Energy analysis of industrial sensors in novel wireless SHM systems

Boyle, David; Srbinovski, Bruno; Popovici, Emanuel; O’Flynn, Brendan

doi:10.1109/icsens.2012.6411286

Cited by 11 publications

(12 citation statements)

References 2 publications

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“…For instance, in cases of structural health monitoring (SHM) of civil infrastructures, the latest generation of sensors used by geomonitoring experts are extremely expensive with respect to energy requirements. In some applications, the energy cost of sensor sampling ranges from approximately double, up to few orders of magnitude more, than the energy required to wirelessly transmit data [ 7 ]. This is due to the fact that some of the sensors (e.g., gas and pressure sensors) have an associated warm up period, or that measurement of the phenomenon requires sampling in the range of seconds.…”

Section: Introductionmentioning

confidence: 99%

An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

Srbinovski

Magno

Murphy

et al. 2016

Sensors

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Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN) are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind). Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA) in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources) and power hungry sensors (ultrasonic wind sensor and gas sensors). The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA.

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Section: Introductionmentioning

confidence: 99%

An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

Srbinovski

Magno

Murphy

et al. 2016

Sensors

Self Cite

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“…Although it is not a true approximation of the energy cost for our target system (where sampling the sensors is significantly more energy intensive that radio communication [2]), we are interested in the impact of the protocols' coexistance on the system's energy e ciency, and thus it is su cient for the purposes of this evaluation. Figure 6 shows the total time for which the radio is active for each {IP I D , IP I C } pair.…”

Section: Energy E Ciencymentioning

confidence: 99%

“…that of a cable stayed bridge 3 , during and post construction. Some interesting technical challenges were involved in the first instance, such as using heterogeneous sensors [2] to satisfy the monitoring requirements of geophysical engineering domain specialists, and incorporating hybrid energy harvesting and storage to provide e↵ective perpetual energy to the devices in the field [16]. A simple system architecture was developed, where sensor data is periodically communicated over multiple hops towards a sink node, which in turn connects to a gateway and transfers data to networked servers, thus allowing analytics to be peformed by domain experts.…”

Section: Background and Motivationmentioning

confidence: 99%

“…numerous connected (or integrated) sensors and actuators [2], which participate in the same network -Applications are likely to evolve from traditional notions of networks of devices collaboratively detecting distributed phenomena to more targeted sensing of discrete, localised phenomena that contribute to the monitoring and control of macro systems -Applications are likely to require the ability to exert fine-grained control over individual devices, which may include commands that can be generated autonomously or manually by users, i.e. human-in-the-loop…”

Section: Introductionmentioning

confidence: 99%

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Towards Precision Control in Constrained Wireless Cyber-Physical Systems

Boyle

Kolcun

Yeatman

2016

Internet of Things. IoT Infrastructures

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Abstract. This paper introduces the problem of high precision control in constrained wireless cyber-physical systems. We argue that balancing conflicting performance objectives, namely energy e ciency, high reliability and low latency, whilst concurrently enabling data collection and targeted message dissemination, are critical to the success of future applications of cyber-physical systems that leverage networks of constrained wireless devices. We describe the contemporary art in practical collection and dissemination techniques, and select the most applicable for evaluation. A comprehensive simulation study is presented, the results of which show that the current art falls significantly short of desirable performance when inter-packet intervals decrease to those required for precision control. It follows that there is a significant need for further study and new solutions to solve this emerging problem.

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“…Therefore, there are few, if any, 'one size its all' solutions. If one assumes that sensors and actuators are low cost with respect to energy in terms of sampling and information processing (which is not always true in the case of industrial applications [9]), communication is widely accepted to be the primary consumer of energy [10]. This energy consumption occurs when the radio transceiver is in an active state to send, receive and/or route packets.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Communication in Wireless Networks

Boyle¹,

Kolcun²,

Yeatman³

2017

ICT - Energy Concepts for Energy Efficiency and Sustainability

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This chapter describes the evolution of, and state of the art in, energy-eicient techniques for wirelessly communicating networks of embedded computers, such as those found in wireless sensor network (WSN), Internet of Things (IoT) and cyberphysical systems (CPS) applications. Speciically, emphasis is placed on energy eiciency as critical to ensuring the feasibility of long lifetime, low-maintenance and increasingly autonomous monitoring and control scenarios. A comprehensive summary of link layer and routing protocols for a variety of traic paterns is discussed, in addition to their combination and evaluation as full protocol stacks.

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Energy analysis of industrial sensors in novel wireless SHM systems

Cited by 11 publications

References 2 publications

An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

Towards Precision Control in Constrained Wireless Cyber-Physical Systems

Energy-Efficient Communication in Wireless Networks

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