Playground Safety Scoring App Project

ISEF Category: Systems Software

Subcategory: Mobile Apps  ·  Difficulty: Intermediate  ·  Setup: Home Setup  ·  Time: 1 to 2 Months

The Hook

Playgrounds look safe until you test them like a machine would. A small height change or a harder landing surface can change injury risk fast. Your phone can help measure both. That makes this a real software project with a real safety use.

What Is It?

This project asks you to turn playground inspection into a mobile app. The app would guide a parent around a playground, then score features like fall height, surfacing, and equipment condition. You would use computer vision, which means software that reads images or video, to estimate things like edge height or a simple foot or heel drop response on the ground surface.

Think of it like a safety checklist with a camera attached. One part of the app can ask yes or no questions, like whether bolts are exposed or guardrails are missing. Another part can use image analysis to estimate distances or compare surface appearance before and after a small impact. The final score can compare those results with public guidance from the U.S. Consumer Product Safety Commission, so your app does more than guess.

Why This Is a Good Topic

This is a strong science fair topic because you can test whether a phone-based score matches expert safety guidelines. You can also compare different playgrounds, surfacing types, or equipment zones, which gives you clear data. The project connects to a real problem, since falls are a major cause of playground injuries. You can learn app design, image analysis, validation, and how to turn messy real-world observations into a useful scoring model.

Research Questions

• How does a phone-based surface response score compare with visual safety ratings from CPSC guidelines? ?
• What is the effect of playground surface type on the app’s predicted fall risk score? ?
• Does adding checklist questions improve agreement between app scores and guideline-based expert ratings? ?
• To what extent does camera angle change the app’s estimate of fall height or edge height? ?
• Which playground features contribute most to the final safety score in your model? ?
• How does the app perform on different equipment types, such as slides, swings, and climbers? ?

Basic Materials

• Smartphone with camera and video recording.
• Measuring tape or ruler.
• Notebook or spreadsheet for field notes.
• Printed copy of CPSC public playground safety guidelines.
• Basic tripod or phone stand.
• Chalk or tape for marking test points.
• Simple checklist form for observations.

Advanced Materials

• Smartphone with depth sensor or multiple cameras.
• Tripod with adjustable height.
• Reference object with known dimensions for camera calibration.
• Portable surface hardness tester or durometer.
• Small data logger or accelerometer sensor.
• Laptop for model testing and error analysis.
• Access to labeled playground inspection examples for training or validation.

Software & Tools

• Google Sheets: Organizes field data and helps you compare app scores across playgrounds.

Experiment Steps

1. Define the exact safety features your app will score, such as surface type, fall height, and checklist items.
2. Choose one clear output, such as a single safety score or a ranked risk level.
3. Design the image or video measurements you can estimate reliably with a phone camera.
4. Build a reference set of playground examples and label them using public safety guidance.
5. Plan how you will compare app predictions with a human checklist or guideline-based score.
6. Decide what error metric will tell you whether the app is accurate enough to matter.

Common Pitfalls

• Using shaky handheld video, which makes edge detection and height estimates jump around.
• Mixing different lighting conditions, which changes surface appearance and breaks image-based scoring.
• Treating checklist answers as ground truth without checking them against public safety guidance.
• Building a single overall score that hides which playground feature caused the risk.
• Testing only one playground type, which makes the app look better than it really is.

What Makes This Competitive

A stronger project will do more than make a working app. You can compare your scores against a clear external standard, then measure where the app fails and why. You can also test whether one feature, like surface response, adds predictive value beyond a simple checklist. If you include calibration, error analysis, and a comparison across several playground types, your project starts to look like real validation work.

Project Variations

• Compare urban and suburban playgrounds to see whether your app gives different risk profiles by setting.
• Focus only on surfacing and test whether surface compressibility predicts the final safety score better than visual inspection alone.
• Build a version that scores accessibility features, such as transfer points and path width, alongside safety features.

Learn More

• OpenCV Documentation: Read the official guides for edge detection, image calibration, and video processing.