Water Quality Monitoring and Control With AI
Ashay Devidas Shende, Shrikant A. Tekade, Arpan Arunrao Deshmukh, Sandeep Tembhurkar, P. Selvakumar
Abstract
Water quality monitoring is a crucial process that involves the assessment and analysis of water characteristics to determine its suitability for various uses, from drinking and agriculture to recreation and aquatic life support. This monitoring plays a pivotal role in environmental stewardship and public health protection by identifying contaminants, tracking pollution sources, and guiding regulatory decisions. However, the practice is fraught with challenges stemming from technological limitations, resource constraints, and the dynamic nature of water systems. This article explores the significance of water quality monitoring, the challenges faced in implementing effective monitoring programs, and the advancements and strategies employed to overcome these hurdles. In agriculture, water quality directly affects crop productivity and soil health, especially in irrigation-dependent regions. Poor water quality, characterized by high salinity or heavy metal contamination, can impair soil fertility and reduce crop yields, thereby jeopardizing food security and economic stability.