Artificial Intelligence-Driven Models for Environmental Management

Shrikaant Kulkarni, Ph.D., is a Research Professor at Sanjivani University, Kopargaon, India, and an Adjunct Professor at Faculty of Business, Victorian Institute of Technology, Melbourne, Australia. Dr. Kulkarni has been a senior academic and researcher for more than four decades. He has published over 100 research papers, 100+ book chapters, and edited 50+ reference books.

• List of Contributors xxiPreface xxiiiPart I Foundations of AI in Environmental Management 11 Application of AI in Environmental Sustainability 3Pawan Whig, Shashi Kant Gupta, Rahul Reddy Nadikattu, and Pavika Sharma1.1 Introduction 31.2 AI Applications in Environmental Monitoring 61.3 AI in Climate Change Mitigation 91.4 AI in Resource Management 131.5 AI in Biodiversity Conservation 171.6 AI in Sustainable Urban Planning 211.7 Ethical and Governance Considerations 251.8 Challenges and Future Prospects 331.9 Conclusion 38References 382 The Role of AI in Environmental Research and Sustainability 43Iti Batra, Seema Nath Jain, Nikhitha Yathiraju, and Kavita Mittal2.1 Introduction 432.2 AI Applications in Environmental Monitoring 462.3 AI in Natural Resource Management 502.4 AI for Biodiversity and Ecosystem Conservation 532.5 AI in Urban Sustainability 562.6 Reducing Environmental Footprints with AI 592.7 Ethical Considerations in AI-Driven Environmental Research 622.8 Case Study 652.9 Conclusion 67References 683 AI and Environmental Data Science 71Ashima Bhatnagar Bhatia, Meghna Sharma, and Bhupesh Bhatia3.1 Introduction 713.2 Fundamentals of Artificial Intelligence 743.3 Environmental Data Science 763.4 AI Applications in Environmental Science 803.5 Case Studies 833.6 Challenges and Limitations 863.7 Case Study 883.8 Future Directions 913.9 Conclusion 94References 95Part II AI in Natural Resource Management 994 Application of AI for Natural Source Management 101Pawan Whig, Rahul Reddy Nadikattu, Shashi Kant Gupta, and Shrikaant Kulkarni4.1 Introduction 1014.2 AI Technologies in NRM 1034.3 Applications of AI in Specific Natural Resource Sectors 1064.4 Case Studies 1084.5 Challenges and Limitations 1104.6 Future Directions 1124.7 Case Study: Application of AI in NRM 114References 1175 Future Prospects of AI for Management of Natural Resources 121Meghna Sharma, Ashima Bhatnagar Bhatia, and Bhupesh Bhatia5.1 Introduction 1215.2 Overview of AI Technologies 1235.3 AI in Water Management 1255.4 AI in Forestry 1275.5 AI in Agriculture 1295.6 AI in Biodiversity Conservation 1315.7 Challenges and Barriers to AI Implementation 1345.8 Case Study 1365.9 Conclusion 139References 139Part III AI Models for Climate Change Mitigation and Adaptation 1436 AI in Climate Change Prediction 145Seema Sharma, Anupriya Jain, Sachin Sharma, and Sonia Duggal6.1 Introduction 1456.2 AI Technologies in Climate Prediction 1486.3 AI Applications in Climate Science 1506.4 AI for Climate Mitigation and Adaptation 1526.5 Case Studies 1556.6 Case Study: IBM’s Green Horizon Project for Air Quality Prediction 156References 1597 AI-Driven Environmental Real-Time Monitoring, and Screening 163Kavita Mittal, Rahul Reddy Nadikattu, Pawan Whig, and Iti Batra7.1 Introduction 1637.2 Understanding AI in Environmental Monitoring 1667.3 Applications of AI in Real-Time Environmental Monitoring 1687.4 AI Techniques for Screening Environmental Data 1717.5 Case Studies of AI-Driven Environmental Monitoring 1747.6 Challenges in Implementing AI for Environmental Monitoring 1777.7 Case Study 1807.8 