Autonomous wireless sensor network based Building Energy and Environment Monitoring system design

Wang, Wensi; Wang, Ningning; Jafer, E.; Hayes, Michael; O’Flynn, Brendan; O’Mathuna, Cian

doi:10.1109/esiat.2010.5568311

Cited by 37 publications

(20 citation statements)

References 7 publications

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“…This kind of monitoring has the objective to use energy more rationally, allowing for an overall reduction of energy consumption and carbon emission, while reducing the present costs associated with this kind of monitoring. Several works have been published in this field, and among which, [79] is an example. In this work, a WSN with sixty two nodes is deployed to an office building.…”

Section: Energy and Environment Monitoring In Buildingsmentioning

confidence: 99%

Energy Harvesting Electronic Systems

Carvalho

Paulino

2015

CMOS Indoor Light Energy Harvesting System for Wireless Sensing Applications

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This chapter presents a literature review about the various ambient energy sources that can be harvested and the description of some related systems. As such, this chapter will provide a brief overview about each source and describe some systems that use that same energy source. This will be extended on to the domain of the wireless sensor networks and the aspects related to it, being presented some examples of energy harvesting powered WSN in different environments. A brief description of what is expected from each network and how it succeeds in harvesting the energy that enables it to work will receive a particular focus. Since light is the energy source being harvested, in order to power the system described in this book, some more attention will be dedicated to the analysis of this source.

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Section: Energy and Environment Monitoring In Buildingsmentioning

confidence: 99%

Energy Harvesting Electronic Systems

Carvalho

Paulino

2015

CMOS Indoor Light Energy Harvesting System for Wireless Sensing Applications

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“…These small sensors, can work collaboratively in a distributed fashion to collect information more efficiently [1], [2], [3], [4]. Some of the diverse range of applications of sensor networks include monitoring [5], [6], intrusion detection [7] and surveillance [8].…”

Section: Introductionmentioning

confidence: 99%

Maximum life span strategy for target tracking in mobile sensor networks

Mahboubi

Masoudimansour

Aghdam

et al. 2012

2012 American Control Conference (ACC)

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In this paper, an energy-efficient technique is proposed for tracking a target in a field using a network of mobile sensors while maximizing the life span of the network. The most important energy consumption sources in a mobile sensor network (MSN) are sensing, communication and movement of the sensors. In the proposed technique, first the field is divided into a grid of arbitrarily small cells. This grid is then used to obtain a graph with properly weighted edges. The weight assignment is done in such a way that it results in a close estimate of the maximum lifetime for the network. Finally, using a shortest path algorithm, an efficient route is found to transfer information from the target to destination.

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“…Therefore, it is of great significance to establishing and improving real-time monitoring systems for buildings to realize unattended and intelligent building security control [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Application of Wireless Sensor Network Technology in Security Control of Intelligent Buildings

Wang

Shao

2018

Int. J. Onl. Eng.

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Abstract-When a wireless sensor network is used to perform real-time security monitoring inside a building, there are drawbacks like multi-path signal fading and difficulty in spectrum sensing. In light of these problems, this paper proposes an improved signal spectrum sensing algorithm based on support vector machine (SVM), which inhibits the impacts brought by the low signal-noiseratio (SNR) environment in the transmission process of wireless sensor signals through the embedded cyclostationary characteristic parameters. Based on this, considering the low efficiency and poor fault tolerance of multi-task monitoring and scheduling inside the building, this paper also proposes a multi-task coordination and scheduling algorithm based on physical information integration, which achieves multi-task scheduling and execution through intelligent breakdown and prioritization of general tasks. The simulation test shows that, compared with the artificial neural network (ANN) algorithm and the maximumminimum eigenvalue (MME) algorithm, the proposed algorithm has much better spectrum sensing effect under low SNR, takes less computation time, and achieves higher accuracy in large-scale multi-task coordination and scheduling. The research conclusions can provide new ideas for the application of wireless sensor network in intelligent building security monitoring.

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Autonomous wireless sensor network based Building Energy and Environment Monitoring system design

Cited by 37 publications

References 7 publications

Energy Harvesting Electronic Systems

Energy Harvesting Electronic Systems

Maximum life span strategy for target tracking in mobile sensor networks

Application of Wireless Sensor Network Technology in Security Control of Intelligent Buildings

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