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I. Abstract
I. Abstract
In this study, we design and implement an AIoT-enabled simple pendulum experiment to explore the relationship between the pendulum's period, length, and mass. Leveraging an Arduino-based system equipped with an IR emitter and receiver, we precisely measure the pendulum's oscillation period, while 3D-printed components allow for tunable control over the pendulum's length and mass.
In this study, we design and implement an AIoT-enabled simple pendulum experiment to explore the relationship between the pendulum's period, length, and mass. Leveraging an Arduino-based system equipped with an IR emitter and receiver, we precisely measure the pendulum's oscillation period, while 3D-printed components allow for tunable control over the pendulum's length and mass.
Integrating the Internet of Things (IoT) enables real-time data collection and analysis, providing an enhanced framework for conducting experiments. Through this setup, we validate the classical pendulum theory, showing that the period depends on the square root of the length and is independent of mass for small angles. The experiment also allows for investigating damped and driven pendulum behaviors. Our approach highlights the educational and research potential of combining AI, IoT, and traditional physics experiments to enhance experimental accuracy and understanding.
Integrating the Internet of Things (IoT) enables real-time data collection and analysis, providing an enhanced framework for conducting experiments. Through this setup, we validate the classical pendulum theory, showing that the period depends on the square root of the length and is independent of mass for small angles. The experiment also allows for investigating damped and driven pendulum behaviors. Our approach highlights the educational and research potential of combining AI, IoT, and traditional physics experiments to enhance experimental accuracy and understanding.
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