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Opportunities and Challenges in Energy Harvesting and Smart Sensors

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 10 May 2024 | Viewed by 8207

Special Issue Editors


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Guest Editor
D.I.E.E.I., Dipartimento di Ingegneria Elettrica Elettronica e Informatica, University of Catania, Viale Andrea Doria 6, 95125 Catania, Italy
Interests: sensors; transducers; MEMS; NEMS; fluxgate magnetometers; energy harvesting; green and biodegradable sensors; bacterial-cellulose-based sensors and transducers

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Guest Editor
Electric department, National Engineering School of Sfax (ENIS), Route de la Soukra km 4 - 3038 sfax, Tunisia
Interests: Wireless Sensor Networks (WSN); microcontrollers; energy optimization; system frequency scaling; internet of things; energy harvesting; heterogeneous networks

Special Issue Information

Dear Colleagues,

Recent advances in integrated circuit consumption driven by IoT (Internet of Things) requirements offer new perspectives. Traditionally, energy harvesting was negligible compared to the consumption of the circuits. However, nowadays, new component trends enable energy harvesting as a promising solution to significantly improve the energy efficiency of an application or to simply eliminate the use of batteries in some devices such as IoT wireless sensor nodes. The sensor nodes provide extra-energy by gathering, kinetic (wind, waves, gravity, vibration), piezo, electromagnetic (radio frequencies, photovoltaic), or thermal energy (solar, thermal gradients) for an “unlimited” amount of time.

The target of this special issue is to investigate the recent trends of energy scavenging and to present the latest research, with particular focus on the power management policies combined with low-power operations for sustainable sensor networks, the design, and the modeling of energy-harvesting. Contributions to this Special Issue are invited to submit original papers and focused reviews.

Topics of interest include, but are not limited to, the following:

  • Energy management techniques
  • Hardware for energy-harvesting
  • Internet of (battery-less) things
  • Low power sensors and WSNs
  • Adaptive algorithms
  • Smart sensors and smart energy harvesting
  • Simulations of Innovative solutions for sustainable sensor networks
  • Transducer design and optimization
  • System design, modeling and integration
  • Real experimental verification and characterization

Prof. Dr. Carlo Trigona
Prof. Rym Chéour
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Sensors 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 2600 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

  • energy harvesting
  • smart sensors
  • energy management
  • energy saving
  • Wireless sensor networks
  • energy efficiency
  • system design

Published Papers (3 papers)

