Piezoelectric Sensors as Energy Harvesters for Ultra Low-Power IoT Applications.

Industrial Internet of Things LoRaWAN energy harvesting piezoelectric vibration

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
18 Apr 2024
Historique:
received: 20 03 2024
revised: 12 04 2024
accepted: 16 04 2024
medline: 27 4 2024
pubmed: 27 4 2024
entrez: 27 4 2024
Statut: epublish

Résumé

The aim of this paper is to discuss the usability of vibrations as energy sources, for the implementation of energy self-sufficient wireless sensing platforms within the Industrial Internet of Things (IIoT) framework. In this context, this paper proposes to equip vibrating assets like machinery with piezoelectric sensors, used to set up energy self-sufficient sensing platforms for hard-to-reach positions. Preliminary measurements as well as extended laboratory tests are proposed to understand the behavior of commercial piezoelectric sensors when employed as energy harvesters. First, a general architecture for a vibration-powered LoRaWAN-based sensor node is proposed. Final tests are then performed to identify an ideal trade-off between sensor sampling rates and energy availability. The target is to ensure continuous operation of the device while guaranteeing a charging trend of the storage component connected to the system. In this context, an Ultra-Low-Power Energy-Harvesting Integrated Circuit plays a crucial role by ensuring the correct regulation of the output with very high efficiency.

Identifiants

pubmed: 38676204
pii: s24082587
doi: 10.3390/s24082587
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Francesco Rigo (F)

Department of Information Engineering, University of Padova, 35131 Padova, Italy.

Marco Migliorini (M)

Department of Information Engineering, University of Padova, 35131 Padova, Italy.

Alessandro Pozzebon (A)

Department of Information Engineering, University of Padova, 35131 Padova, Italy.

Classifications MeSH