1st Edition
Data-Driven Farming Harnessing the Power of AI and Machine Learning in Agriculture
Editor Biography
Contributors
Preface
Acknowledgments
1. Leveraging IoT for Precision Health Monitoring in Livestock with Artificial Intelligence
Devinder Kaur and Amandeep Kaur Virk
2. Significance of Machine Learning in Apple Disease Detection and Implications
Saimul Bashir, Syed Nisar Hussain Bukhari, Faisal Firdous, and Gursimran Jeet Kour
3. Intelligent Inputs Revolutionizing Agriculture: An Analytical Study
Nelofar Ara, Sani Mustapha Kura, VK Aswathy, and Mohammad Amin Wani
4. Case Studies on the Initiatives and Success Stories of Edge AI Systems for Agriculture
Thamizhiniyan Natarajan and Shanmugavadivu Pichai
5. Crop Recommender: Machine Learning–Based Computational Method to Recommend the Best Crop Using Soil and Environmental Features
Syed Nisar Hussain Bukhari, Jewiara Khursheed Wani, Ummer Iqbal, and Muneer Ahmad Dar
6. A Perusal of Machine-Learning Algorithms in Crop-Yield Predictions
Anshika Gupta, Mohit Soni, and Kalpana Katiyar
7. Harvesting Intelligence: AI and ML Revolutionizing Agriculture
Arya Kumari, Muhammad Najeeb Khan, and Amit Kumar Sinha
8. Using Deep Learning to Detect Apple Leaf Disease
Syed Nisar Hussain Bukhari, Rukaya Manzoor, Ummer Iqbal, and Muneer Ahmad Dar
9. Agricultural Crop-Yield Prediction: Comparative Analysis Using Machine Learning Models
Kukatlapalli Pradeep Kumar, S. Babu Kumar, Amarthya Dutta Gupta, Kevin Johnson, and Meghan Mary Michael
10. Fundamentals of AI and Machine Learning with Specific Examples of Application in Agriculture
Manoj Kumar Mahto, P. Laxmikanth, and V.S.S.P.L.N. Balaji Lanka
11. Farming Futures: Leveraging Machine Language for Potato Leaf Disease Forecasting and Yield Optimization
A. Vijayalakshmi, A. Nidin, and Deepthi Das
12. Classification of Farms for Recommendation of Rice Cultivation Using Naive Bayes and SVM: A Case Study
Qurat-ul-ain, Uzma Hameed, and Hamira Mehraj
13. Neural Networks for Crop Disease Detection
Mohammad Ubaidullah Bokhari, Gaurav Yadav, and Md. Zeyauddin
14. Short-Term Weather Forecasting for Precision Agriculture in Jammu and Kashmir: A Deep-Learning Approach
Syed Nisar Hussain Bukhari and Sana Farooq Pandit
15. Deep Reinforcement Learning for Smart Irrigation
Aakansha Khanna and Inzimam Ul Hassan
Index
Biography
Dr. Syed Nisar Hussain Bukhari is an accomplished researcher and academician, holding Bachelor’s, Master’s, and Ph.D. degrees in Computer Science. His research interests include artificial intelligence and ML, deep learning, and applying AI and ML in interdisciplinary areas like agriculture and healthcare. His other work areas are bioinformatics, immunoinformatics, and computational biology, and he has taught courses on AI and ML at undergraduate (UG) and postgraduate (PG) levels. He has proven experience in providing expert advice on the use of technology in different domains.
