scholarly journals Energy Harvesting Sources, Storage Devices and System Topologies for Environmental Wireless Sensor Networks: A Review

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2446 ◽  
Author(s):  
Michal Prauzek ◽  
Jaromir Konecny ◽  
Monika Borova ◽  
Karolina Janosova ◽  
Jakub Hlavica ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Storage Devices ◽  
Storage Devices ◽  
Term Operation ◽  
Harvesting Systems ◽  
Distinct Features

The operational efficiency of remote environmental wireless sensor networks (EWSNs) has improved tremendously with the advent of Internet of Things (IoT) technologies over the past few years. EWSNs require elaborate device composition and advanced control to attain long-term operation with minimal maintenance. This article is focused on power supplies that provide energy to run the wireless sensor nodes in environmental applications. In this context, EWSNs have two distinct features that set them apart from monitoring systems in other application domains. They are often deployed in remote areas, preventing the use of mains power and precluding regular visits to exchange batteries. At the same time, their surroundings usually provide opportunities to harvest ambient energy and use it to (partially) power the sensor nodes. This review provides a comprehensive account of energy harvesting sources, energy storage devices, and corresponding topologies of energy harvesting systems, focusing on studies published within the last 10 years. Current trends and future directions in these areas are also covered.

scholarly journals Increasing network lifetime using data compression in wireless sensor networks with energy harvesting

2017 ◽  
Vol 13 (1) ◽  
pp. 155014771668968 ◽  
Author(s):  
Sunyong Kim ◽  
Chiwoo Cho ◽  
Kyung-Joon Park ◽  
Hyuk Lim
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Data Compression ◽  
Network Lifetime ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Entire Network

In wireless sensor networks powered by battery-limited energy harvesting, sensor nodes that have relatively more energy can help other sensor nodes reduce their energy consumption by compressing the sensing data packets in order to consequently extend the network lifetime. In this article, we consider a data compression technique that can shorten the data packet itself to reduce the energies consumed for packet transmission and reception and to eventually increase the entire network lifetime. First, we present an energy consumption model, in which the energy consumption at each sensor node is derived. We then propose a data compression algorithm that determines the compression level at each sensor node to decrease the total energy consumption depending on the average energy level of neighboring sensor nodes while maximizing the lifetime of multihop wireless sensor networks with energy harvesting. Numerical simulations show that the proposed algorithm achieves a reduced average energy consumption while extending the entire network lifetime.

Design and Implementation of a Dual-Band Rectifier Antenna for Efficient RF Energy Harvesting in Wireless Sensor Networks

2018 ◽  
Vol 28 (02) ◽  
pp. 1950034 ◽  
Author(s):  
Asmita Rajawat ◽  
P. K. Singhal
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dual Band ◽  
Slot Antenna ◽  
Design System ◽  
Rf Energy Harvesting ◽  
Rf Energy

Wireless sensor networks (WSN) have observed an exponential amount of growth in the recent past. The energy associated with the sensor nodes is limited which is a major bottleneck for the WSN technologies. The sensor nodes in WSN need to be continuously charged and thus an efficient RF energy harvesting needs to be explored. In the proposed design, a dual-band rectifier antenna for RF energy harvesting has been developed for 900 MHz and 2.45 GHz frequencies as RF energy is mainly available in the range of 900 MHz–2.45 GHz. The antenna proposed is microstrip U slot antenna with S11 parameter below −10 dB at 2.45 GHz and 0.8 GHz with a gain of 5.1 dBi and 10.1 dBi at 900 MHz and 2.45 GHz, respectively. The circuit for the rectifier uses Schottky Diode HSMS-285C for the purpose of rectification. The rectifier circuit used is a Greinacher Voltage Multiplier. Impedance Matching of the rectifier has been processed out to improve the performance of the circuit. Simulations of rectifier have been done on Advanced Design System (ADS) Software. The conversion efficiency at 900 MHz and 2.45 GHz is found to be 78.7% and 51.768%, respectively. The proposed design can find its uses in large number of energy harvesting applications under wireless power transmission such as powering of Wireless Sensor Nodes.

scholarly journals Modified Echo State Network Enabled Dynamic Duty Cycle for Optimal Opportunistic Routing in EH-WSNs

