Have you ever been trapped in unexpected heavy rain? Weather forecasting systems have long tried to predict adverse weather events. However, these systems rely heavily on bulky, static, and expensive equipment such as weather radar, which hampers timely updates to local weather conditions for personal use. To address this gap in knowledge and practical application, a research team from Osaka Metropolitan University and University of Tokyo has developed a lightweight, attachable sensor plate that features a flexible impedance sensor and tank computing analysis.
This single device allows real-time measurement of raindrop size and Wind speedreports weather information When attached to awnings, cars or homes. Professor Kuniharu Takei, head of the research from Osaka Metropolitan University, noted, “The results open a promising economic approach. weather Reporting and contributing to disaster preparedness And more safety for the community.”
To determine the volume of rain, the sensor measures electrical resistance It is generated when a drop of rain hits its surface. It is protected by a highly hydrophobic silicone sheet of polydimethylsiloxane (PDMS), which is immersed in graphene and treated with a laser. The highly water-resistant silicone repels water droplets, ensuring the sensor’s durability and stability. Laser installation allows continuous control and measurement of behavior Water dropswhether they are standing, sliding, bouncing, or splitting on the sensor surface.
The sensor can be easily installed over a wide range of surfaces and remains effective when flat or curved. Testing of changes in rain volume estimates using the sensor mounted at different angles showed no significant differences, indicating that the sensor could be connected to hand-held items such as umbrellas. If it is widely adopted, it will be possible to obtain collective data that will enable the development of local weather maps in real time.
Wind speed has a significant influence on the behavior of water droplets, indicating the need to measure wind speed at the same time as raindrop size. Traditionally, measuring multiple pieces of weather data would require multiple sensors, which increases power consumption. Going beyond this traditional practice, the researchers used a machine learning algorithm called Reservoir Computing (RC) to analyze the output data. Changes in the rain and wind conditions It resulted from changes in resistance that were detected by the sensor and then recorded as time series data. This data was used to train the machine, which predicted the pattern and reported rain volume and wind speed as output information.
Although there is still more work to be done to improve its accuracy, the sensor is expected to be a mainstay for the next generation of weather sensing. The study published in advanced materials, advances the United Nations Sustainable Development Goals on resilient infrastructure, sustainable cities and climate action. “We believe that this device can contribute to the realization of the ultimate IoT society, which is safe, convenient and disaster-free,” concluded Professor Takei, “and we would like to actively participate in industry, government and academia cooperation that promotes such practical applications.”
Seiji Wakabayashi et al, A flexible multitasking sensor via reservoir computation, advanced materials (2022). DOI: 10.1002 / adma.202201663
Presented by Osaka Metropolitan University
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