Information and communication technologies for agriculture. Theme II, Data

Information and communication technologies for agriculture. Theme II, Data / Dionysis D. Bochtis, Dimitrios E. Moshou, Giorgos Vasileiadis, Athanasios Balafoutis, Panos M. Pardalos, editors.

This volume is the second (II) of four under the main themes of Digitizing Agriculture and Information and Communication Technologies (ICT). The four volumes cover rapidly developing processes including Sensors (I), Data (II), Decision (III), and Actions (IV). Volumes are related to 'digital tr...

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Bibliographic Details
Corporate Author: EFITA Congress
Other Authors: Bochtis, Dionysis D. (Editor), Moshou, Dimitrios (Editor), Vasileiadis, Giorgos (Editor), Balafoutis, Athanasios (Editor), Pardalos, P. M. (Panos M.), 1954- (Editor)
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, 2022.
Series:Springer optimization and its applications ; v. 183.
Subjects:
Agricultural informatics > Congresses.
Agricultural innovations > Congresses.
Internet of things > Industrial applications > Congresses.
Informática > Aplicaciones en Agricultura
Agricultural informatics
Agricultural innovations
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
Online Access:Click for online access
Table of Contents:
  • Section 1 Data Technologies: You Got Data.... Now What: Building the Right Solution for the Problem (Jackman)
  • Data fusion and its applications in Agriculture (Moshou)
  • Machine learning technology and its current implementation in agriculture (Anagnostis)
  • Section 2 Applications: Application possibilities of IoT based management systems in agriculture (Tóth)
  • Plant species detection using image processing and deep learning: A mobile-based application (Mangina)
  • Computer vision-based detection and tracking in the olive sorting pipeline (Gogos)
  • Integrating spatial with qualitative data to monitor land use intensity: evidence from arable land - animal husbandry systems (Vasilakos)
  • Air drill seeder distributor head evaluation: a comparison between laboratory tests and Computational Fluid Dynamics simulations (R. Scola)
  • Section 3 Value Chain: Data - based agricultural business continuity management policies (Podaras)
  • Soybean price trend forecast using deep learning techniques based on prices and text sentiments (F. Silva)
  • Use of unsupervised machine learning for agricultural supply chain data labeling (F. Silva).

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