Using Wireless Sensor Networks for Precision Irrigation Scheduling

Lea‐Cox, John D.

doi:10.5772/31236

Cited by 7 publications

(2 citation statements)

References 72 publications

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“…It can be used in both research projects and as decision support for commercial services. WSN can be used for monitoring air temperature for frost/freeze protection (Pierce and Elliott, 2008;Diedrichs et al, 2014) with specific applications in orchards (Marković et al, 2013) and vineyards (Valente et al, 2011), as well as for scheduling irrigation (Haule and Michael, 2014;Lea-Cox, 2012), managing site-specific irrigation (Kim and Evans, 2009;Matese et al, 2009), optimising plant growth (Hwang et al, 2010), and monitoring farmland (Corke et al, 2010) among others. Vineyards have characteristics that favour the use of WSN, like small fields with infrastructure (posts) to attach the sensors to (Morais et al, 2008), for different relevant purposes (Burrell et al, 2004;Togami et al, 2011;Lloret et al, 2011;Lopes et al, 2015).…”

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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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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“…Compared with wired networks, WSNs can be installed in a wide range of environments and provide benefits in terms of cost, size, power, flexibility, and distributed intelligence [1]. WSNs have been utilized in tasks such as remote monitoring, management of the agricultural environment [2], precise irrigation [3], and greenhouses [4]. Most of the research associated with WSNs focus on areas such as design of the sensors, energy cost, and applications to new scenarios.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Solutions to 3G Gateway Issues in Agriculture WSNs

Zhang

Liu

et al. 2015

International Journal of Distributed Sensor Networks

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Wireless sensor networks (WSN) are used extensively in various important areas of agriculture. Many of the associated activities involve the transmission of data or control commands through gateways that connect the servers to 3G networks. In this paper, we investigate the issues caused by Radio Resource Control (RRC) state transitions, which introduce high sudden delays in TCP packets. The packets that are subjected to these delays are then usually retransmitted because of timeouts. Further, the recently recommended TCP retransmission timer settings (RFC6298) reduce the initial retransmission timeout (RTO) from the previous three seconds to one second, further exacerbating the phenomenon of SYN packet retransmission, because a SYN packet is always the first packet to trigger the RRC state to change. We conduct a number of tests to examine the phenomenon and analyze the effect of this spurious retransmission timeout. Consequently, we propose recommendations for improvement.

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Species-specific irrigation scheduling with a spatially explicit biophysical model: A comparison to substrate moisture sensing with insight into simplified physiological parameterization

Barnard

Bauerle

2015

Agricultural and Forest Meteorology

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Using Wireless Sensor Networks for Precision Irrigation Scheduling

Cited by 7 publications

References 72 publications

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

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

Analysis and Solutions to 3G Gateway Issues in Agriculture WSNs

Species-specific irrigation scheduling with a spatially explicit biophysical model: A comparison to substrate moisture sensing with insight into simplified physiological parameterization

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