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I. Abstract
I. Abstract
The AIoTs Free Fall Experiment aims to measure the acceleration due to gravity g by integrating Artificial Intelligence of Things (AIoTs) technology with video analysis. In this experiment, a small object is dropped from various heights, and its motion is recorded using a webcam. The recorded video is then analyzed using ImageJ software, which tracks the object’s position frame-by-frame.
The AIoTs Free Fall Experiment aims to measure the acceleration due to gravity g by integrating Artificial Intelligence of Things (AIoTs) technology with video analysis. In this experiment, a small object is dropped from various heights, and its motion is recorded using a webcam. The recorded video is then analyzed using ImageJ software, which tracks the object’s position frame-by-frame.
This data is used to generate height vs time and height vs time squared graphs, from which the gravitational acceleration is calculated. The experiment highlights the use of AIoTs in improving data collection and analysis in physics education, enabling precise measurement of motion and fostering a deeper understanding of classical mechanics. Additionally, the results are compared to the theoretical value of g=9.81 m/s², with consideration of possible errors due to factors such as air resistance and measurement inaccuracies. This approach enhances traditional experimental methods by leveraging AIoTs for real-time data processing and analysis.
This data is used to generate height vs time and height vs time squared graphs, from which the gravitational acceleration is calculated. The experiment highlights the use of AIoTs in improving data collection and analysis in physics education, enabling precise measurement of motion and fostering a deeper understanding of classical mechanics. Additionally, the results are compared to the theoretical value of g=9.81 m/s², with consideration of possible errors due to factors such as air resistance and measurement inaccuracies. This approach enhances traditional experimental methods by leveraging AIoTs for real-time data processing and analysis.
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