(Gautam Buddha University Greater Noida, India.)
Dr. Santosh Kumar Tiwari is an Assistant Professor at the School of Law, Justice & Governance, Gautam Buddha University, Greater Noida, Delhi, India. His academic interests encompass law, governance, and interdisciplinary approaches to emerging technologies and society. He contributes to the discussion of intelligent agents for water quality monitoring and environmental protection.
Santosh Kumar Tiwari, M.Menaka. In: Agentic Artificial Intelligence: Intelligent Autonomous Systems and Real-World Applications — ISBN: 978-81-69935-67-8. Pages: 136 - 159
Cognitive agents can enhance traditional monitoring systems by perpetually assessing water-quality parameters, corroborating sensor data, amalgamating diverse environmental information, identifying irregularities, forecasting future water-quality scenarios, analysing potential contamination incidents, and producing suitable decision-making assistance. This section introduces a cohesive structure for water-quality surveillance and environmental safeguarding utilising intelligent agents. It addresses critical water-quality metrics, sensor networks, data collection, preprocessing, calibration, machine learning and deep learning forecasting, anomaly identification, pollution-source assessment, spatial water-quality mapping, early-warning systems, watershed surveillance, intelligent irrigation, aquatic ecosystem preservation, and autonomous environmental governance. Edge-cloud frameworks and multi-agent systems are analysed for extensive surveillance. The section further discusses elucidation, ambiguity, information security, data management, human supervision, and assessment techniques. Future investigative pathways concerning digital twins, self-governing aquatic robots, satellite-enhanced surveillance, federated learning, multimodal foundational models, and cooperative environmental agents are examined. The section highlights constrained independence, dependable perception, clear rationale, and human oversight as crucial tenets for the implementation of intelligent agents in environmental conservation.
