Title: Strategies based on IoT for supporting the decision-making in agriculture: a systematic literature mapping

Authors: Mario José Diván; María Laura Sánchez-Reynoso

Addresses: Economy School, National University of La Pampa, Santa Rosa, CP6300, Argentina ' Economy School, National University of La Pampa, Santa Rosa, CP6300, Argentina

Abstract: This work implements a systematic mapping study (SMS) of the literature to identify strategies and approaches oriented to support the data-driven decision-making in agriculture using internet-of-thing (IoT) devices. SMS is applied to the Scopus database, with a focus on those data coming from IoT devices, which eventually could be complemented through big data repositories. Seventy-four documents are retained based on the defined filters about the subject. A scoring model is proposed and implemented aim of establishing an order for documents, while a balance between the content precision, the number of citations, and the publishing year. The top ten documents are contrasted, while the rest of the documents are synthesised, highlighting their contributions and opportunities to improve in an ordered way based on the scoring model. The documented main subjects related to real-time decision-making based on IoT devices are represented by precision agriculture, cultivating monitoring, and irrigation management systems.

Keywords: strategies; internet of things; IoT; decision-making; agriculture; systematic literature mapping.

DOI: 10.1504/IJRIS.2021.117080

International Journal of Reasoning-based Intelligent Systems, 2021 Vol.13 No.3, pp.155 - 171

Received: 08 Nov 2019
Accepted: 03 Apr 2020
Published online: 16 Aug 2021 *

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