A wireless sensor network-based monitoring system with dynamic convergecast tree algorithm for precision cultivation management in orchid greenhouses

Jiang, Joe‐Air; Wang, Chien Hao; Liao, Min Sheng; Zheng, Xiang Yao; Liu, Jen Hao; Chuang, Cheng Long; Hung, Che Lun; Chen, Chia Pang

doi:10.1007/s11119-016-9448-7

Cited by 48 publications

(23 citation statements)

References 18 publications

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“…Accordingly, ∆2 = 2π N S ·1 . The parameter ρ is chosen as ρ = ρ M AX +ρ M IN 2 , so that it obeys the bound (16). We then perform two experiments: First, we generate data from assigning source positions on the grid.…”

Section: Simulation Results In 1dmentioning

confidence: 99%

“…Then, we compare the two methods in the case that the measurements are contaminated by Gaussian noise of strength 40 B. The last experiment is also repeated for ρ = 5 ρ M AX +ρ M IN 2 , which clearly violates the bound (16).…”

Section: Simulation Results In 1dmentioning

confidence: 99%

“…From a practical point of view, we make one adjustment: Due to the increase of number of points in the grid, performing the optimization using explicit matrices and a standardized software like Figure 4: The source localization performance results in a noisy scenario with SN R = 40dB. In the above figure, ρ is chosen within the bounds described by (16), in the below figure, ρ violates (16).…”

Section: D Simulationmentioning

confidence: 99%

See 2 more Smart Citations

Compressed Sensing: From Theory to Praxis

Flinth¹,

Hashemi²,

Kutyniok³

2017

Compressive Sensing of Earth Observations

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We propose a scheme utilizing ideas from infinite dimensional compressed sensing for thermal source localization. Using the soft recovery framework of one of the authors, we provide rigorous theoretical guarantees for the recovery performance. In particular, we extend the framework in order to also include noisy measurements. Further, we conduct numerical experiments, showing that our proposed method has strong performance, in a wide range of settings. These include scenarios with few sensors, off-grid source positioning and high noise levels, both in one and two dimensions.objective function based on the Unit-Norm-Tight-Frame (UNTF) concept. Although the paper emphasizes on empirical aspects, theoretical claims are also derived.Excluding [23,22], all of the previously mentioned works do not explicitly try to utilize the useful structures which exist for diffusion sources, such as sparsity and spatiotemporal correlation among measurement governed by a PDE constraint. In particular, none of them use the powerful framework of compressed sensing [2]. Therefore, Rostami et al. [34] proposed a compressed sensing method for reconstructing the diffusion field by incorporating PDE constraints in recovery part as a side information. This effort was extended to the 2D scenario in [15] by one of the authors of this article, together with co-authors. In a similar way but by utilizing an analysis formulation for the source localization problem, [17] consider the source localization inverse problem for other types of sources or governing equations, with PDE side information in a co-sparse framework.

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Section: Simulation Results In 1dmentioning

confidence: 99%

Section: Simulation Results In 1dmentioning

confidence: 99%

Section: D Simulationmentioning

confidence: 99%

See 1 more Smart Citation

Compressed Sensing: From Theory to Praxis

Flinth¹,

Hashemi²,

Kutyniok³

2017

Compressive Sensing of Earth Observations

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“…Jagannathan and Priyatharshini [5] developed an ICT-based system to observe soil moisture content, nutrient content, and the soil pH of agricultural areas. Jiang et al [8] proposed a wireless sensor network (WSN) based algorithm with a novel dynamic converge cast tree algorithm (DCTA) in orchid greenhouses for achieving high-precision cultivation of orchids. Lin et al [7] developed an ICT-based monitoring system to access the real-time risk of soil and irrigation water contamination in a pilot…”

Section: Introductionmentioning

confidence: 99%

Blockchain: The Evolutionary Next Step for ICT E-Agriculture

et al. 2017

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Blockchain technology, while still challenged with key limitations, is a transformative Information and Communications Technology (ICT) that has changed our notion of trust. Improved efficiencies for agricultural sustainable development has been demonstrated when ICT-enabled farms have access to knowledge banks and other digital resources. UN FAO-recommended ICT e-agricultural infrastructure components are a confluence of ICT and blockchain technology requirements. When ICT e-agricultural systems with blockchain infrastructure are immutable and distributed ledger systems for record management, baseline agricultural environmental data integrity is safeguarded for those who participate in transparent data management. This paper reviewed blockchain-based concepts associated with ICT-based technology. Moreover, a model ICT e-agriculture system with a blockchain infrastructure is proposed for use at the local and regional scale. To determine context specific technical and social requirements of blockchain technology for ICT e-agriculture systems, an evaluation tool is presented. The proposed system and tool can be evaluated and applied to further developments of e-agriculture systems.

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“…To meet these requirements, different intelligent control strategies such as fuzzy logic have been discussed, and achievements have been made in the remote control of climatic variables [2][3][4]. In addition, research has been conducted using different versions of fuzzy controllers such as traditional [5], inverted [6], adaptive [7], and improved via particle swarm optimization [8].…”

Section: Introductionmentioning

confidence: 99%

Low-Cost Fuzzy Logic Control for Greenhouse Environments with Web Monitoring

Robles-Algarín¹,

Cabarcas²,

Llanos³

2017

Electronics

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Abstract:The design and implementation of a low-cost system for monitoring and remote control of a greenhouse using fuzzy logic is presented. For the control system, an Arduino Mega board was programmed with a fuzzy algorithm to monitor and perform control actions for environmental temperature, soil moisture, relative humidity, and lighting. A website was designed to visualize the main indicators of agricultural interest and to get access to tools such as forced ventilation, misting systems, and sprinkler irrigation. For connectivity to the webpage, an Arduino Ethernet Shield was used. Thus, it was possible to establish a local area network and monitor and control the greenhouse climate variables manually or automatically. The application designed allowed access to the configuration, monitoring, and control of climatic conditions in the greenhouse. The effectiveness of fuzzy logic to control nonlinear systems was therefore verified without the mathematical model of the plant. Thus, the use of resources for a gable roof greenhouse prototype was optimized.

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A wireless sensor network-based monitoring system with dynamic convergecast tree algorithm for precision cultivation management in orchid greenhouses

Cited by 48 publications

References 18 publications

Compressed Sensing: From Theory to Praxis

Compressed Sensing: From Theory to Praxis

Blockchain: The Evolutionary Next Step for ICT E-Agriculture

Low-Cost Fuzzy Logic Control for Greenhouse Environments with Web Monitoring

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