Low-Cost IoT LoRa®Solutions for Precision Agriculture Monitoring Practices

Silva, Nuno; Mendes, Jorge; Silva, Renato; Santos, Filipe Neves dos; Mestre, Pedro; Serôdio, Carlos; Morais, Raul

doi:10.1007/978-3-030-30241-2_20

Cited by 20 publications

(18 citation statements)

References 13 publications

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“…This protocol uses Long-Range (LoRa) modulation [15] in its physical layer and features a low data rate with low complexity and long coverage. Recently, a case study has been done for PA using a LoRaWAN network for viticulture and greenhouses [16,17], and a more specific micro use case like smart irrigation [18]. It specifically highlights the importance of accurate readings from sensors in a greenhouse along with a requirement for better data visualization and analysis.…”

Section: Crop Rotation Crop-specific Design Management and Adaptationmentioning

confidence: 99%

“…LoRaWAN is an open standard which uses LoRa modulation to enable long-range and low-cost solution with optimal power consumption. There has been a growing interest of using LoRaWAN for precision agriculture, such as the design of the greenhouse irrigation system (master/slave) [35], case study on open agricultural monitoring in Kenya [36] and also precision farming in viticulture [16]. These use cases require further end-to-end scalable solutions and a remote monitoring dashboard for data visualization.…”

Section: Related Workmentioning

confidence: 99%

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Leveraging LoRaWAN Technology for Precision Agriculture in Greenhouses

Singh

Aernouts

Meyer

et al. 2020

Sensors

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The technology development in wireless sensor network (WSN) offers a sustainable solution towards precision agriculture (PA) in greenhouses. It helps to effectively use the agricultural resources and management tools and monitors different parameters to attain better quality yield and production. WSN makes use of Low-Power Wide-Area Networks (LPWANs), a wireless technology to transmit data over long distances with minimal power consumption. LoRaWAN is one of the most successful LPWAN technologies despite its low data rate and because of its low deployment and management costs. Greenhouses are susceptible to different types of interference and diversification, demanding an improved WSN design scheme. In this paper, we contemplate the viable challenges for PA in greenhouses and propose the successive steps essential for effectual WSN deployment and facilitation. We performed a real-time, end-to-end deployment of a LoRaWAN-based sensor network in a greenhouse of the ’Proefcentrum Hoogstraten’ research center in Belgium. We have designed a dashboard for better visualization and analysis of the data, analyzed the power consumption for the LoRaWAN communication, and tried three different enclosure types (commercial, simple box and airflow box, respectively). We validated the implications of real-word challenges on the end-to-end deployment and air circulation for the correct sensor readings. We found that temperature and humidity have a larger impact on the sensor readings inside the greenhouse than we initially thought, which we successfully solved through the airflow box design.

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Section: Crop Rotation Crop-specific Design Management and Adaptationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Leveraging LoRaWAN Technology for Precision Agriculture in Greenhouses

Singh

Aernouts

Meyer

et al. 2020

Sensors

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“…Precision Agriculture (PA) strategies have demonstrated that it is possible to acquire, process and analyze temporal, spatial an individual data, combining them with other information to support management decisions aimed to improve resource use efficiency, productivity, quality, profitability and sustainability of agricultural production [ 7 ]. ICTs make field level crop management more operational and easier [ 8 ], since data gathering is often carried out by using specific electronic instrumentation deployed in crops. Such devices allow ambient, plant and soil information to be sensed and properly sent to processing elements, capable of generating knowledge useful for Decision Support Systems (DSSs), in the context of crop management [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…A significant number of research works related to PA are found in the state of the art. Specifically, the systems that use Wireless Sensor Networks (WSNs) [ 8 ], have been widely tested in diverse crops, under different conditions [ 13 , 14 , 15 , 16 ]. Some of the works are focused on evaluating the network structure in terms of coverage range, throughput, latency or consumption, among other common parameters related to electronic design and communication techniques.…”

Section: Introductionmentioning

confidence: 99%

Irriman Platform: Enhancing Farming Sustainability through Cloud Computing Techniques for Irrigation Management

