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    1. Data och IT
    2. Systemvetenskap och AI
    3. Artificiell intelligens

    Environmental Monitoring Using Artificial Intelligence

    AvA. Suresh,T. Devi

    Inbunden, Engelska, 2025

    2 460 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Environmental Monitoring Using Artificial Intelligence is a vital resource for anyone looking to leverage cutting-edge technologies in artificial intelligence and sensor systems to effectively address environmental challenges, offering innovative solutions and insights essential for creating a sustainable future. Environmental Monitoring Using Artificial Intelligence provides a comprehensive exploration of the cutting-edge technologies transforming environmental monitoring. This book bridges the gap between artificial intelligence (AI), natural language processing (NLP), and sensor-based systems, highlighting their potential to revolutionize the way we address pressing environmental challenges. Each chapter presents innovative case studies, real-world applications, and the latest research on how these technologies are being utilized to monitor and manage ecosystems, water resources, air quality, and urban sustainability. From advanced sensor networks to machine learning models, this book covers a broad spectrum of topics, including smart water solutions, biodiversity conservation, waste management, and agricultural sustainability. It offers an interdisciplinary approach, making it an essential resource for environmental engineers, data scientists, researchers, and policymakers. Whether you’re exploring smart city innovations, renewable energy monitoring, or AI-driven solutions for environmental protection, Environmental Monitoring Using Artificial Intelligence equips readers with the knowledge and tools to leverage technology for a sustainable future.

    Produktinformation

    • Utgivningsdatum:2025-03-21
    • Mått:237 x 158 x 30 mm
    • Vikt:794 g
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:432
    • Förlag:John Wiley & Sons Inc
    • ISBN:9781394270361

    Utforska kategorier

    • Artificiell intelligens inom Data och IT

    Mer om författaren

    A. Suresh, PhD, is an associate professor in the Department of Networking and Communications in the School of Computing, at the SRM Institute of Science and Technology, Tamil Nadu, India with over decades of experience. He has been granted nine patents, published over 150 papers in technical journals and over 100 papers at international scientific conferences, as well as several books. Additionally, he has served as an editor and reviewer for various journals and a chair of several conferences and workshops. T. Devi, PhD, is a professor in the Department of Computer Science and Engineering at the Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India. She has published her research work in reputed international journals and presented papers in several national and international and conferences and has published patents in the computer science and engineering field. Her areas of specialization include cryptography, network security, cloud computing, artificial intelligence, machine learning, and blockchain. N. Deepa, PhD, is an associate professor in the Department of Computer Science and Engineering at the Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India. She has presented papers in several national and international conferences, as well as published her research work in reputed international journals and conferences and patents in the computer science and engineering field. Her areas of specialization include deep learning, machine learning, mobile computing, cryptography, network security, and blockchain. Ali Kashif Bashir, PhD, is a professor at the School of Computing and Mathematics, Manchester Metropolitan University, United Kingdom and an adjunct professor at the School of Electrical Engineering and Computer Science, National University of Science and Technology, Islamabad. Additionally, he has authored over 90 peer-reviewed articles and advised several startups in the field of STEM-based education, robotics, and smart homes. He is a senior member of the Institute of Electrical and Electronics Engineers and a Distinguished Speaker for the Association for Computing Machinery and serves as an editor and reviewer for a number of journals.

