ICIMLA-2020: Impacts and Challenges of IoT and Machine Learning in Agriculture |
Website | https://sites.google.com/view/springercfc/de-gryter?authuser=1&fbclid=IwAR276sEzIcvK3w54VwPClZaKfjHmXDH1n115dueJph3xzCrCqPxEu0jFO9w |
Submission link | https://easychair.org/conferences/?conf=icimla2020 |
Abstract registration deadline | March 31, 2020 |
Submission deadline | April 15, 2020 |
- Book Title: IoT and Machine Learning in Agriculture – Technological Impacts and Challenges
- Publisher: De Gruyter, China
Editors:
- Dr. Vishal Jain, BVICAM, New Delhi, India
- Prof. Jyotir Moy Chatterjee, Lord Buddha Education Foundation, Nepal
- Dr. Abhishek Kumar, Chitkara University, Himachal Pradesh, India
- Prof. Pramod Singh Rathore, Aryabhata Engineering College & Research Center, Rajasthan, India
Submission Link: https://easychair.org/conferences/?conf=icimla2020
Submission Guidelines
Agriculture is one of the most fundamental human activities. As long as we’ve pursued it, we’ve tried to master it. Better techniques meant greater yields. This, in turn, kept humans happier and healthier – and helped birth modern society as we know it. There’s only one hitch in this success story, however. As our farming capacity has expanded, usage of resources such as land, fertilizer, and water have grown exponentially. Environmental pressures from modern farming techniques have stressed our natural landscapes. Still, by some estimates, worldwide food production will need to increase 70% by 2050 to keep up with global demand. With global populations rising, it falls to technology to make farming processes more efficient and keep up with the growing demand. Fortunately, the combination of more data from the Internet of agricultural things and new machine learning capabilities can contribute a crucial part. Machine Learning (ML) and Internet of Things (IoT) can play an very promising role in the Agricultural Industry, some examples will be like, an artificial intelligence programmed drone to monitor the field, An IoT designed automated crop watering system, Sensors embedded in the field to monitor temperature and humidity, Etc. Agriculture industry is the largest in the world, but when it comes to innovation here there is lot more to explore. IoT devices can be used to analyze the status of crops. For instance, with soil sensors, farmers can detect any irregular conditions such as high acidity and efficiently tackle these issues to improve their yield. The data gathered from sensors allows to apply analytics and get the insight that aid decisions around harvesting. In this book we will try to explore the impacts of ML and IoT in Agriculture sector and we will try to point out the challenges facing by the agro industry which can be solved by both Machine Learning and Internet of Things.
Recommended Topics:
- An Efficient Machine Learning Regression Model for Rainfall Prediction
- Controlling water usage for optimal plant growth with application of Sensors
- Current and prospective methods for plant disease detection
- Determining custom fertilizer profiles based on soil chemistry using machine learning
- Determining the optimal time to plant and harvest using CNN
- Development of Precision Agriculture and Innovation of Engineering Technologies
- Heuristic Prediction of Rainfall Using Machine Learning Techniques
- Internet of things platform for smart farming
- Plant & Soil Monitoring For Precision Farming using data analytics
- Plant disease detection by imaging sensors
- Remote sensing applications for precision agriculture
- Reporting weather conditions regression and prediction techniques.
- Sensing for soil moisture and nutrients with supervised learning concept
- UAV-based crop and weed classification for smart farming
- Using deep learning for image-based plant disease detection
Researchers and practitioners are invited to submit on or before 31st March, 2020, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by 15th April, 2020 about the status of their proposals and sent chapter guidelines. Full chapters are expected to be submitted by 30th May, 2020 and all interested authors must consult the guidelines for manuscript submissions at https://www.degruyter.com/fileasset/pdfs/meHinweiseAutorenEn.pdf and https://www.degruyter.com/page/faq-authors?lang=en prior to submission. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project.
Publication
This book is scheduled to be published by De Gruyter. The independent academic publisher De Gruyter can look back at a company history of 270 years. Today, the De Gruyter group publishes over 1,300 new titles each year in the humanities, social sciences, STM and law, more than 700 subscription based or Open Access journals, and a variety of digital products. The company is headquartered in Berlin, with offices in Basel, Beijing, Boston and Munich. Under its umbrella brand De Gruyter, the company runs the imprints of De Gruyter Akademie Forschung, Birkhäuser, De Gruyter Mouton, De Gruyter Oldenbourg, and De Gruyter Saur. Details are available at: https://www.degruyter.com/
Contact
- Dr. Vishal Jain, BVICAM, New Delhi (Email: drvishaljain83@gmail.com)
- Prof. Jyotir Moy Chatterjee, Lord Buddha Education Foundation, Nepal (Email: jyotirchatterjee@gmail.com)
- Dr. Abhishek Kumar, Chitkara University, Himachal Pradesh, India (Email: abhishekkmr812@gmail.com)
- Prof. Pramod Singh Rathore, Aryabhata Engineering College & Research Center, Rajasthan, India (Email: pramodrathore88@gmail.com )