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Smartphone Applications Targeting Precision Agriculture Practices—A Systematic Review

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INESC TEC—Institute for Systems and Computer Engineering, Technology and Science, Pólo da UTAD, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal
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UTAD—University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5000-801 Vila Real, Portugal
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INESC TEC—Institute for Systems and Computer Engineering, Technology and Science, Pólo da FEUP, Faculdade de Engenharia da Universidade do Porto, 4200-465 Porto, Portugal
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Author to whom correspondence should be addressed.
Agronomy 2020, 10(6), 855; https://doi.org/10.3390/agronomy10060855
Received: 1 May 2020 / Revised: 26 May 2020 / Accepted: 11 June 2020 / Published: 16 June 2020
(This article belongs to the Section Precision and Digital Agriculture)
Traditionally farmers have used their perceptual sensorial systems to diagnose and monitor their crops health and needs. However, humans possess five basic perceptual systems with accuracy levels that can change from human to human which are largely dependent on the stress, experience, health and age. To overcome this problem, in the last decade, with the help of the emergence of smartphone technology, new agronomic applications were developed to reach better, cost-effective, more accurate and portable diagnosis systems. Conventional smartphones are equipped with several sensors that could be useful to support near real-time usual and advanced farming activities at a very low cost. Therefore, the development of agricultural applications based on smartphone devices has increased exponentially in the last years. However, the great potential offered by smartphone applications is still yet to be fully realized. Thus, this paper presents a literature review and an analysis of the characteristics of several mobile applications for use in smart/precision agriculture available on the market or developed at research level. This will contribute to provide to farmers an overview of the applications type that exist, what features they provide and a comparison between them. Also, this paper is an important resource to help researchers and applications developers to understand the limitations of existing tools and where new contributions can be performed. View Full-Text
Keywords: precision agriculture; mobile applications; mobile computing; smartphone-based apps; machine learning; visual inspection precision agriculture; mobile applications; mobile computing; smartphone-based apps; machine learning; visual inspection
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Mendes, J.; Pinho, T.M.; Neves dos Santos, F.; Sousa, J.J.; Peres, E.; Boaventura-Cunha, J.; Cunha, M.; Morais, R. Smartphone Applications Targeting Precision Agriculture Practices—A Systematic Review. Agronomy 2020, 10, 855.

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