Autonomous Sensor Platform for Environmental Monitoring Applications

Lieschnegg, Michael; Fuchs, Anton; Lechner, Bernhard; Mariani, Oliver

doi:10.1007/978-3-642-27638-5_10

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…Over the last decades, we have been witnesses to the rapid development of WSNs, mainly due to their high cost-effectiveness and convenience in comparison with traditional wire-based communication technologies [6,7]. As stated in [8,9], the recent progress in wireless communication and micro/nanoelectronic technologies allows WSNs to cooperatively monitor large-scale geographical areas with high accuracy, rapidly process real-time field data, and effectively transmit the relevant information to the end-users through the base station (see Figure 2 for the general architecture of WSNs [10]) . In addition, modern sensor nodes present significantly versatile devices, thereby having the ability to sense various dynamically changing physical quantities such as seismic events, light, temperature, humidity, etc.…”

Section: Introduction 1theoretical Insight Into Wireless Sensor Networkmentioning

confidence: 99%

“…In addition, modern sensor nodes present significantly versatile devices, thereby having the ability to sense various dynamically changing physical quantities such as seismic events, light, temperature, humidity, etc. [8,11]. Moreover, the application of WSNs results in other practical benefits such as the possibility to detect tracked events online, simple and fast deployment of the monitoring infrastructure, etc.…”

Section: Introduction 1theoretical Insight Into Wireless Sensor Networkmentioning

confidence: 99%

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Distributed Mechanism for Detecting Average Consensus with Maximum-Degree Weights in Bipartite Regular Graphs

Kenyeres

2021

Mathematics

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In recent decades, distributed consensus-based algorithms for data aggregation have been gaining in importance in wireless sensor networks since their implementation as a complementary mechanism can ensure sensor-measured values with high reliability and optimized energy consumption in spite of imprecise sensor readings. In the presented article, we address the average consensus algorithm over bipartite regular graphs, where the application of the maximum-degree weights causes the divergence of the algorithm. We provide a spectral analysis of the algorithm, propose a distributed mechanism to detect whether a graph is bipartite regular, and identify how to reconfigure the algorithm so that the convergence of the average consensus algorithm is guaranteed over bipartite regular graphs. More specifically, we identify in the article that only the largest and the smallest eigenvalues of the weight matrix are located on the unit circle; the sum of all the inner states is preserved at each iteration despite the algorithm divergence; and the inner states oscillate between two values close to the arithmetic means determined by the initial inner states from each disjoint subset. The proposed mechanism utilizes the first-order forward and backward finite-difference of the inner states (more specifically, five conditions are proposed) to detect whether a graph is bipartite regular or not. Subsequently, the mixing parameter of the algorithm can be reconfigured the way it is identified in this study whereby the convergence of the algorithm is ensured in bipartite regular graphs. In the experimental part, we tested our mechanism over randomly generated bipartite regular graphs, random graphs, and random geometric graphs with various parameters, thereby identifying its very high detection rate and proving that the algorithm can estimate the arithmetic mean with high precision (like in error-free scenarios) after the suggested reconfiguration.

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Section: Introduction 1theoretical Insight Into Wireless Sensor Networkmentioning

confidence: 99%

Section: Introduction 1theoretical Insight Into Wireless Sensor Networkmentioning

confidence: 99%

Distributed Mechanism for Detecting Average Consensus with Maximum-Degree Weights in Bipartite Regular Graphs

Kenyeres

2021

Mathematics

View full text Add to dashboard Cite

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Application of Wavelet Technique in Image Fusion and its Introduction as an Early Detection Tool for Spreading of Plant Pests in Philippines’ Agricultural Sector: Initial Stage

Medalla

2018

2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environm

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Autonomous Sensor Platform for Environmental Monitoring Applications

Cited by 2 publications

References 18 publications

Distributed Mechanism for Detecting Average Consensus with Maximum-Degree Weights in Bipartite Regular Graphs

Distributed Mechanism for Detecting Average Consensus with Maximum-Degree Weights in Bipartite Regular Graphs

Application of Wavelet Technique in Image Fusion and its Introduction as an Early Detection Tool for Spreading of Plant Pests in Philippines’ Agricultural Sector: Initial Stage

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