Forcén-Muñoz

Pavón-Pulido

López-Riquelme

et al. 2021

Sensors

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Crop sustainability is essential for balancing economic development and environmental care, mainly in strong and very competitive regions in the agri-food sector, such as the Region of Murcia in Spain, considered to be the orchard of Europe, despite being a semi-arid area with an important scarcity of fresh water. In this region, farmers apply efficient techniques to minimize supplies and maximize quality and productivity; however, the effects of climate change and the degradation of significant natural environments, such as, the “Mar Menor”, the most extent saltwater lagoon of Europe, threatened by resources overexploitation, lead to the search of even better irrigation management techniques to avoid certain effects which could damage the quaternary aquifer connected to such lagoon. This paper describes the Irriman Platform, a system based on Cloud Computing techniques, which includes low-cost wireless data loggers, capable of acquiring data from a wide range of agronomic sensors, and a novel software architecture for safely storing and processing such information, making crop monitoring and irrigation management easier. The proposed platform helps agronomists to optimize irrigation procedures through a usable web-based tool which allows them to elaborate irrigation plans and to evaluate their effectiveness over crops. The system has been deployed in a large number of representative crops, located along near 50000 ha of the surface, during several phenological cycles. Results demonstrate that the system enables crop monitoring and irrigation optimization, and makes interaction between farmers and agronomists easier.

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“…There is therefore good reason to consider the extensive implementation of LPWAN in agriculture and particularly in viticulture. Nevertheless, very few studies related to the use of LPWAN under the specific conditions of viticulture have been reported in the literature (Davcev et al, 2018;Silva et al, 2019;Spachos, 2020).…”

Section: Introductionmentioning

confidence: 99%

Empirical mapping for evaluating an LPWAN (LoRa) wireless network sensor prior to installation in a vineyard

et al. 2021

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The main aim of this study was to use Empirical mapping to test the efficiency of local low cost wireless network sensors (LPWAN - Low-Power Wide Area Network) before being applied in real wine-growing conditions. The second aim was to obtain information on the communication distances to be expected from a LPWAN, taking into account the specific needs and real conditions of a vineyard. A hand-held autonomous end-device was specifically built to simulate short messages sent by sensors via a locally designed LPWAN. This device was used to test the quality of the network from different locations within an entire vineyard and also inside the cellar. Two parameters were used to test the quality of reception of the messages: i) The Received Signal Strength Indication (RSSI), which is the received signal power measured in decibels (dB or dBm), and ii) the Signal-to-Noise Ratio (SNR), which is the ratio of the received signal power to the ambient noise power. Maps of signal reception and errors between the observed and the theoretical signal highlighted how vineyard environment (e.g., hedges, topography, and buildings) affects the signal. The results show that the maximum communication distance differed considerably from distances published in the literature. In the open field, the signal, although attenuated by the distance, was received up to 600 meters away, or even more in favourable conditions. Meanwhile, in urban areas the signal was attenuated by buildings and the electro-magnetic environment and therefore communication distances were very short (< 50 m). Empirical mapping has great potential for determining how the local environment affects signal quality and as a decision support tool for identifying the optimal location for the sensors and gateway. With a single well-positioned gateway, such low cost wireless sensor networks (LPWAN-LoRa) could be used by small to medium-sized vineyards to collect information from sensors either outside in the fields or indoors in the vineyard cellar. This paper proposes a very cheap method (< 40 €) for testing and spatialising the quality of a low cost wireless sensor network before its implementation, and it also provides information on zones with low quality reception.

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Low-Cost IoT LoRa®Solutions for Precision Agriculture Monitoring Practices

Cited by 20 publications

References 13 publications

Leveraging LoRaWAN Technology for Precision Agriculture in Greenhouses

Leveraging LoRaWAN Technology for Precision Agriculture in Greenhouses

Irriman Platform: Enhancing Farming Sustainability through Cloud Computing Techniques for Irrigation Management

Empirical mapping for evaluating an LPWAN (LoRa) wireless network sensor prior to installation in a vineyard

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