Solar Energy Harvesting System for Wireless Sensor Networks
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".
Deadline for manuscript submissions: closed (10 February 2023) | Viewed by 4175
Special Issue Editors
Interests: IoT; WSN; CPS; edge AI; green computing; approximate computing
Interests: embedded computing system; machine learning at the edge; energy-quality scalability; mobile and embedded security; and Internet-of-Things
Special Issue Information
Dear Colleagues,
A lot of platforms for wireless sensor networks (WSNs) are designed to run on batteries, which have a very limited lifetime. This energy constraint causes a severe problem for applications in which a sensor system is supposed to operate for long periods. Longer lifetimes are necessary if WSNs are to become a ubiquitous part of our environment. While a lot of effort has been put into developing techniques to make more efficient use of limited amounts of energy, alternative power sources will eventually need to be employed.
Environmental energy has recently emerged as a feasible supplement to battery power for wireless sensor systems where manual recharging or replacement of batteries is not practical. Since solar energy has a high-power density (compared to other renewable energy sources) and a periodic charge cycle, it is one of the most attractive energy sources. Therefore, we invite cutting-edge scientific researchers to draw a picture of the use of solar energy to WSNs. Topics of interest include, but are not limited to, the following research issues:
- Network-wide distributed protocols to enhance QoS for solar-powered WSNs (e.g. routing protocol, MAC protocol);
- Resource management for energy neutral operations;
- Advancements on circuits of solar-energy harvesting for embedded systems;
- Power management algorithms for solar-energy harvesting sensing systems;
- Architectures for energy-neutral sensing systems;
- Middleware support for interoperability among WSNs using heterogeneous energy sources;
- Online measurement and forecasting algorithms of solar energy intake and consumption;
- Simulation tools and modelling of solar-powered WSNs;
- Practical deployments and implementation experiences.
Prof. Dong Kun Noh
Prof. Younghyun Kim
Dr. Ikjune Yoon
Guest Editors
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