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 98
Author(s):  
Rajkumar Singh Rathore ◽  
Suman Sangwan ◽  
Kabita Adhikari ◽  
Rupak Kharel
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Duty Cycle ◽  
Opportunistic Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Echo State Network ◽  
Proposed Model

Minimizing energy consumption is one of the major challenges in wireless sensor networks (WSNs) due to the limited size of batteries and the resource constrained tiny sensor nodes. Energy harvesting in wireless sensor networks (EH-WSNs) is one of the promising solutions to minimize the energy consumption in wireless sensor networks for prolonging the overall network lifetime. However, static energy harvesting in individual sensor nodes is normally limited and unbalanced among the network nodes. In this context, this paper proposes a modified echo state network (MESN) based dynamic duty cycle with optimal opportunistic routing (OOR) for EH-WSNs. The proposed model is used to act as a predictor for finding the expected energy consumption of the next slot in dynamic duty cycle. The model has adapted a whale optimization algorithm (WOA) for optimally selecting the weights of the neurons in the reservoir layer of the echo state network towards minimizing energy consumption at each node as well as at the network level. The adapted WOA enabled energy harvesting model provides stable output from the MESN relying on optimal weight selection in the reservoir layer. The dynamic duty cycle is updated based on energy consumption and optimal threshold energy for transmission and reception at bit level. The proposed OOR scheme uses multiple energy centric parameters for selecting the relay set oriented forwarding paths for each neighbor nodes. The performance analysis of the proposed model in realistic environments attests the benefits in terms of energy centric metrics such as energy consumption, network lifetime, delay, packet delivery ratio and throughput as compared to the state-of-the-art-techniques.

scholarly journals A Review on Conservation of Energy in Wireless Sensor Networks

2020 ◽  
Vol 1 (2) ◽  
pp. 1-16
Author(s):  
Oluwadara J. Odeyinka ◽  
Opeyemi A. Ajibola ◽  
Michael C. Ndinechi ◽  
Onyebuchi C. Nosiri ◽  
Nnaemeka Chiemezie Onuekwusi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Data Communication ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Usage ◽  
Wireless Sensor Nodes ◽  
Conservation Of Energy ◽  
Battery Energy

This paper is a review on energy conservation in wireless sensor networks (WSNs). Due to the nature of wireless sensor nodes in terms of deployment and their common usage in terrains with limited access, recharging or replacing sensor nodes batteries may be difficult. This paper examined various sources of energy in WSNs Battery, energy harvesting and energy transference. Also, various energy usage operations and energy wastage activities in WSNs were examined, and comparisons of different routing protocols based on network structure, energy dissipation, data communication cost, and entire energy usage in WSNs were itemized. The prospects of the machine learning (ML) approach in addressing energy constraint issues in WSNs were reviewed. This paper recommends a compound approach in routing decisions to maximize energy usage operation and minimize energy wastage activities, consideration for energy harvesting and transference mechanisms, and exploring the potentials in ML algorithms to resolve energy problem in wireless sensor networks.

A Routing Protocol for Solar Energy Harvesting Wireless Sensor Networks

2013 ◽  
Vol 734-737 ◽  
pp. 2903-2906
Author(s):  
He Pei Li ◽  
Ling Tao Zhang ◽  
Su Bo He
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Solar Energy ◽  
Routing Protocol ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Data Delivery ◽  
Solar Energy Harvesting

Energy and lifetime issues are crucial to the wide applications of wireless sensor networks. This paper proposes a routing protocol, SEHRP (Solar Energy Harvesting Routing Protocol), for solar energy harvesting wireless sensor networks. This protocol classifies all the sensor nodes into various regions for which each region has been assigned its transmission priority, and the data can only be delivered from lower priority regions to higher priority region. SEHRP can also detect the sensor nodes which are under the charging state, then avoid choosing those charging nodes to ensure the successful data delivery. Simulation results show that, compared to the baseline protocol, SEHRP can achieve significant performance improvements in terms of average energy consumption and average data delivery rate.

scholarly journals Event Distortion-Based Clustering Algorithm for Energy Harvesting Wireless Sensor Networks

2021 ◽  
Author(s):  
Ali Al-Qamaji ◽  
Baris Atakan
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Theoretical Framework ◽  
Base Station ◽  
Acceptable Level ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Spatially Correlated

