Date
Publisher
arXiv
Smartphones have become a standard measurement instrument in the physics laboratory. Their built-in accelerometers, gyroscopes, magnetometers, and cameras have been used to investigate a wide range of phenomena in mechanics, and rotational motion in particular has proven especially well-suited to smartphone-based experiments. A recurring limitation, however, is that most experiments rely on precompiled sensor apps whose interfaces cannot be tailored to a specific activity, and until recently creating customized smartphone laboratories required programming knowledge beyond what most physics teachers possess. This paper makes two connected contributions. First, we present a validated smartphone experiment for uniform circular motion (UCM) and uniformly accelerated circular motion (UACM), in which the angular velocity and the angular acceleration are obtained from two independent smartphone channels and checked against independent video analysis with Tracker.10,14 Second, we show that generative AI can serve as a no-code development tool for the physics laboratory: the browser-based application used here was produced entirely through natural-language prompting, with no manual coding, extending to rotational motion the approach we recently introduced for acoustic experiments. The emphasis is therefore not only on what is measured, but also on how the measuring instrument itself was built.
Study at a glance
- Question: Can generative AI create a custom browser app that accurately measures circular motion using smartphone sensors?
- Setting and data: Laboratory setup using a Redmi Note 13 Pro 5G smartphone on a rotating platform, with measurements recorded at 50 Hz.
- Method: Laboratory experiment comparing AI-generated browser app sensor data with independent video analysis (Tracker).
Why it matters
Most smartphone physics experiments rely on precompiled apps that teachers cannot customize. Creating tailored laboratory tools traditionally required programming skills beyond what most physics educators possess.
Key findings
- A custom browser laboratory application was generated entirely through natural-language prompts without writing or editing any code by hand.
- Measurements of angular velocity and angular acceleration between the smartphone's internal sensor channels differed by only 0.1% to 0.5%.
- Smartphone sensor measurements agreed with independent video analysis to better than 0.5% for uniform circular motion and below 1% for accelerated circular motion.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
