Combining solar and vibration energy harvesting for rainfall prediction

Overview

Rainfall prediction plays a crucial role in various sectors such as agriculture, water resource management, and disaster preparedness. Traditional prediction methods often rely on complex meteorological models and expensive equipment. However, advancements in energy harvesting technology offer the opportunity to develop low-cost and sustainable solutions for rainfall prediction.

This project proposes to leverage solar and vibration energy harvesting for rainfall prediction. Combined measurements from both solar and vibration energy harvesting can provide comprehensive data for real-time monitoring of cloud coverage and rainfall intensity. By continuously monitoring the cloud coverage using solar panels output and the intensity of rain using piezoelectric transducers, patterns and trends in cloud coverage and rainfall intensity can be analysed. Machine learning algorithms can then be employed to predict future rainfall based on historical data and current energy harvesting readings, leading to accurate and reliable rainfall prediction.

Research activities

Research activities include the following:

• Investigate the principles of operation and characteristics of solar panels and piezoelectric materials.
• Design and fabricate a prototype integrating solar panels with piezoelectric coatings and capable of simultaneously sampling the solar panel and the piezoelectric outputs.
• Develop algorithms and methods for data analysis to extract meaningful information from the solar panel output for sensing cloud coverage and piezoelectric output for measuring rainfall intensity.
• Evaluate the performance and accuracy of the integrated sensing system in real-world weather conditions.
• Demonstrate the potential applications and benefits of the proposed solution for weather monitoring and rainfall prediction.

Outcomes

The aim of this bachelor project is to explore the feasibility of combining solar panels and piezoelectric coatings for cloud coverage sensing and rainfall prediction. By leveraging renewable energy sources and innovative sensing technologies, this project seeks to develop a sustainable and cost-effective solution for monitoring weather patterns and predicting rainfall events.

Skills and experience

Familiarity with energy harvesting technology and data analysis with Python programming skills.

Keywords

• energy harvesting
• data science
• machine learning

Contact

Contact the supervisor for more information.