New Perspectives in Agricultural Water Management
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water, Agriculture and Aquaculture".
Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 14074
Special Issue Editors
Interests: machine learning; data mining; computer vision
Special Issues, Collections and Topics in MDPI journals
2. Associate Professor, School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: machine learning; computational intelligence; renewable energy systems; complex systems
Special Issues, Collections and Topics in MDPI journals
Interests: drip irrigation; water-saving management; soil–salt relations; drainage; saline water utilization; crop-water plating mode; aerated irrigation; agroecosystem preservation; fertilizer measurements
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Advances in information and communication technologies have driven the evolution of traditional agricultural production into smart farming. Since irrigation and drainage scheduling significantly impacts crop production, agricultural water management is crucial in modern agriculture. Nowadays, thanks to the Internet of Things (IoT) techniques various types of connected sensors are being installed in farms. For instance, besides traditional soil moisture sensors, digital cameras now can be employed to monitor plant growth in a real-time manner. Therefore, more data and information related to every aspect of agricultural production is collected and agricultural water management is becoming complicated and complex by considering all the available information. The accumulated data from different sensors covers a wide range of data formats, such as time-series, images, videos, sound waves, etc. To achieve better decision-making in agricultural water management, intelligent information processing and data analytics approaches are highly desired and thus both structured and unstructured data can be fully utilized.
This special issue will focus on new perspectives in agricultural water management driven by the IoT and sensor techniques. The goal is that it provides an opportunity for us to gain a significantly better understanding of the current developments and the future direction of smart agricultural water management.
Potential topics include but are not limited to the following:
- IoT solutions for Agricultural Water Management
- Data-driven Soil Moisture Forecasting Approaches
- Image Processing and Computer Vision Algorithms for Plant Water Analysis
- Metaheuristic Algorithms for Irrigation and Drainage Scheduling
- Multi-Source Data Fusion Algorithms
- Machine Learning and Deep Learning Algorithms for Irrigation System Modelling
Dr. Long Wang
Dr. Chao Huang
Prof. Dr. Zhenhua Wang
Guest Editors
Manuscript Submission Information
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Keywords
- irrigation
- drainage
- machine learning
- internet of things
- sensor technologies
- data-driven
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