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Research

14 pages, 8171 KiB  
Article
Piezoelectric Energy Harvesting from Low-Frequency Vibrations Based on Magnetic Plucking and Indirect Impacts
by Michele Rosso, Alessandro Nastro, Marco Baù, Marco Ferrari, Vittorio Ferrari, Alberto Corigliano and Raffaele Ardito
Sensors 2022, 22(15), 5911; https://0-doi-org.brum.beds.ac.uk/10.3390/s22155911 - 08 Aug 2022
Cited by 7 | Viewed by 2698
Abstract
This work proposes a mono-axial piezoelectric energy harvester based on the innovative combination of magnetic plucking and indirect impacts, e.g., impacts happening on the package of the harvester. The harvester exploits a permanent magnet placed on a non-magnetic mass, free to move within [...] Read more.
This work proposes a mono-axial piezoelectric energy harvester based on the innovative combination of magnetic plucking and indirect impacts, e.g., impacts happening on the package of the harvester. The harvester exploits a permanent magnet placed on a non-magnetic mass, free to move within a predefined bounded region located in front of a piezoelectric bimorph cantilever equipped with a magnet as the tip mass. When the harvester is subjected to a low-frequency external acceleration, the moving mass induces an abrupt deflection and release of the cantilever by means of magnetic coupling, followed by impacts of the same mass against the harvester package. The combined effect of magnetic plucking and indirect impacts induces a frequency up-conversion. A prototype has been designed, fabricated, fastened to the wrist of a person by means of a wristband, and experimentally tested for different motion levels. By setting the magnets in a repulsive configuration, after 50 s of consecutive impacts induced by shaking, an energy of 253.41 μJ has been stored: this value is seven times higher compared to the case of harvester subjected to indirect impacts only, i.e., without magnetic coupling. This confirms that the combination of magnetic plucking and indirect impacts triggers the effective scavenging of electrical energy even from low-frequency non-periodical mechanical movements, such as human motion, while preserving the reliability of piezoelectric components. Full article
(This article belongs to the Special Issue Opportunities and Challenges in Energy Harvesting and Smart Sensors)
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19 pages, 7124 KiB  
Article
A Methodology for Extracting Power-Efficient and Contrast Enhanced RGB Images
by Elias Dritsas and Maria Trigka
Sensors 2022, 22(4), 1461; https://0-doi-org.brum.beds.ac.uk/10.3390/s22041461 - 14 Feb 2022
Cited by 3 | Viewed by 1645
Abstract
Smart devices have become an integral part of people’s lives. The most common activities for users of such smart devices that are energy sources are voice calls, text messages (SMS) or email, browsing the World Wide Web, streaming audio/video, and using sensor devices [...] Read more.
Smart devices have become an integral part of people’s lives. The most common activities for users of such smart devices that are energy sources are voice calls, text messages (SMS) or email, browsing the World Wide Web, streaming audio/video, and using sensor devices such as cameras, GPS, Wifi, 4G/5G, and Bluetooth either for entertainment or for the convenience of everyday life. In addition, other power sources are the device screen, RAM, and CPU. The need for communication, entertainment, and computing makes the optimal management of the power consumption of these devices crucial and necessary. In this paper, we employ a computationally efficient linear mapping algorithm known as Concurrent Brightness & Contrast Scaling (CBCS), which transforms the initial intensity value of the pixels in the YCbCr color system. We introduce a methodology that gives the user the opportunity to select a picture and modify it using the suggested algorithm in order to make it more energy-friendly with or without the application of a histogram equalization (HE). The experimental results verify the efficacy of the presented methodology through various metrics from the field of digital image processing that contribute to the choice of the optimal values for the parameters a,b that meet the user’s preferences (low or high-contrast images) and green power. For both low-contrast and low-power images, the histogram equalization should be omitted, and the appropriate a should be much lower than one. To create high-contrast and low-power images, the application of HE is essential. Finally, quantitative and qualitative evaluations have shown that the proposed approach can achieve remarkable performance. Full article
(This article belongs to the Special Issue Opportunities and Challenges in Energy Harvesting and Smart Sensors)
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17 pages, 1251 KiB  
Article
Towards Hybrid Energy-Efficient Power Management in Wireless Sensor Networks
by Rym Chéour, Mohamed Wassim Jmal, Sabrine Khriji, Dhouha El Houssaini, Carlo Trigona, Mohamed Abid and Olfa Kanoun
Sensors 2022, 22(1), 301; https://0-doi-org.brum.beds.ac.uk/10.3390/s22010301 - 31 Dec 2021
Cited by 17 | Viewed by 2661
Abstract
Wireless Sensor Networks (WSNs) are prone to highly constrained resources, as a result ensuring the proper functioning of the network is a requirement. Therefore, an effective WSN management system has to be integrated for the network efficiency. Our objective is to model, design, [...] Read more.
Wireless Sensor Networks (WSNs) are prone to highly constrained resources, as a result ensuring the proper functioning of the network is a requirement. Therefore, an effective WSN management system has to be integrated for the network efficiency. Our objective is to model, design, and propose a homogeneous WSN hybrid architecture. This work features a dedicated power utilization optimization strategy specifically for WSNs application. It is entitled Hybrid Energy-Efficient Power manager Scheduling (HEEPS). The pillars of this strategy are based on the one hand on time-out Dynamic Power Management (DPM) Intertask and on the other hand on Dynamic Voltage and Frequency Scaling (DVFS). All tasks are scheduled under Global Earliest Deadline First (GEDF) with new scheduling tests to overcome the Dhall effect. To minimize the energy consumption, the HEEPS predicts, defines and models the behavior adapted to each sensor node, as well as the associated energy management mechanism. HEEPS’s performance evaluation and analysis are performed using the STORM simulator. A comparison to the results obtained with the various state of the art approaches is presented. Results show that the power manager proposed effectively schedules tasks to use dynamically the available energy estimated gain up to 50%. Full article
(This article belongs to the Special Issue Opportunities and Challenges in Energy Harvesting and Smart Sensors)
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