ReviewSensors (Basel, Switzerland)2018
Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review.
Review in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of Precision Agriculture Technologies for Sustainable Crop Production and Environmental Sustainability: A Systematic Review.TheScientificWorldJournal · 2024Pooled it
- BDD/PPy Composites with Low Interfacial Resistance for Energy Storage and Theoretical Feasibility for Pollutant Sensing.Nanomaterials (Basel, Switzerland) · 2026Article
- Optimized Rectifier Topologies for Low-Voltage Electromagnetic Energy Harvesters.Sensors (Basel, Switzerland) · 2026Article
- Batteryless IoT Sensing Using Thermoelectric Energy Harvesting from Industrial Motor Waste Heat.Sensors (Basel, Switzerland) · 2026Article
- Multi-Band Enhanced Energy Harvesting from Dual Sources Using a Symmetrical Gradient Metamaterial Beam.Sensors (Basel, Switzerland) · 2025Article
- Self-generated temperature gradient under uniform heating in p-i-n junction carbon nanotube thermoelectric generators.Scientific reports · 2025Article
- Theoretical and Experimental Study of Energy-Harvesting and Movement-Sensing Solutions in Pneumatic Systems.Sensors (Basel, Switzerland) · 2024Article
- ERIRMS Evaluation of the Reliability of IoT-Aided Remote Monitoring Systems of Low-Voltage Overhead Transmission Lines.Sensors (Basel, Switzerland) · 2024Article
- Design and development of a compact, wide-angle metamaterial electromagnetic energy harvester with multiband functionality and polarization-insensitive features.Scientific reports · 2024Article
- Optimal Design and Development of Magnetic Field Detection Sensor for AC Power Cable.Sensors (Basel, Switzerland) · 2024Article
- Electromagnetic Energy Harvester Targeting Wearable and Biomedical Applications.Sensors (Basel, Switzerland) · 2024Article
- Advances in Smart Photovoltaic Textiles.ACS nano · 2024Review
- Smart Detecting and Versatile Wearable Electrical Sensing Mediums for Healthcare.Sensors (Basel, Switzerland) · 2023Review
- Article
- A Comprehensive Survey on RF Energy Harvesting: Applications and Performance Determinants.Sensors (Basel, Switzerland) · 2022Review
- Tool Condition Monitoring for High-Performance Machining Systems-A Review.Sensors (Basel, Switzerland) · 2022Review
- Enabling Distributed Intelligence with Ferroelectric Multifunctionalities.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Review
- A High-Performance Coniform Helmholtz Resonator-Based Triboelectric Nanogenerator for Acoustic Energy Harvesting.Nanomaterials (Basel, Switzerland) · 2021Article
- Application of NSGA-II to Obtain the Charging Current-Time Tradeoff Curve in Battery Based Underwater Wireless Sensor Nodes.Sensors (Basel, Switzerland) · 2021Article
- A Survey on the Application of WirelessHART for Industrial Process Monitoring and Control.Sensors (Basel, Switzerland) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Condition monitoring can reduce machine breakdown losses, increase productivity and operation safety, and therefore deliver significant benefits to many industries. The emergence of wireless sensor networks (WSNs) with smart processing ability play an ever-growing role in online condition monitoring of machines. WSNs are cost-effective networking systems for machine condition monitoring. It avoids cable usage and eases system deployment in industry, which leads to significant savings. Powering the nodes is one of the major challenges for a true WSN system, especially when positioned at inaccessible or dangerous locations and in harsh environments. Promising energy harvesting technologies have attracted the attention of engineers because they convert microwatt or milliwatt level power from the environment to implement maintenance-free machine condition monitoring systems with WSNs. The motivation of this review is to investigate the energy sources, stimulate the application of energy harvesting based WSNs, and evaluate the improvement of energy harvesting systems for mechanical condition monitoring. This paper overviews the principles of a number of energy harvesting technologies applicable to industrial machines by investigating the power consumption of WSNs and the potential energy sources in mechanical systems. Many models or prototypes with different features are reviewed, especially in the mechanical field. Energy harvesting technologies are evaluated for further development according to the comparison of their advantages and disadvantages. Finally, a discussion of the challenges and potential future research of energy harvesting systems powering WSNs for machine condition monitoring is made.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.