Wireless sensor network with irrigation valve control

Coates, Robert W.; Delwiche, M. J.; Broad, Alan; Holler, Mark

doi:10.1016/j.compag.2013.04.013

Cited by 86 publications

(34 citation statements)

References 6 publications

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“…Goumopoulos et al [38] also implemented a variable rate water application setup for a fixed irrigation system capable of zone-specific irrigation of strawberries. Individual nozzle control in a micro-sprinkler system has been demonstrated by Coates et al [39]. They reported individual control of 54 nodes in a vineyard with the system.…”

Section: Control Of Water Application In Precision Irrigationmentioning

confidence: 87%

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

et al. 2017

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Globally, the irrigation of crops is the largest consumptive user of fresh water. Water scarcity is increasing worldwide, resulting in tighter regulation of its use for agriculture. This necessitates the development of irrigation practices that are more efficient in the use of water but do not compromise crop quality and yield. Precision irrigation already achieves this goal, in part. The goal of precision irrigation is to accurately supply the crop water need in a timely manner and as spatially uniformly as possible. However, to maximize the benefits of precision irrigation, additional technologies need to be enabled and incorporated into agriculture. This paper discusses how incorporating adaptive decision support systems into precision irrigation management will enable significant advances in increasing the efficiency of current irrigation approaches. From the literature review, it is found that precision irrigation can be applied in achieving the environmental goals related to sustainability. The demonstrated economic benefits of precision irrigation in field-scale crop production is however minimal. It is argued that a proper combination of soil, plant and weather sensors providing real-time data to an adaptive decision support system provides an innovative platform for improving sustainability in irrigated agriculture. The review also shows that adaptive decision support systems based on model predictive control are able to adequately account for the time-varying nature of the soil-plant-atmosphere system while considering operational limitations and agronomic objectives in arriving at optimal irrigation decisions. It is concluded that significant improvements in crop yield and water savings can be achieved by incorporating model predictive control into precision irrigation decision support tools. Further improvements in water savings can also be realized by including deficit irrigation as part of the overall irrigation management strategy. Nevertheless, future research is needed for identifying crop response to regulated water deficits, developing improved soil moisture and plant sensors, and developing self-learning crop simulation frameworks that can be applied to evaluate adaptive decision support strategies related to irrigation.

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Section: Control Of Water Application In Precision Irrigationmentioning

confidence: 87%

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

et al. 2017

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“…The wireless sensor network (WSN) has been applied in many applications such as military (Atzori, Iera, & Morabito, 2010;Shelby and Bormann, 2009), healthcare (Alemdar & Ersoy, 2010;Holleman, Yeager, Prasad, Smith, & Otis, 2008), agriculture (Coates, Delwiche, Broad, & Holler, 2013;Xiaohong & Guodong, 2012), and environment (Ghini, Bettiol & Hamada, 2011;Romer & Mattern, 2004;Xufeng , Xiong, Hu, Xie, & Zhou, 2013). With the rapid growth of WSN in the recent years, Internet of Things (IoT) has attracted lot of researchers from both academic and industrial institutions (Atzori et al, 2010;Shelby & Bormann, 2009).…”

Section: Introductionmentioning

confidence: 99%

Wireless sensing modules for rural monitoring and precision agriculture applications

Lam

et al. 2017

Journal of Information and Telecommunication

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In this work, a new design of wireless sensing modules for the wireless sensor network was proposed and the specifications were tested (Received Signal Strength Indicator -RSSI, Packet Reception Ratio -PRR, Link Quality Indicator -LQI) in comparison with some commercial products. Indeed, we focus on the design of wireless sensing nodes and programming of the data transfer protocol for wireless sensing nodes (from the PHYSICAL layer to MAC layer) Experimental results show that the designed wireless sensing modules have the potential for real-world application with readrange (over 150 m), RSSI (bigger than -80 dBm), LQI (bigger than 108) and PRR (over 99%) in the range between 0 and 150 m. ARTICLE HISTORY

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“…Fortunately, rapid advances in wireless sensor networks (WSNs) technology continue to bring innovative and significant benefits to precision agriculture. 2,3 In the past decades, a great many WSNs have been developed and deployed for a variety of crop production applications, such as soil moisture sensing; 4 soil moisture, temperature, electrical conductivity (EC), and video-surveillance; 5 soil moisture and canopy temperature sensing; 6 autonomous closed-loop zone-specific irrigation and valve control; 7,8 automated irrigation schedule through combined analysis of air humidity 1 and temperature, soil moisture and temperature, irradiation, and wind speed; 9 and frost protection and dew condensation prevention. 10 Nowadays, palm plantations are widely cultivated in the arid regions of the Mediterranean, from the traditional food cultivars to the growing industry of bio--fuels.…”

Section: Introductionmentioning

confidence: 99%

Practical deployment of an in-field wireless sensor network in date palm orchard

Rao

Zhu

et al. 2017

International Journal of Distributed Sensor Networks

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Recent advances in agriculture-oriented sensors and wireless communication technologies offer great opportunities for the development and application of precision agriculture. This article describes our experience during the deployment of an experimental in-field sensor network that provided real-time monitoring in a 10-year-old date palm orchard. Taking into account the spatial variability of multiple growth-determining soil variables, the sub-regions of the sensor placement were determined by delineating the orchard into several monitoring zones. Then, the specific number of the required sensors was calculated based on the requirement of data accuracy. The sensors were distributed into the target orchard by combining the tree number with the coefficient variability of growth-determining soil variables in the monitoring zones. Finally, the networking was realized by means of synthesizing the received wireless signal strength distribution, the layout of monitoring zones, and the number of the required sensors. Some data from the deployed wireless sensor network are presented and discussed.

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Wireless sensor network with irrigation valve control

Cited by 86 publications

References 6 publications

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation

Wireless sensing modules for rural monitoring and precision agriculture applications

Practical deployment of an in-field wireless sensor network in date palm orchard

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