrigation, predict droughts, and track leaks in water distribution systems, such as machine learning, predictive analytics and remote sensing. So artificial intelligence can help the country allocate its water supply more efficiently and reduce waste, as it adapts to climate variability. Moreover, AI-based decision making can support decision makers in creating evidence-based strategies for sustainable water utilization. AI Is Poised to Change Iraq's Water Sector — But Data and Tech Infrastructures Lag Behind(https://civlified.com/ai-poised-change-iraq-water-sector-data-tech-infrastructures-lag-behind) The research reveals that despite AI technologies remain in their infancy, they can catalyze they are a catalyst for sustainable water management in Iraq and signify significant investments in information and communications technologies (ICT), capacity building and inter-sectoral collaboration are needed to realise their potential. So, by having AI in water management system, Iraq has one step closer to touch a sustainable development and have a vision of water security.
Institutions
- Northern Technical University (IQ)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-04-03
- DOI
- https://doi.org/10.5281/zenodo.15129985
- Primary Topic
- Knowledge Management and Technology
- Type
- article
- Field-Weighted Citation Impact
- 0.00