Edge-IoT Synthetic Data Engine

Bankole Synthetic Sensor API

A FastAPI-powered synthetic data engine that streams realistic IoT sensor readings for prototyping, testing, and demonstration. Generate configurable accelerometer, gyroscope, and environmental sensor data on demand through a simple REST interface.

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Sample Dataset Preview

A synthetic sensor dataset with 60 records spanning accelerometer vibration, temperature, pressure, and soil moisture readings. Some entries simulate sensor anomalies (high temperature, pressure, and moisture) for testing detection logic.

timestamp	vibration	temperature	pressure	soil_moisture	anomaly
0	0.013378907718622983	19.887993997169936	101.29934940739335	30.275496537022644	false
1	-0.0051279438967971255	20.218571999896525	101.50264340584152	30.00539624923254	false
2	0.026788528337124532	19.903476405480728	101.27622223492813	30.086205501401068	false
3	0.13179823650671166	20.241845048629045	101.13957051142104	29.868081090893888	false
4	-0.04599942146030294	19.919334812087254	101.5130935673119	29.948828521732473	false

Showing rows 0-4. The full dataset (60 rows) is available for download.

Quickstart - Python

Install the requests library and call the /stream endpoint to receive a batch of synthetic sensor readings.

python

import requests

url = "http://localhost:8000/stream"
params = {"sample_rate_hz": 10, "duration_seconds": 5}

response = requests.get(url, params=params)
data = response.json()
print(data)

Quickstart - cURL

Use cURL to fetch synthetic data directly from the command line:

bash

curl "http://localhost:8000/stream?sample_rate_hz=10&duration_seconds=5"

Live Sample Response

Fetch a live 5-second sample at 1 Hz from the running API server:

Integration Instructions

Run the FastAPI server locally to serve synthetic sensor data:

1. Install Dependencies

bash

pip install fastapi uvicorn pydantic numpy

2. Start the Server

From the directory containing sensor_synthetic_data.py, run:

bash

uvicorn sensor_synthetic_data:app --reload

The API will be available at http://localhost:8000. The --reload flag enables hot-reloading during development.

3. Calling from Other Languages

The API returns JSON, so you can call it from any language. Here is a JavaScript example using the Fetch API (browser or Node.js):

javascript

fetch("http://localhost:8000/stream?sample_rate_hz=10&duration_seconds=5")
  .then((res) => res.json())
  .then((data) => console.log(data));