Special Issue "Recent advancements in Environment Sustainability, AgriFood using applied artificial intelligence in Multimedia Systems"

Submission Deadline: 30 July 2021
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Guest Editors
Dr. Mohammad Tabrez Quasim, University of Bisha, Saudi Arabia.
Dr. Surbhi Bhatia, King Faisal University, Saudi Arabia.
Dr. Fahad Alqarni, University of Bisha, Saudi Arabia.
Dr. Kapal Dev, University of Johannesburg, South Africa.
Dr. Mohammad Alojail, King Faisal University, Saudi Arabia.

Summary

Applied Artificial Intelligence techniques have proven to be efficient and flexible at solving dynamic and complex real-world problems. The multimedia content consisting of image and video data is abundantly shared online including numerous amount of datasets. The plethora of techniques under the banner of applied artificial intelligence (AI) includes Machine Learning, Neural Networks, Deep Learning, Fuzzy Logic, Evolutionary Computation, Intelligent Agent Systems, Cellular Automata, Game Theory, and other similar systems. The use of these techniques has enabled the development of robust decision support systems across numerous fields. The combination of multimedia and applied AI in agriculture, food production, and its security, environmental sustainability will open vast areas of research for multimedia-rich applications such as video streaming, farming, organic cultivation, diseases, pests control, diagnosis, and so forth. Since the new multimedia data keeps growing exponentially, the applied AI techniques will be useful to come up with robust solutions for decision making. For example, how to collect data and related information in real-time, and how to rapidly process a large amount of multimedia data using image processing techniques, and further to apply the applied artificial intelligence techniques to achieve desirable performances in terms of both accuracy and efficiency.

Thus, for this special issue, deeply investigated works describing both theoretical and practical evaluations related to the design, analysis, and implementation of technologies for image processing in healthcare, agriculture, and environmental sustainability in multimedia systems are invited.


Keywords
Image processing and acquisition techniques
Image computing convergence
Machine learning for IoT devices in agriculture
Machine learning for IoT devices in the Food Supply chain
AI-enabled secure AgriFood
Deep Learning approach for environment sustainability
Applied AI in real-time analytics
Data analytics for multimedia big data systems in agriculture, food security
Image, audio, and video compression standards for AgriFood
AI in predictive analytics
AI for future Computing vision-based approaches
Innovations in multimedia systems for agriculture