Energy Harvesting Based Wireless Sensor Research Articles

Coverage performance of nonlinear energy harvesting based wireless sensor networks for the healthcare in hospitals

Wireless sensors are important nowadays to collect real‐time data in hospital wards. Small sensors can be deployed either on/in patients' bodies or at fixed locations in wards. We propose an autonomous wireless system, where sensors can harvest energy from radio frequency signals, monitor and transmit data using the harvested energy. By properly modeling energy statuses and stochastic distributions of sensors, we analyze the coverage performance using Campbell's theorem, probability generating functional (PGFL), and Gil‐Pelaez inversion theorem. The nonlinear energy harvesting model and the general Nakagami‐m fading channels are considered in the analysis. Numerical results show that the coverage performance degrades when sensors are distributed more densely, the energy and data links are prolonged, or the transmission rate gets larger, while it improves when higher power is used for the energy transfer, or the energy and data links undergo lighter fading. Our proposed scheme can well facilitate the long‐time monitoring tasks in hospital wards, which can greatly alleviate the burdens of medical staff.

Machine Learning Prediction Based Adaptive Duty Cycle MAC Protocol for Solar Energy Harvesting Wireless Sensor Networks

The dynamic nature of energy harvesting rate, arising because of ever changing weather conditions, raises new concerns in energy harvesting based wireless sensor networks (EH-WSNs). Therefore, this drives the development of energy aware EH solutions. Formerly, many Medium Access Control (MAC) protocols have been developed for EH-WSNs. However, optimizing MAC protocol performance by incorporating predicted future energy intake is relatively new in EH-WSNs. Furthermore, existing MAC protocols do not fully harness the high harvested energy to perform aggressively despite the availability of sufficient energy resources. Therefore, a prediction-based adaptive duty cycle (PADC) MAC protocol has been proposed, called PADC-MAC, that incorporates current and future harvested energy information using the mathematical formulation to improve network performance. Furthermore, a machine learning model, namely nonlinear autoregressive (NAR) neural network, is employed that achieves good prediction accuracy under dynamic harvesting scenarios. As a result, it enables the receiver node to perform aggressively better when there is sufficient inflow of incoming harvesting energy. In addition, PADC-MAC uses a self-adaptation technique that reduces energy consumption. The performance of PADC-MAC is evaluated using GreenCastalia in terms of packet delay, network throughput, packet delivery ratio, energy consumption per bit, receiver energy consumption, and total network energy consumption using realistic harvesting data for 96 consecutive hours under dynamic solar harvesting conditions. The simulation results show that PADC-MAC provides lower average packet delay of the highest priority packets and all packets, energy consumption per bit, and total energy consumption by more than 10.7%, 7.8%, 81%, and 76.4%, respectively when compared to three state-of-the-art protocols for EH-WSNs.

Traffic Models for Energy Harvesting Based Wireless Sensor Networks

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.

Adaptive MAC Protocol for Solar Energy Harvesting Based Wireless Sensor Networks in Agriculture

The wireless sensor network is one of the promising technologies in the agriculture field. Its actual usage in real agriculture fields is limited by its dependence on the small batteries which cannot make the network survive for long. Various protocols are being designed at the network and MAC layer to increase the lifetime of the nodes, but up to a certain extent only. Hence the energy harvesting to power up the WSN nodes is a promising technology to fulfill this ever energy demand, but the protocols need to be redesigned for this scenario. Solar energy harvesting based MAC protocol which is adaptive to the changing weather conditions is designed in this paper for the smart agriculture applications. It is based on the multilayer and receiver-initiated process to improve network quality. It has shown the remarkable performance over the other energy harvesting based protocols in terms of ENO ratio, energy consumption and collision rate.

Design and Fabrication of a 3-D Printed Concentrating Solar Thermoelectric Generator for Energy Harvesting Based Wireless Sensor Nodes

This letter presents the design of a solar thermoelectric generator (STEG) system for long-range wireless sensor networks in precision agriculture applications. The proposed STEG consists of a sunlight concentrator structure integrated with a Fresnel lens and a commercial thermoelectric module that is adapted to an energy harvester circuit and a wireless sensor node. The STEG is assembled using an inexpensive 3-D printed structure that can be mechanically adjusted to different sun exposure conditions. The proposed STEG prototype has been fabricated and tested. Measurement results demonstrate the STEG's capability of generating a maximum temperature difference of 60 °C between the hot-side of the thermoelectric module and the heatsink attached to the cold-side, with a maximum instantaneous output power of 6.93 mW. Charging a 0.22 F supercapacitor, the STEG supplies enough energy in approximately 2.2 h to sustain the operation of a wireless sensor node that measures soil temperature, humidity, and conductivity for precision agriculture applications. This letter presents a promising, cost-effective new approach to the conversion of solar energy into electricity for self-powered sensor networks.

Recent Advances in MAC Protocols for the Energy Harvesting Based WSN: A Comprehensive Review

Wireless sensor networks are catching the attention of the researchers in various fields like structural, healthcare monitoring, but the real world adoption is getting difficult due to its dependence on the battery power, so energy harvesting comes to its rescue. To utilize the harvested energy in the best manner, MAC protocols which control the transreceiver in a node are presented here. They are different from the battery powered WSN where the focus is on increasing the lifetime of the nodes, rather these protocols focus on improving the quality of the network. With optimal tradeoff between the infinite network lifetime and energy availability, MAC protocols need to be redesigned for energy harvesting based wireless sensor networks (EHWSN). In this paper first EH technology in wireless sensor networks is discussed. Then a survey of EH based MAC protocols is done in a classified manner. The comparison of the protocols is done based on the different metrics such as energy conservation factor, scalability, latency etc. State of the art literature survey is presented so that users have consolidated data to pick up the one based on their application requirement. Challenges specific to applications is presented along with the various gaps to give an insight into the future research directions. To the best of the author’s knowledge, review of all the EHWSN MAC protocols is not reported till date.

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks.

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks.