Survey of Energy Harvesting Technologies for Wireless Sensor Networks

Williams, Alexander; Torquato, Matheus F.; Cameron, Ian; Fahmy, Ashraf; Sienz, Johann

doi:10.1109/access.2021.3083697

Cited by 66 publications

(21 citation statements)

References 98 publications

(256 reference statements)

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“…The best way to achieve the above goals is to use wireless energy harvesting [12], [13]. By using the wireless energy harvesting technologies from ambient signals, the energy efficiency of the network will be significantly improved [14]- [16].…”

Section: A Backgroundmentioning

confidence: 99%

Multi-BD Symbiotic Radio-Aided 6G IoT Network: Energy Consumption Optimization with QoS Constraint Approach

Saadat¹

2023

Preprint

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<p>Symbiotic radio (SR) is a novel paradigm in cognitive ambient backscatter communication, which makes the connection of devices without the need to reallocation of the frequency spectrum and complex energy infrastructure and so, can turn a 6G network into a green communication. In the system model of this paper, the base stations (BSs) with the active antennas, symbiotic backscatter devices (SBDs) and symbiotic user equipment (SUE) are considered. The main purpose is to minimize the energy consumption (EC) in the SR network and increase energy efficiency (EE) by taking into account to fulfillment of the minimum required throughput for SBDs. To this end, we introduce a new scheduling system called Timing SR (T-SR) to optimal resource allocation between SBDs. In this system, SBDs harvest energy from ambient signals and then send their information without interfering with each other, even in simultaneous transmission, to SUE by using the carrier of its signal. The main optimization problem has non-convex objective functions and constraints. To solve it, we use the novel mathematical methods called conic quadratic representation (CQR) and sequential quadratic (SQ) techniques. Finally, simulation results demonstrate the superiority of the proposed method compared to other outlined schemes in reducing the EC.</p>

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Section: A Backgroundmentioning

confidence: 99%

Multi-BD Symbiotic Radio-Aided 6G IoT Network: Energy Consumption Optimization with QoS Constraint Approach

Saadat¹

2023

Preprint

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“…The proposed solutions typically augment the sensing systems by adding multiple backup sensors equipped with supplementary modules. This, however, comes at the price of an increased power consumption, which in turn calls for the necessity of proper energy harvesting technologies [97,98].…”

Section: Wsn For Land Monitoringmentioning

confidence: 99%

Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives

Fascista

2022

Sensors

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Fighting Earth’s degradation and safeguarding the environment are subjects of topical interest and sources of hot debate in today’s society. According to the United Nations, there is a compelling need to take immediate actions worldwide and to implement large-scale monitoring policies aimed at counteracting the unprecedented levels of air, land, and water pollution. This requires going beyond the legacy technologies currently employed by government authorities and adopting more advanced systems that guarantee a continuous and pervasive monitoring of the environment in all its different aspects. In this paper, we take the research on integrated and large-scale environmental monitoring a step further by providing a comprehensive review that covers transversally all the main applications of wireless sensor networks (WSNs), unmanned aerial vehicles (UAVs), and crowdsensing monitoring technologies. By outlining the available solutions and current limitations, we identify in the cooperation among terrestrial (WSN/crowdsensing) and aerial (UAVs) sensing, coupled with the adoption of advanced signal processing techniques, the major pillars at the basis of future integrated (air, land, and water) and large-scale environmental monitoring systems. This review not only consolidates the progresses achieved in the field of environmental monitoring, but also sheds new lights on potential future research directions and synergies among different research areas.

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“…William et al [19] introduced the results of a survey regarding the current state of EH (Energy Harvesting) technology for small-scale WSNs in terms of EH methods, energy storage technologies, and EH system architectures. It aims to combine methods and storage, including multi-source architecture and multi-storage, as well as to highlight several other optimization considerations.…”

Section: B Sensor Energy In Wsnmentioning

confidence: 99%

Wireless Sensor Network Based Monitoring System: Implementation, Constraints, and Solution

Miptahudin

Suryani²,

Wirawan³

2022

JOIV : Int. J. Inform. Visualization

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Wireless Sensor Network (WSN) is a collection of sensors communicating at close range by forming a wireless-based network (wireless). Since 2015 research related to the use of WSN in various health, agriculture, security industry, and other fields has continued to grow. One interesting research case is the use of WSN for the monitoring process by collecting data using sensors placed and distributed in locations based on a wireless system. Sensors with low power, multifunction, supported by a combination of wireless network, microcontroller, memory, operating system, radio communication, and energy source in the form of an integrated battery enable a monitoring process of the monitoring area to run properly. The implementation of the wireless sensor network includes five main parts, namely sender, receiver, wireless transmission media, data/information, network architecture/configuration, and network management. Network management itself includes network configuration management, network performance management, network failure management, network security management, and network financing management. The main obstacles in implementing a wireless sensor network include three things: an effective and efficient data sending/receiving process, limited and easily depleted sensor energy/power, network security, and data security that is vulnerable to eavesdropping and destruction. This paper presents a taxonomy related to the constraints in implementing Wireless Sensor Networks. This paper also presents solutions from existing studies related to the constraints of implementing the WSN. Furthermore, from the results of the taxonomy mapping of these constraints, new gaps were identified related to developing existing research to produce better solutions.

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Survey of Energy Harvesting Technologies for Wireless Sensor Networks

Cited by 66 publications

References 98 publications

Multi-BD Symbiotic Radio-Aided 6G IoT Network: Energy Consumption Optimization with QoS Constraint Approach

Multi-BD Symbiotic Radio-Aided 6G IoT Network: Energy Consumption Optimization with QoS Constraint Approach

Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives

Wireless Sensor Network Based Monitoring System: Implementation, Constraints, and Solution

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