Implementation of the AI System 1807.9 Quantitative Analysis 1807.10 Conclusion 181References 1828 AI-Driven Environmental Problem Design for Sustainable Solutions 185Rattan Sharma, Pawan Whig, and Shashi Kant Gupta8.1 Introduction 1858.2 AI Technologies and Techniques 1888.3 AI in Real-Time Monitoring Systems 1918.4 Environmental Problem Design Using AI 1928.5 AI for Resource Management and Efficiency 1938.6 AI-Driven Solutions for Carbon Footprint Reduction 1948.7 Case Studies: AI Applications in Waste Management and Energy Conservation 1958.8 Case Study 2038.9 Conclusion 2058.10 Conclusion 207References 2089 AI in Soil Health Management for Health Food Production 211Rashmi Gera and Anupriya Jain9.1 Introduction 2119.2 Understanding Soil Health 2139.3 AI Technologies in Soil Health Management 2159.4 AI Applications in Soil Health Management 2169.5 Case Studies 2189.6 Case Study 219References 222Part IV AI in Pollution Control and Waste Management 22510 AI for Evaluation of the Impacts of Environmental Pollution on Human Health 227Anumaan Whig, Vaibhav Gupta, and Pawan Whig10.1 Introduction 22710.2 Case Studies: Respiratory and Cardiovascular Diseases Linked to Air Pollution 23310.3 Case Studies 24010.4 Case Study 243References 24911 Artificial Intelligence for Air/Water Quality Prediction 253Shashi Kant Gupta, Ashima Bhatnagar Bhatia, Vinay Aseri, and Shrikaant Kulkarni11.1 Introduction 25311.2 Monitoring Waterborne Pollutants 27411.3 Case Studies and Applications 27611.4 Challenges and Limitations 27911.5 Case Study 28211.6 Conclusion 285References 28512 AI Technology for Protection of Water Supplies from Contamination to Produce Healthy Foods 289Sonia Duggal and Anupriya Jain12.1 Introduction 28912.2 Water Contamination and its Impact on Food Production 29212.3 AI Technologies for Water Quality Monitoring 29612.4 AI-Driven Water Management in Agriculture 30112.5 Case Studies 30512.6 AI in Precision Irrigation for Water Contamination Prevention 30712.7 Challenges and Limitations 30712.8 Data Quality and Availability 30812.9 Regulatory and Ethical Considerations 31012.10 Case Study 31212.11 Future Directions in AI for Water and Food Safety 314References 31913 AI in Waste Management Technologies for Sustainable Agriculture 323Nikhitha Yathiraju, Meghna Sharma, and Sonia Duggal13.1 Introduction 32313.2 AI Applications in Agricultural Waste Management 32513.3 Challenges and Future Prospects 32613.4 Types of Agricultural Waste 32713.5 Impact of Improper Waste Management on the Environment 32813.6 AI Technologies in Waste Management 33013.7 AI Applications in Agricultural Waste Management 33213.8 Benefits of AI in Sustainable Agriculture 33513.9 Case Study: Implementation of AI in Agricultural Waste Management for Sustainable Agriculture 338References 34214 The Internet of Things (IoTs) for Environmental Pollution 345Pushan Kumar Dutta, Pawan Whig, Shashi Kant Gupta, and Vinay Aseri14.1 Introduction 34514.2 Geospatial Information Systems (GIS) in Environmental Pollution 34814.3 Remote Sensing (RS) in Pollution Monitoring 35214.4 Atmospheric Pollution Detection 35414.5 Water Pollution Detection 35414.6 Soil and Land Pollution 35414.7 Internet of Things (IoT) in Environmental Pollution Management 35714.8 Integration of GIS, RS, and IoT for Pollution Control 36114.9 Applications and Case Studies 36614.10 Advantages and Challenges 36914.11 Case Study: Smart Environmental Monitoring in Barcelona, Spain 37214.12 Policy Implications and Environmental Management 375References 378Index 383