    Innehållsförteckning

    • Preface xv1 Transformative Trends in AI for Environmental Monitoring: Challenges, Applications 1Leena Sri R., Divya Vetriveeran, Rakoth Kandan Sambandam, Jenefa J. and Karthikeyan Thangavel1.1 Introduction 21.2 Literature Verticals 31.3 Key Methodologies in Literature Review 51.4 Most Common Methods in Environmental Monitoring 81.5 AI Architectures for Environmental Monitoring 81.6 Applications of AI in Environmental Monitoring 171.7 Challenges and Limitations of Using AI in Environment Modeling 201.8 Future Directions 221.9 Conclusion 24Acknowledgements 25References 252 Fundamentals of AI and NLP in Environmental Analysis 29Sreedevi Chikkudu and Suresh Annamalai2.1 Introduction 302.2 AI and NLP Techniques 332.3 AI Models and NLP System with Data Science Cycle 352.4 Environmental Analysis Using AIoT and NLP 39Bibliography 423 Smart Environmental Monitoring Systems: IoT and Sensor-Based Advancements 45D. Roja Ramani, B. Ben Sujitha and Shrikant Tangade3.1 Introduction 463.2 Essential Elements and Factors for Environmental Monitoring with IoT 493.3 Diverse Avenues and Methodologies in IoT Environmental Applications 533.4 Conclusion 58References 584 Remote Monitoring Advancements: A New Approach to Biodiversity Conservation 61D. Roja Ramani, K. Kalaiarasan and Shrikant Tangade4.1 Introduction 624.2 Indicators of Primary Biodiversity 634.3 Exploring Biodiversity Conservation Strategies 644.4 AI Enhancing Animal Observation Images 654.5 AI and ML for Preserving Flora 654.6 Deep Learning Tracks Terrestrial Mammals via Satellites 674.7 Conclusion 69References 695 Smart Water Solutions: A Case Study on Drone-Led Hydrological Investigation of Water Diversion from Lakshmiyapuram Catchment to Sivakasi Periyakulam Tank 71I. Baskar, A. Haamidh, S. Suriya and K. Parameswari5.1 Introduction 725.2 Software Used 755.3 Methodology 785.4 Conclusion and Recommendation 99Acknowledgement 100References 1006 Sustainable Waste Management as a Key Feature for Smart City: A Case Study of Vadodara, Gujarat, India 103Sahil Menghani, Hardik Giri Gosai, Parashuram Kallem, Payal Desai and Uma Hapani6.1 Introduction 1046.2 Material and Methodology 1126.3 Result and Discussion 1206.4 Limitation of Study 1276.5 Conclusion and Future Prospects 128References 1287 Sensor Technologies for Environmental Data Collection 133Adimulam Raghuvira Pratap and Suresh Annamalai7.1 Introduction 1347.2 Sensor Technologies 1347.3 Background of Sensing 1357.4 Types of Sensors 1367.5 Applications of Sensors 1457.6 Challenges of Sensors 1487.7 Environmental Sensors 1497.8 Summary and Recommendations 163Bibliography 1648 Significance and Advancement of Sensor Technologies for Environmental Analysis 167S. Thanga Revathi, Mary Subaja Christo, A. Sathya and Suresh Annamalai8.1 Introduction 1688.2 Sensing and Sensor Fundamentals 1698.3 Key Sensor Technology Components 1748.4 Regulations and Standards - Sensor Technologies 1788.5 Conclusion 179Bibliography 1799 Texture-Based Classification of Organic and Pesticidal Spinach Using Machine Learning 181P. Prittopaul, M. Usha, Mervin Retnadhas Mary, Ganesha Ram G., Ashween Raj V. S. and Godwin Wilfred Raj A.9.1 Introduction 1829.2 Related Works 1839.3 Proposed Work 1869.4 Implementation and Results 1939.5 Conclusion 197References 19810 Deep Bidirectional LSTM for Emotion Detection through Mobile Sensor Analysis 201D. Roja Ramani, Naveen Chandra Gowda, S. Sreejith and Shrikant Tangade10.1 Introduction 20210.2 Literature Survey 20610.3 Methodology 20910.4 Results and Discussion 21510.5 Conclusion 21810.6 Future Directions 219References 22011 A Comparative Analysis of AlexNet and ResNet for Pneumonia Detection 225Jenefa J., Divya Vetriveeran, Rakoth Kandan Sambandam, Vinodha D., S. Thaiyalnayaki and P. Karthikeyan11.1 Introduction 22611.2 Related Works 22711.3 AlexNet 23411.4 ResNet 23711.5 Proposed Work 24011.6 Conclusion 247Acknowledgments 247References 24712 Comparison of Borewell Rescue L-Type Different Arm with Different Materials 251K.P. Sridhar, Arun M., C. Prajitha, S. Deepa, Abubeker K.M. and Rajalakshmi Selvaraj12.1 Introduction 25212.2 Related Works 25312.3 Proposed Method 25512.4 Cylinder 25512.5 Ellipse 25912.6 I-Beam 26212.7 L-Angle 26512.8 Mathematical Analysis 26912.9 Results and Discussion 27112.10 Conclusion 275References 27613 Optimizing Almond and Walnut Farming: A U-Net-Powered Deep Learning Approach for Energy Efficiency Prediction and Damage Assessment 279D. Roja Ramani, N. Deepa, Naveen Chandra Gowda and Naandhini Sidnal13.1 Introduction 28013.2 Literature Survey 28413.3 Methodology 29013.4 Results and Discussion 29413.5 Conclusion 298References 29914 Enhancing Sustainable Management of Waste Dump Sites with Smart Drones and Geospatial Tech: Air Quality Monitoring and Analysis 303Naveen Chandra Gowda, Veena H. N., Aghila Rajagopal and Shrikant Tangade14.1 Introduction 30414.2 Review of Relevant Literature 30714.3 Methodological Framework 31014.4 Outcomes and Discourse 31614.5 Conclusion 321References 32115 Voltage Veggies: A Shocking Revolution in Agriculture 325P. Prittopaul, M. Usha, Mervin Retnadhas Mary, Rageshwaran H.R., Praveen Kumar D., Praveen Kumar S. and Mugunthan Kennedy K.15.1 Introduction 32615.2 Proposed Methodology 33015.3 Experimental Approach 34315.4 Conclusion and Future Research Directions 34815.5 Conclusion 350References 35016 Emperor Penguin Optimized Loop Selection Process for Routerless NoC Design 353N.L. Venkataraman, S. Sumithra, S. Suresh Kumarm, K. Kokulavani and Gunasekaran Thangevel16.1 Introduction 35416.2 Related Works 35516.3 Design of Routerless NoC 35616.4 Emperor Penguin Optimized (EPO) Loop Selection 35816.5 Result and Discussion 36416.6 Conclusion 371References 37217 Case Study on Flyover Construction and the Air Quality Measurement by the Emission Level of Pollutants 375K.P. Sridhar, C. Prajitha, S. Deepa, Rinesh.S, Arun.M and Srinath Doss17.1 Introduction 37617.2 Related Study 37717.3 Case Study on Flyover Construction and the Air Quality Measurement 37817.4 Conclusion 384References 385About the Editors 389Index 391