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Updated: Jul 8, 2025
08:54
Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing
Published on: February 13, 2018
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Computation harvesting from nature dynamics for predicting wind speed and direction.
Takumi Aita1, Hiroyasu Ando2, Yuichi Katori3,4
1Graduate School of Science and Technology, University of Tsukuba, Tsukuba, Japan.
Plos One
|December 14, 2023
Summary
This study uses plant movement in movies as natural sensors to estimate wind speed and direction. This approach demonstrates robust and generalizable computation from natural dynamics.
Area of Science:
- Complex systems and natural computation.
- Exploiting nonlinear dynamics for computational resources.
Background:
- Natural phenomena exhibit complex dynamics due to nonlinear interactions.
- Natural computation frameworks utilize phenomena like quantum mechanics and cellular dynamics for calculations.
- Sensor-rich environments enable the observation of natural dynamics, such as plant movement captured by cameras.
Purpose of the Study:
- To present a methodology for estimating wind speed and direction using naturally occurring sensors in movies.
- To investigate the computational capabilities of natural dynamics for environmental sensing.
- To demonstrate the robustness and generalization performance of this natural computation approach.
Main Methods:
- Utilizing physical reservoir computing principles.
- Analyzing images of plant movement as indirect sensor outputs reflecting wind state.
- Developing a methodology for wind speed and direction estimation from video data.
Main Results:
- Demonstrated the effectiveness of the proposed methodology through experimentation.
- Revealed high robustness in estimating wind parameters from natural sensor data.
- Showcased strong generalization performance for computational tasks using natural dynamics.
Conclusions:
- Natural dynamics, exemplified by plant movement, can serve as effective natural sensors.
- The proposed physical reservoir computing approach offers a robust and generalizable method for environmental sensing.
- This work highlights the potential of natural computation in a sensor-rich society.
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