IoT Vertical and Topical Summit for Agriculture
08-09 May 2018 – Tuscany, Italy

Call for Papers

Submission of Original and Novel Technical Papers Addressing the Summit Themes

Download Call for Papers PDF

Novel and Original Papers

Novel and original papers will be selected through a peer review process (the paper will be published on IEEE Xplore and indexed on Scopus).

The topics will include, among others, the following subjects:

  • Computerized decision-support aids
  • Electronic monitoring and control
  • Sensors and sensor systems
  • Wireless sensors and actuators networks
  • Cloud, Mist, and Fog/Edge computing in agriculture
  • Machine learning in agriculture
  • Autonomous vehicles in agriculture
  • Applications of artificial intelligence
  • Machine vision
  • Robotics
  • Simulation and modeling
  • Connectivity and Communications
  • Human Machine Interfaces

Submission deadline: 30 March 2018
Notifications of acceptance: 23 April 2018

Technical Papers

The IEEE IoT Vertical and Topical Summit on Agriculture – Tuscany (Tuscany2018) solicits two types of technical paper submissions:

  • Full papers describing original research. Suggested size is four pages; papers up to six pages will be accepted. Extended versions of selected papers may be considered for publication in IEEE IoT Journal: http://iot-journal.weebly.com/
  • Extended abstracts describing emerging results of new research areas or relevant topics from an industrial point of view, not to exceed two pages

Papers and abstracts will be fully peer reviewed. Papers are expected to be 4-6 pages in length and extended abstracts 2 pages long. If the submission is accepted and presented, it will be included in the conference proceedings and be submitted to the IEEE Xplore Digital Library. IEEE takes the protection of intellectual property very seriously. All submissions will be screened for plagiarism using CrossCheck. By submitting your work you agree to allow IEEE to screen your work for plagiarism: http://www.crossref.org/crosscheck/index.html