Machine learning is a critical tool for sensing due to its ability to process and interpret complex sensor data, as well as to enhance the accuracy and efficiency of sensing applications in diverse fields. This paper provides an overview of machine learning’s multifaceted applications in microwave photonics, soft robotics, and precision agriculture sensing. Recently, machine learning techniques have revolutionized the field of microwave photonics. As an example, we will discuss an implementation of deep learning and generative adversarial network for data argumentation in instantaneous frequency measurement, which effectively decreases required training experimental dataset size by 98.75% and reduces error to <5%. Enhancing the practicability and accuracy of the system. Next, we shift our focus to the integration of fiber optic sensors in soft robotics to offer a lightweight, compact, and soft means of analyzing important robot parameters. By utilizing sensor data, machine learning algorithms enable real-time feedback, adaptability, and improved control of soft robot. Lastly, we also developed fiber optic sensors for non-invasive and continuous underground monitoring of root growth. Monitoring plant root growth is essential for agriculture; however, strain generated by the growth of root is relatively weak and noisy. Therefore, data collected by these fiber sensors is fed to a residual neural network to facilitate extraction of meaningful insights. In summary, machine learning has driven substantial progress in various fields that elevates the levels of accuracy and efficiency beyond previous achievements.
Optical technologies can be found in many aspects of our daily lives. We have developed three experiments using items that can be found in a toy box or around the house to demonstrate and explain optical concepts. Videos of the experiments, their principle, and applications are available on our YouTube channel. The first experiment uses moldable putty to make a shapeable lens and light guide to observe refraction and total internal reflection respectively. The putty’s characteristics allows for hand molding into different shapes to observe how light propagation is changed within the putty in real time. The second experiment is to learn about color absorption and reflection. The color pattern of clothing would change depending on the color of light that is used to illuminate it. The experiment illustrates how optical communication can use different colors to support multiple users. The third experiment uses a bubble to illustrate light interference, the principle behind eyeglasses coating. Different colors are seen at different locations on the bubble due to light interference. The above experiments can be carried out at home or at school through our outreach program. During our school outreach, we relate the above hands-on experiments with two demonstrations. The first demonstration is a laser-transmitted audio system that explains how electrical signals can be transmitted using optical fibers. While the second allows for the observation of how laser light is guided within an optical fiber. The toy-based experiments are a fun approach to introduce complex concepts to students.
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