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CLOSED Call for Papers: Special Issue on AI, Edge, and IoT for Smart Agriculture

The advent of technologies such as artificial intelligence (AI), edge, and Internet of Things (IoT) has shown a new direction of innovative research for smart agriculture. Usually, these techniques are used in agriculture to improve various farming practices such as crop growth assessment, pest control, disease monitoring, irrigation, planting, crop spraying, and field analysis. The IoT enables the farmers to obtain plenty of data relating to crop yield, soil quality, nutrition measurements, and several other valuable information through which they make better management decisions and improve overall agricultural productivity.

With the active implementation of AI-empowered tools and techniques, an augmented analysis of the real-time agricultural imagery data (aerial, terrestrial, and aquatic) can be made efficiently and turned into actionable insights to improve sustainable farming practices. Further, it works autonomously without human interventions and makes the monitoring process of large-scale agricultural land more straightforward. Also, it is undoubtful that enabling AI-empowered drones in agriculture will contribute to social good and help out the agricultural community across the globe to take the next leap in leveraging smart agricultural practice to meet the emerging food demands.

This special issue aims to explore advances in AI-empowered tools and techniques for smart agriculture. Topics of interest for the special issue include, but not, limited to the following:

  • AI-empowered internet of drones for smart agriculture: Technology, practices, and future directions
  • Edge computing foundations and applications for smart agriculture
  • Yield prediction and optimization in smart agriculture using IoT and AI techniques
  • Farm automation using edge computing
  • AI-enabled sensor based precision agriculture and smart farming
  • Crop monitoring and pest surveillance using AI and IoT techniques
  • Advances in computational intelligence techniques for AI-empowered smart agriculture
  • Innovations in cloud and edge-enabled methodologies for AI-empowered smart agriculture
  • New trends in AI-empowered internet of drones for real-time exploration of fertilizer management, pest management, plant health management, weed detection, and pest control in smart agriculture
  • AI-empowered internet of drones for livestock monitoring in smart agriculture
  • Advances in AI and IoT for protection and management of natural resources and biodiversity
  • AI-empowered edge computing for precision agriculture
  • AI for harvest/post-harvest
  • Cooperative farming solutions using AI-empowered IoT, and edge computing techniques
  • AI-empowered aerial drones and autonomous vehicles for smart farming

Timeline

Submissions due: April 27, 2021

Reviews due: June 27, 2021

Revisions due: July 27, 2021

Final reviews due: August 29, 2021

Final notifications: September 7, 2021

Publication: November/December 2021

Submission Guidelines

For manuscript submission, acceptable file formats are Microsoft Word and PDF. Manuscripts should not exceed 5,000 words including references, with each average-size figure counting as 250 words toward this limit. Please include all figures and tables, as well as a cover page with author contact information (name, postal address, phone, fax, and email address) and a 200-word abstract. Submitted manuscripts must not have been previously published or currently submitted for publication elsewhere, and all manuscripts must be cleared for publication. All previously published papers must have at least 30% new content compared to any conference (or other) publication. Accepted articles will be edited for structure, style, clarity, and readability.

Log in to ScholarOne and submit your manuscript. Please direct ScholarOne-related questions to the IEEE Micro magazine assistant at micro-ma@computer.org.

Questions?

Contact guest editors Dr. Neeraj Kumar and Dr. Sudip Misra at micro6-2-2021@computer.org, or Editor-in-Chief Lizy John at ljohn@ece.utexas.edu.

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