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Big Data Processing Architecture for Smart Farming
Author(s) -
Amine Roukh,
Fabrice Nolack Fote,
Sidi Ahmed Mahmoudi,
Saïd Mahmoudi
Publication year - 2020
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2020.10.014
Subject(s) - computer science , big data , cloud computing , architecture , agriculture , productivity , profitability index , data science , internet of things , precision agriculture , database , computer security , data mining , business , operating system , art , ecology , macroeconomics , finance , biology , economics , visual arts
In the era of Big data, data-driven farming is changing the agricultural businesses thanks to the use of modern technologies such as the Internet of Things (IoT) sensors, drones, and farm monitoring. IoT devices produce a massive amount of precious agri-data, which are collected and analyzed in real-time using innovative application tools. This combination of technology, known as “Smart farming”, helps various stakeholders in the agri-ecosystem to monitor crops in real-time, as well as maximize productivity and profitability in farm and business operations with the minimum efforts. Although many Smart farming solutions have been introduced, both from industry and academia, universal applicability of these approaches for other farms, unfortunately, is not feasible. Most of these solutions are based on a home-made non-standard Big data processing architecture. In this paper, we propose WALLeSMART, a cloud-based Smart farming management system, applied to the Wallonia region of Belgium. The framework introduces a general architecture to address the challenges of acquisition, processing, storing, and visualization of very large amounts of data, both in batch and real-time basis. An initial prototype has been developed and tested with various farms showing prominent results.

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