Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/514E997A-E3EF-49C9-8F0B-BFD3F19C3742 | - |
| Identifier | https://doi.org/10.1016/j.comnet.2020.107147 | - |
| Identifier | https://www.sciencedirect.com/science/article/pii/S1389128620301201 | - |
| Language | en | - |
| Extent | 14 pages | en |
| Extent | 1,58 megabytes | en |
| Title | Towards smart farming: systems, frameworks and exploitation of multiple sources | en |
| Creator | Lytos Anastasios | en |
| Creator | Lagkas, Thomas D | en |
| Creator | Sarigiannidis, Panagiotis, 1979- | en |
| Creator | Zervakis Michail | en |
| Creator | Ζερβακης Μιχαηλ | el |
| Creator | Livanos Georgios | en |
| Creator | Λιβανος Γεωργιος | el |
| Publisher | Elsevier | en |
| Content Summary | Agriculture is by its nature a complicated scientific field, related to a wide range of expertise, skills, methods and processes which can be effectively supported by computerized systems. There have been many efforts towards the establishment of an automated agriculture framework, capable to control both the incoming data and the corresponding processes. The recent advances in the Information and Communication Technologies (ICT) domain have the capability to collect, process and analyze data from different sources while materializing the concept of agriculture intelligence. The thriving environment for the implementation of different agriculture systems is justified by a series of technologies that offer the prospect of improving agricultural productivity through the intensive use of data. The concept of big data in agriculture is not exclusively related to big volume, but also on the variety and velocity of the collected data. Big data is a key concept for the future development of agriculture as it offers unprecedented capabilities and it enables various tools and services capable to change its current status. This survey paper covers the state-of-the-art agriculture systems and big data architectures both in research and commercial status in an effort to bridge the knowledge gap between agriculture systems and exploitation of big data. The first part of the paper is devoted to the exploration of the existing agriculture systems, providing the necessary background information for their evolution until they have reached the current status, able to support different platforms and handle multiple sources of information. The second part of the survey is focused on the exploitation of multiple sources of information, providing information for both the nature of the data and the combination of different sources of data in order to explore the full potential of ICT systems in agriculture. | en |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en |
| Date of Item | 2021-08-02 | - |
| Date of Publication | 2020 | - |
| Subject | Agriculture | en |
| Subject | Big data | en |
| Subject | Machine learning | en |
| Subject | Smart farming | en |
| Subject | Internet of Things | en |
| Bibliographic Citation | A. Lytos, T. Lagkas, P. Sarigiannidis, M. Zervakis, and G. Livanos, “Towards smart farming: systems, frameworks and exploitation of multiple sources,” Comput. Netw., vol. 172, May 2020. doi: 10.1016/j.comnet.2020.107147 | en |
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