Universe

Fall Detection Computer Vision Model

byIfesTask:
Object Detection
License:CC BY 4.0

How to use the Fall Detection Detection API

Try This Model

Drop an image here or click to upload

Or try a test image 

Code Snippets

from inference_sdk import InferenceHTTPClient

CLIENT = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key="API_KEY"
)

result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="fall-detection-ca3o8-bfjkl/1")
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Or, Use Free Fall-Detected Detection API

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Code
pip install inference-sdk
# 1. Import the library
from inference_sdk import InferenceHTTPClient

# 2. Connect to your workspace
client = InferenceHTTPClient(
  api_url="https://serverless.roboflow.com",
  api_key="API_KEY"
)

# 3. Run your workflow on an image
result = client.run_workflow(
  workspace_name="<YOUR_WORKSPACE>",
  workflow_id="<YOUR_WORKFLOW_ID>",
  images={
    "image": "YOUR_IMAGE.jpg"  # Path to your image file
  },
  parameters={
    "classes": "Fall-Detected"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Run on custom image

Drop an image here or click to upload

Detecting classes:
Or try a test image 
See all 4.5k imagesFall Detection fallen-person sample showing Fall-DetectedFall Detection fallen-person sample showing Fall-DetectedFall Detection fallen-person sample showing Fall-DetectedFall Detection fallen-person sample showing Fall-DetectedFall Detection fallen-person sample showing Fall-DetectedFall Detection fallen-person sample showing Fall-DetectedFall Detection fallen-person sample showing Fall-DetectedFall Detection fallen-person sample showing Fall-DetectedFall Detection fallen-person sample showing Fall-DetectedFall Detection fallen-person sample showing Fall-DetectedFall Detection fallen-person sample showing Fall-DetectedFall Detection fallen-person sample showing Fall-Detected

About Fall Detection Model

Here are a few use cases for this project:

  1. Elderly Care Monitoring: The Fall Detection model can be integrated into smart home systems or camera-assisted monitoring services to promptly identify when elderly individuals fall, enabling caregivers or family members to respond quickly to potential injuries or medical emergencies.

  2. Workplace Safety: In high-risk work environments like construction sites or factories, the Fall Detection model can be implemented to monitor employees and detect any accidents, alerting supervisors or emergency medical services immediately to provide assistance.

  3. Public Safety: Security cameras in public spaces such as parks, streets, or shopping centers can utilize the Fall Detection model to detect falls and possible criminal activities or accidents, allowing law enforcement or emergency services to respond in a timely manner.

  4. Assisted Living Facilities: The Fall Detection model can help improve the safety of residents in assisted living facilities, nursing homes, or rehabilitation centers by monitoring common areas for falls and automatically notifying staff members when incidents occur.

  5. Sports Injury Detection: The Fall Detection model can be used in gyms or sports centers to monitor athletes during training sessions, helping to quickly identify falls or injuries and enabling coaches or medical staff to intervene if necessary.

Cite This Project

LicenseCC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ fall-detection-ca3o8-bfjkl_dataset,
  title = { Fall Detection Dataset },
  type = { Open Source Dataset },
  author = { Ifes },
  howpublished = { \url{ https://universe.roboflow.com/ifes-nnvnq/fall-detection-ca3o8-bfjkl } },
  url = { https://universe.roboflow.com/ifes-nnvnq/fall-detection-ca3o8-bfjkl },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2025 },
  month = { sep },
  note = { visited on 2026-07-29 },
}

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