scholarly journals Feasibility of Harvesting Solar Energy for Self-Powered Environmental Wireless Sensor Nodes

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2058
Author(s):  
Yuyang Li ◽  
Ehab A. Hamed ◽  
Xincheng Zhang ◽  
Daniel Luna ◽  
Jeen-Shang Lin ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Harvesting ◽  
Solar Energy ◽  
Renewable Energy Sources ◽  
Average Energy ◽  
Vital Role ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Self Powered ◽  
Average Energy Consumption

Energy harvesting has a vital role in building reliable Environmental Wireless Sensor Networks (EWSNs), without needing to replace a discharged battery. Solar energy is one of the main renewable energy sources that can be used to efficiently charge a battery. This paper introduces two solar energy harvesters and their power measurements at different light conditions in order to charge rechargeable AA batteries powering EWSN nodes. The first harvester is a primitive energy harvesting circuit that is built using elementary off-shelf components, while the second harvester is based on a commercial boost converter chip. To prove the effectiveness of harvesting solar energy, five EWSN nodes were distributed at a nature reserve (the Audubon Society of Western Pennsylvania, USA) and the sunlight at their locations was recorded for more than five months. For each recorded illumination, the corresponding harvested energy has been estimated and compared with the average energy consumption of the EWSN with the most power consumption. The results show that the daily harvested energy effectively compensates for the energy consumption of the EWSN nodes, and the battery charge capacity of 295 mAh can reliably support their daily dynamic energy consumption.

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.

scholarly journals A Novel Approach to Reduce Energy Consumption By Clustering With Genetic Algorithm and Sleeping Time in The IoT

2021 ◽  
Author(s):  
Negin Babaei ◽  
Alireza Hedayati
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Novel Approach ◽  
Timing Mechanisms ◽  
Reduce Energy Consumption ◽  
Average Energy Consumption

Abstract Internet of things is one of the most important technologies in the last century which covers various domains such as wireless sensor networks. Wireless sensor networks consist of a large number of sensor nodes that are scattered in an environment and collect information from the surrounding environment and send it to a central station. One of the most important problems in these networks is saving energy consumption of nodes and consequently increasing lifetime of networks. Work has been done in various fields to achieve this goal, one of which is clustering and the use of sleep timing mechanisms in wireless sensor networks. Therefore, in this article, we have examined the existing protocols in this field, especially LEACH-based clustering protocols. The proposed method tries to optimize the energy consumption of nodes by using genetic-based clustering as well as a sleep scheduling mechanism based on the colonial competition algorithm. The results of this simulation show that our proposed method has improved network life (by 18%) and average energy consumption (by 11%) and reduced latency in these networks (by 17%).

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.

An Energy Aware Routing Based on Swarm Intelligence for Wireless Sensor Networks

2013 ◽  
Vol 706-708 ◽  
pp. 635-638
Author(s):  
Yong Lv
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Network Lifetime ◽  
Average Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Energy Efficient Routing

Wireless Sensor Networks consisting of nodes with limited power are deployed to collect and distribute useful information from the field to the other sensor nodes. Energy consumption is a key issue in the sensor’s communications since many use battery power, which is limited. In this paper, we describe a novel energy efficient routing approach which combines swarm intelligence, especially the ant colony based meta-heuristic, with a novel variation of reinforcement learning for sensor networks (ARNet). The main goal of our study was to maintain network lifetime at a maximum, while discovering the shortest paths from the source nodes to the sink node using an improved swarm intelligence. ARNet balances the energy consumption of nodes in the network and extends the network lifetime. Simulation results show that compared with the traditional EEABR algorithm can obviously improve adaptability and reduce the average energy consumption effectively.

scholarly journals Impedance Analysis and Optimization of Self-Powered Interface Circuit for Wireless Sensor Nodes Application

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Yuan Dong ◽  
Dezhi Li ◽  
Benjamin Ducharne ◽  
Xiaohui Wang ◽  
Jun Gao ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Power Management ◽  
The Self ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Extraction ◽  
Wireless Sensor Node ◽  
Interface Circuit ◽  
Environment Temperature ◽  
Self Powered

Energy harvesting for self-powered wireless sensor networks (WSNs) is increasingly needed. In this paper, a self-powered WSN node scenario is proposed and realized by coupling the electric charge extraction interface circuit, power management module, and wireless communication module. Firstly, the output power of an optimized self-powered energy extraction circuit is compared with different energy extraction circuits under various loads and excitation amplitudes theoretically. Then, an energy-harvesting setup is established to validate the load-carrying capacity and working condition of the self-powered optimized synchronized switch harvesting on inductor (SP-OSSHI) circuit. It gives guidance to select and estimate the appropriate energy-consuming level for the sensor and modules. Finally, by connecting the energy-harvesting system, power management element, and sensing part together, a self-powered wireless sensor node is accomplished. Under 18 Hz resonant excitation, the whole self-powered system transmits 32 bytes of data every 30 seconds including the acceleration and environment temperature. This prototype strongly proves the feasibility of the self-powered WSN node. These research results have potential to be used in different application fields.

scholarly journals A Nonlinear Electromagnetic Energy Harvesting System for Self-Powered Wireless Sensor Nodes

2019 ◽  
Vol 8 (1) ◽  
pp. 18 ◽  
Author(s):  
Kankan Li ◽  
Xuefeng He ◽  
Xingchang Wang ◽  
Senlin Jiang
Keyword(s):  
Energy Harvesting ◽  
Electromagnetic Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Interface Circuit ◽  
Electromagnetic Energy Harvesting ◽  
Energy Harvesting System ◽  
Self Powered ◽  
Nonlinear Interface

The Internet of things requires long-life wireless sensor nodes powered by the harvested energy from environments. This paper proposes a nonlinear electromagnetic energy harvesting system which may be used to construct fully self-powered wireless sensor nodes. Based on a nonlinear electromagnetic energy harvester (EMEH) with high output voltage, the model of a nonlinear interface circuit is derived and a power management circuit (PMC) is designed. The proposed PMC uses a buck–boost direct current-direct current (DC–DC) converter to match the load resistance of the nonlinear interface circuit. It includes two open-loop branches, which is beneficial to the optimization of the impedance matching. The circuit is able to work even if the stored energy is completely drained. The energy harvesting system successfully powered a wireless sensor node. Experimental results show that, under base excitations of 0.3 g and 0.4 g (where 1 g = 9.8 m·s−2) at 8 Hz, the charging efficiencies of the proposed circuit are 172% and 28.5% higher than that of the classic standard energy-harvesting (SEH) circuit. The experimental efficiency of the PMC is 41.7% under an excitation of 0.3 g at 8 Hz.

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.

Sign in / Sign up

Export Citation Format

Share Document