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Related Concept Videos

Applications of EMF Measurements01:26

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Related Experiment Video

Updated: May 8, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

SIVEH: numerical computing simulation of wireless energy-harvesting sensor nodes.

Antonio Sanchez1, Sara Blanc, Salvador Climent

  • 1ITACA Institute, Universitat Politècnica de València, Valencia 46022, Spain. antoniosanchez@itaca.upv.es

Sensors (Basel, Switzerland)
|September 7, 2013
PubMed
Summary

This study introduces SIVEH, a novel numerical energy harvesting model for sensor nodes. It uses I-V tracking for superior accuracy in predicting energy performance over long durations, optimizing for energy neutrality.

Related Experiment Videos

Last Updated: May 8, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

  • Electrical Engineering
  • Computer Science
  • Energy Systems

Background:

  • Traditional energy modeling for sensor nodes often lacks accuracy due to component variations.
  • Accurate energy harvesting predictions are crucial for the long-term operation of autonomous sensor networks.

Purpose of the Study:

  • To present SIVEH (Simulator I-V for EH), a numerical energy harvesting model for sensor nodes.
  • To demonstrate the enhanced accuracy of I-V hardware tracking over conventional methods.
  • To enable fast, long-term simulations of energy harvesting systems.

Main Methods:

  • Developed a numerical energy harvesting model, SIVEH, utilizing I-V hardware tracking.
  • Integrated dynamic adjustment of sleep time rates for energy-neutral operation.
  • Performed functional verification and comparison with classic energy modeling approaches.

Main Results:

  • SIVEH shows higher accuracy than traditional models, especially with varying power dissipation.
  • The model allows rapid simulation of extended periods (days to years) using real solar data.
  • Enhanced modeling with dynamic sleep time adjustment aids in achieving energy-neutral operation.

Conclusions:

  • SIVEH provides a more accurate and efficient tool for energy harvesting modeling in sensor nodes.
  • The I-V tracking approach is superior for components with voltage- or current-dependent power dissipation.
  • The model facilitates the design of sustainable, energy-neutral sensor systems.