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      Advanced UAV–WSN System for Intelligent Monitoring in Precision Agriculture †

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          Abstract

          The growing need for food worldwide requires the development of a high-performance, high-productivity, and sustainable agriculture, which implies the introduction of new technologies into monitoring activities related to control and decision-making. In this regard, this paper presents a hierarchical structure based on the collaboration between unmanned aerial vehicles (UAVs) and federated wireless sensor networks (WSNs) for crop monitoring in precision agriculture. The integration of UAVs with intelligent, ground WSNs, and IoT proved to be a robust and efficient solution for data collection, control, analysis, and decisions in such specialized applications. Key advantages lay in online data collection and relaying to a central monitoring point, while effectively managing network load and latency through optimized UAV trajectories and in situ data processing. Two important aspects of the collaboration were considered: designing the UAV trajectories for efficient data collection and implementing effective data processing algorithms (consensus and symbolic aggregate approximation) at the network level for the transmission of the relevant data. The experiments were carried out at a Romanian research institute where different crops and methods are developed. The results demonstrate that the collaborative UAV–WSN–IoT approach increases the performances in both precision agriculture and ecological agriculture.

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          Most cited references43

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          Precision Agriculture Techniques and Practices: From Considerations to Applications

          Internet of Things (IoT)-based automation of agricultural events can change the agriculture sector from being static and manual to dynamic and smart, leading to enhanced production with reduced human efforts. Precision Agriculture (PA) along with Wireless Sensor Network (WSN) are the main drivers of automation in the agriculture domain. PA uses specific sensors and software to ensure that the crops receive exactly what they need to optimize productivity and sustainability. PA includes retrieving real data about the conditions of soil, crops and weather from the sensors deployed in the fields. High-resolution images of crops are obtained from satellite or air-borne platforms (manned or unmanned), which are further processed to extract information used to provide future decisions. In this paper, a review of near and remote sensor networks in the agriculture domain is presented along with several considerations and challenges. This survey includes wireless communication technologies, sensors, and wireless nodes used to assess the environmental behaviour, the platforms used to obtain spectral images of crops, the common vegetation indices used to analyse spectral images and applications of WSN in agriculture. As a proof of concept, we present a case study showing how WSN-based PA system can be implemented. We propose an IoT-based smart solution for crop health monitoring, which is comprised of two modules. The first module is a wireless sensor network-based system to monitor real-time crop health status. The second module uses a low altitude remote sensing platform to obtain multi-spectral imagery, which is further processed to classify healthy and unhealthy crops. We also highlight the results obtained using a case study and list the challenges and future directions based on our work.
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            Energy-Efficient Data Collection in UAV Enabled Wireless Sensor Network

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              A Review on the Use of Unmanned Aerial Vehicles and Imaging Sensors for Monitoring and Assessing Plant Stresses

              Unmanned aerial vehicles (UAVs) are becoming a valuable tool to collect data in a variety of contexts. Their use in agriculture is particularly suitable, as those areas are often vast, making ground scouting difficult, and sparsely populated, which means that injury and privacy risks are not as important as in urban settings. Indeed, the use of UAVs for monitoring and assessing crops, orchards, and forests has been growing steadily during the last decade, especially for the management of stresses such as water, diseases, nutrition deficiencies, and pests. This article presents a critical overview of the main advancements on the subject, focusing on the strategies that have been used to extract the information contained in the images captured during the flights. Based on the information found in more than 100 published articles and on our own research, a discussion is provided regarding the challenges that have already been overcome and the main research gaps that still remain, together with some suggestions for future research.
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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                03 February 2020
                February 2020
                : 20
                : 3
                : 817
                Affiliations
                Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania; florin.stoican@ 123456upb.ro (F.S.); grigore.stamatescu@ 123456upb.ro (G.S.); loretta.ichim@ 123456upb.ro (L.I.); cristian.dragana@ 123456gmail.com (C.D.)
                Author notes
                [* ]Correspondence: dan.popescu@ 123456upb.ro ; Tel.: +40-766-218-363
                [†]

                This paper is a considerably extended version of our paper published in Dan, P.; Florin, S.; Loretta, I.; Grigore, S.; Cristian, D. Collaborative UAV-WSN system for data acquisition and processing in agriculture. In Proceedings of the 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS 2019), Metz, France, 18–21 September 2019.

                Author information
                https://orcid.org/0000-0002-4550-9113
                https://orcid.org/0000-0002-9647-6817
                Article
                sensors-20-00817
                10.3390/s20030817
                7038696
                32028736
                ced70c70-1318-4d25-8288-7d0cddb3ff84
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 31 December 2019
                : 31 January 2020
                Categories
                Article

                Biomedical engineering
                unmanned aerial vehicles,wireless sensor networks,intelligent data processing,trajectory planning,relevant data extraction,data consensus,internet of things,precision agriculture

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