AbstractWireless sensor networks (WSNs) consist of compact deployed sensor nodes which collectively report their sensed readings about an event to the Base Station (BS). In WSNs, due to the dense deployment, sensor readings can be spatially correlated and it is nonessential to transmit all their readings to the BS. Therefore, for more energy efficient, it is vital to choose which sensor node should report their sensed readings to the BS. In this paper, the event distortion-based clustering (EDC) algorithm is proposed for the spatially correlated sensor nodes. Here, the sensor nodes are assumed to harvest energy from ambient electromagnetic radiation source. The EDC algorithm allows the energy-harvesting sensor nodes to select and eliminate nonessential nodes while maintain an acceptable level of distortion at the BS. To measure the reliability, a theoretical framework of the distortion function is first derived for both single-hop and two-hop communication scenarios. Then, based on the derived theoretical framework, the EDC algorithm is introduced. Through extensive simulations, the performance of the EDC algorithm is evaluated in terms of achievable distortion level, number of alive nodes and harvested energy levels. As a result, EDC algorithm can successfully exploit both the spatial correlation and energy harvesting to improve the energy efficiency while preserving an acceptable level of distortion. Furthermore, the performance comparisons reveal that the two-hop communication model outperforms the single-hop model in terms of the distortion and energy-efficiency.

Traffic Models for Energy Harvesting Based Wireless Sensor Networks

2020 ◽  
Vol 13 (2) ◽  
pp. 219-226
Author(s):  
Pardeep Kaur ◽  
Preeti Singh ◽  
Balwinder S. Sohi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Mac Protocol ◽  
Traffic Analysis ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Traffic Modeling ◽  
Traffic Models ◽  
Proactive Approach

Background: Energy consumption is an important parameter in wireless sensor networks since it affects the lifetime of sensor nodes. Methods: Battery powered wireless sensor networks cannot sustain for long hence impractical for real-time applications. With energy harvesting and relevant protocols, this issue of extending the lifetime of nodes has been solved largely. The performance can be enhanced further if proper traffic analysis and modeling are done as a proactive approach. Results: A proper understanding of the traffic dynamics provides a base for further network optimization and detection of anomalies within the network. Much of the reported work in energy harvesting based WSN till now, is to design the efficient protocols only, traffic analysis and modeling is the ignored parameter. In this paper traffic models appropriate for the energy harvesting based system have been analyzed and their performance is evaluated for a MAC protocol. Conclusion: Results show that Weibull distribution is the most useful model for traffic modeling in energy harvesting based wireless sensor networks.

scholarly journals Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4113 ◽  
Author(s):  
Xiaoli Tang ◽  
Xianghong Wang ◽  
Robert Cattley ◽  
Fengshou Gu ◽  
Andrew Ball
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Harvesting ◽  
Condition Monitoring ◽  
Wireless Sensor ◽  
Energy Sources ◽  
Field Energy ◽  
Machine Condition ◽  
Machine Condition Monitoring ◽  
Harvesting Systems

Condition monitoring can reduce machine breakdown losses, increase productivity and operation safety, and therefore deliver significant benefits to many industries. The emergence of wireless sensor networks (WSNs) with smart processing ability play an ever-growing role in online condition monitoring of machines. WSNs are cost-effective networking systems for machine condition monitoring. It avoids cable usage and eases system deployment in industry, which leads to significant savings. Powering the nodes is one of the major challenges for a true WSN system, especially when positioned at inaccessible or dangerous locations and in harsh environments. Promising energy harvesting technologies have attracted the attention of engineers because they convert microwatt or milliwatt level power from the environment to implement maintenance-free machine condition monitoring systems with WSNs. The motivation of this review is to investigate the energy sources, stimulate the application of energy harvesting based WSNs, and evaluate the improvement of energy harvesting systems for mechanical condition monitoring. This paper overviews the principles of a number of energy harvesting technologies applicable to industrial machines by investigating the power consumption of WSNs and the potential energy sources in mechanical systems. Many models or prototypes with different features are reviewed, especially in the mechanical field. Energy harvesting technologies are evaluated for further development according to the comparison of their advantages and disadvantages. Finally, a discussion of the challenges and potential future research of energy harvesting systems powering WSNs for machine condition monitoring is made.

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