Energy Harvesting and Sustainable Structure Monitoring System

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708). This special issue belongs to the section "Network Services and Applications".

Deadline for manuscript submissions: closed (7 October 2021) | Viewed by 4381

Special Issue Editors


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Guest Editor
Pyro-E, LLC
Interests: low power wireless sensor; energy harvesting; structure health monitoring; piezoelectric device; power management circuit

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Co-Guest Editor
The University of Texas Rio Grande Valley, Edinburg Campus, 1201 W University Dr, Edinburg, TX 78539, USA
Interests: solid mechanics; piezoelectric energy harvesting; high-entropy alloys; extreme loadings
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is proposed to encourage further research and development of energy harvesting systems and wireless sensor networks for sustainable monitoring systems.

Powering wireless sensor nodes are one of the most attractive applications of energy-harvesting technology for various monitoring purposes for low-cost and sustainable systems, and the extension of lifetime of battery-operated wireless monitoring systems is an essential research topic. Wireless transceiver and sensor design affect the lifetime and reliability of wireless monitoring systems, and hence, the development of a low-power design of wireless sensor nodes is a key technology for sustainable monitoring systems. An energy harvester needs to be designed to meet the power requirements of the wireless sensor and integrated with a power management circuit for maximum power conversion.

Original contributions including the state-of-the-art, benefits of emerging technologies, experimental studies, or which investigate novel schemes and applications are welcome.

Topics relevant to the Special Issue include but are not limited to:

  • Sensor design and implementation for low-power operation;
  • Novel interface circuit for sensors and actuators;
  • Novel energy harvesting systems for sustainable monitoring systems;
  • Low power wireless transceiver design;
  • Low power management for sustainable wireless sensor networks;
  • Energy management algorism for sustainable monitoring systems;
  • Damage detection/localization/assessment
  • Energy harvesting for sustainable and resilient infrastructures.

Dr. Hyunjun Jung
Dr. Yooseob Song
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Sensor and Actuator Networks is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • low power wireless network
  • sensor and actuator
  • structure health monitoring
  • energy management
  • energy harvesting
  • low power electronics

Published Papers (1 paper)

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Research

33 pages, 8845 KiB  
Article
WHISPER: Wireless Home Identification and Sensing Platform for Energy Reduction
by Margarite Jacoby, Sin Yong Tan, Mohamad Katanbaf, Ali Saffari, Homagni Saha, Zerina Kapetanovic, Jasmine Garland, Anthony Florita, Gregor Henze, Soumik Sarkar and Joshua Smith
J. Sens. Actuator Netw. 2021, 10(4), 71; https://0-doi-org.brum.beds.ac.uk/10.3390/jsan10040071 - 06 Dec 2021
Cited by 4 | Viewed by 3849
Abstract
Many regions of the world benefit from heating, ventilating, and air-conditioning (HVAC) systems to provide productive, comfortable, and healthy indoor environments, which are enabled by automatic building controls. Due to climate change, population growth, and industrialization, HVAC use is globally on the rise. [...] Read more.
Many regions of the world benefit from heating, ventilating, and air-conditioning (HVAC) systems to provide productive, comfortable, and healthy indoor environments, which are enabled by automatic building controls. Due to climate change, population growth, and industrialization, HVAC use is globally on the rise. Unfortunately, these systems often operate in a continuous fashion without regard to actual human presence, leading to unnecessary energy consumption. As a result, the heating, ventilation, and cooling of unoccupied building spaces makes a substantial contribution to the harmful environmental impacts associated with carbon-based electric power generation, which is important to remedy. For our modern electric power system, transitioning to low-carbon renewable energy is facilitated by integration with distributed energy resources. Automatic engagement between the grid and consumers will be necessary to enable a clean yet stable electric grid, when integrating these variable and uncertain renewable energy sources. We present the WHISPER (Wireless Home Identification and Sensing Platform for Energy Reduction) system to address the energy and power demand triggered by human presence in homes. The presented system includes a maintenance-free and privacy-preserving human occupancy detection system wherein a local wireless network of battery-free environmental, acoustic energy, and image sensors are deployed to monitor homes, record empirical data for a range of monitored modalities, and transmit it to a base station. Several machine learning algorithms are implemented at the base station to infer human presence based on the received data, harnessing a hierarchical sensor fusion algorithm. Results from the prototype system demonstrate an accuracy in human presence detection in excess of 95%; ongoing commercialization efforts suggest approximately 99% accuracy. Using machine learning, WHISPER enables various applications based on its binary occupancy prediction, allowing situation-specific controls targeted at both personalized smart home and electric grid modernization opportunities. Full article
(This article belongs to the Special Issue Energy Harvesting and Sustainable Structure Monitoring System)
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