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Autonomous UAS-Based Agriculture Applications: General Overview and Relevant European Case Studies
SINTEF AS, Dept Math & Cybernet, N-7465 Trondheim, Norway..
PDMFC, P-1300609 Lisbon, Portugal..ORCID iD: 0000-0001-7273-8862
Hellen Drones, Athens 10680, Greece..
Qamcom, S-41285 Gothenburg, Sweden..ORCID iD: 0000-0002-6903-0756
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2022 (English)In: DRONES, ISSN 2504-446X, Vol. 6, no 5, article id 128Article in journal (Refereed) Published
Abstract [en]

Emerging precision agriculture techniques rely on the frequent collection of high-quality data which can be acquired efficiently by unmanned aerial systems (UAS). The main obstacle for wider adoption of this technology is related to UAS operational costs. The path forward requires a high degree of autonomy and integration of the UAS and other cyber physical systems on the farm into a common Farm Management System (FMS) to facilitate the use of big data and artificial intelligence (AI) techniques for decision support. Such a solution has been implemented in the EU project AFarCloud (Aggregated Farming in the Cloud). The regulation of UAS operations is another important factor that impacts the adoption rate of agricultural UAS. An analysis of the new European UAS regulations relevant for autonomous operation is included. Autonomous UAS operation through the AFarCloud FMS solution has been demonstrated at several test farms in multiple European countries. Novel applications have been developed, such as the retrieval of data from remote field sensors using UAS and in situ measurements using dedicated UAS payloads designed for physical contact with the environment. The main findings include that (1) autonomous UAS operation in the agricultural sector is feasible once the regulations allow this; (2) the UAS should be integrated with the FMS and include autonomous data processing and charging functionality to offer a practical solution; and (3) several applications beyond just asset monitoring are relevant for the UAS and will help to justify the cost of this equipment.

Place, publisher, year, edition, pages
MDPI, 2022. Vol. 6, no 5, article id 128
Keywords [en]
autonomy, unmanned aircraft system, agriculture, regulations
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-59054DOI: 10.3390/drones6050128ISI: 000802556100001Scopus ID: 2-s2.0-85130701173OAI: oai:DiVA.org:mdh-59054DiVA, id: diva2:1669805
Available from: 2022-06-15 Created: 2022-06-15 Last updated: 2022-08-29Bibliographically approved

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Curuklu, Baran

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