A Rapid Review on the Use of Free and Open Source Technologies and Software Applied to Precision Agriculture Practices

Author:

dos Santos Rogério P.12ORCID,Fachada Nuno2ORCID,Beko Marko23ORCID,Leithardt Valderi R. Q.24ORCID

Affiliation:

1. Campus Capanema, Instituto Federal do Paraná—(IFPR), Rua São João, Realeza 2343, Paraná, Brazil

2. COPELABS, Lusófona University, 1749-024 Lisbon, Portugal

3. Instituto de Telecomunicações, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal

4. VALORIZA—Research Centre for Endogenous Resource Valorization, Polytechnic Institute of Portalegre, 7300-555 Portalegre, Portugal

Abstract

Technology plays a crucial role in the management of natural resources in agricultural production. Free and open-source software and sensor technology solutions have the potential to promote more sustainable agricultural production. The goal of this rapid review is to find exclusively free and open-source software for precision agriculture, available in different electronic databases, with emphasis on their characteristics and application formats, aiming at promoting sustainable agricultural production. A thorough search of the Google Scholar, GitHub, and GitLab electronic databases was performed for this purpose. Studies reporting and/or repositories containing up-to-date software were considered for this review. The various software packages were evaluated based on their characteristics and application formats. The search identified a total of 21 free and open-source software packages designed specifically for precision agriculture. Most of the identified software was shown to be extensible and customizable, while taking into account factors such as transparency, speed, and security, although some limitations were observed in terms of repository management and source control. This rapid review suggests that free and open-source software and sensor technology solutions play an important role in the management of natural resources in sustainable agricultural production, and highlights the main technological approaches towards this goal. Finally, while this review performs a preliminary assessment of existing free and open source solutions, additional research is needed to evaluate their effectiveness and usability in different scenarios, as well as their relevance in terms of environmental and economic impact on agricultural production.

Funder

Fundação para a Ciência e Tecnologia

Publisher

MDPI AG

Subject

Control and Optimization,Computer Networks and Communications,Instrumentation

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machine Learning for Automatic Weather Stations: A Case Study;Advances in Intelligent Systems and Computing;2023

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