Internet of Things and machine learning in agriculture technological impacts and challenges
Agriculture is one of the most fundamental human activities. As the farming capacity has expanded, the usage of resources such as land, fertilizer, and water has grown exponentially, and environmental pressures from modern farming techniques have stressed natural landscapes. Still, by some estimates...
| Other Authors: | , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin ; Boston
Walter de Gruyter GmbH,
2021.
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| Series: | De Gruyter frontiers in computational intelligence ;
v. 8. |
| Subjects: | |
| Online Access: | EBSCOhost Перейти в каталог НБ ТГУ |
Table of Contents:
- Frontmatter
- Preface
- Acknowledgments
- Contents
- List of contributors
- Part I. Machine Learning and Internet of Things in Agriculture
- 1. Smart farming : Using IoT and machine learning techniques / Parul Verma and Umesh Kumar
- 2. Food security and farming through IoT and machine learning / Ashish Tripathi, Arun Kumar Singh, Khararee Narayan Singh, Krishna Kant Singh, Pushpa Choudhary, and Prem Chand Vashist
- 3. An innovative combination for new agritechnological era / Jyoti Batra Arora
- 4. Recent advancements and challenges of artificial intelligence and IoT in agriculture / Nilesh Uke, Trupti Thite, and Supriya Saste
- 5. Technological impacts and challenges of advanced technologies in agriculture / Sivakumar Rajagopal, Sonai Rajan Thangaraj, J. Paul Mansingh, and B. Prabadevi
- Part II. Applications of Internet of Things in Agriculture
- 6. IoT-based platform for smart farming - Kaa / Aarti and Amit Kumar
- 7. Internet of things platform for smart farming / K. Krishnaveni, E. Radhamani, and K. Preethi
- 8. Internet of things platform for smart farming / Jibin Varghese, J. Jeba Praba, and John J. George
- 9. Internet of things platform for smart farming / Nikunj Rajyaguru, Shubhendu Vyas, and Kunjan Vyas
- Part III. Applications of Machine Learning in Agriculture
- 10. Kisan-e-Mitra : A tool for soil quality analyzer and recommender system / Suvarna Pawar and Pravin Futane
- 11. Artificial intelligence for plant disease detection : Past, present, and future / J. H. Kamdar, M. D. Jasani, J. D. Jasani, J. Jeba Praba, and John J. George
- 12. Wheat rust disease identification using deep learning / Sapna Nigam, Rajni Jain, Sudeep Marwaha, and Alka Arora
- 13. Image-based hibiscus plant disease detection using deep learning / Sandip Kumar Roy and Preeta Sharan
- 14. Rainfall prediction by applying machine learning technique / Mahua Bose and Kalyani Mali
- 15. Plant leaf disease classification based on feature selection and deep neural network / Tan Pham Nhat and Son Vu Truong Dao
- 16. Using deep learning for image-based plant disease detection / Shubhendu Vyas, Nikunj Rajyaguru, and Kunjan Vyas
- 17. Using deep learning for image-based plant disease detection / Yash Joshi, Sachit Mishra, and R. S. Ponmagal
- 18. Using deep learning for image-based plant disease detection / Punam Bedi, Pushkar Gole, and Sumit Kumar Agarwal
- Index.