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neha-priya-1171/sensor-telemetry-pipeline

API development

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A personal project by a 2nd-year ECE student demonstrating how structured prompt engineering can bridge embedded hardware to cloud backends — without writing a single line of server code from scratch.

개요

A personal project by a 2nd-year ECE student demonstrating how structured prompt engineering can bridge embedded hardware to cloud backends — without writing a single line of server code from scratch. An ESP32 microcontroller reads 6-axis IMU sensor data, timestamps it using NTP, and sends it over Wi-Fi to a FastAPI server hosted on Replit — which validates the data and stores it in a SQLite database. Every packet returns HTTP 201 Created with a sequential record_id. The entire backend was — specifically applying the prompt engineering techniques from my coursework: role framing, iterative refinement, error-driven prompting, and schema anchoring. In Electronics & Communication Engineering, the gap between hardware and software is shrinking fast. Cyber-physical systems, IoT, and smart devices are increasingly central to the field — and they all require this exact stack: a microcontroller producing data, a network layer transporting it, and a backend storing it.

README

원문 README의 일부입니다. 원문 보기.

ESP32 IoT Telemetry Pipeline

Built entirely with AI — no prior backend experience required.

A personal project by a 2nd-year ECE student demonstrating how structured prompt engineering can bridge embedded hardware to cloud backends — without writing a single line of server code from scratch.


What is this?

An ESP32 microcontroller reads 6-axis IMU sensor data, timestamps it using NTP, and sends it over Wi-Fi to a FastAPI server hosted on Replit — which validates the data and stores it in a SQLite database. Every packet returns HTTP 201 Created with a sequential record_id.

The entire backend was scaffolded, debugged, and deployed using AI — specifically applying the prompt engineering techniques from my coursework: role framing, iterative refinement, error-driven prompting, and schema anchoring.


Why this matters for ECE

In Electronics & Communication Engineering, the gap between hardware and software is shrinking fast. Cyber-physical systems, IoT, and smart devices are increasingly central to the field — and they all require this exact stack: a microcontroller producing data, a network layer transporting it, and a backend storing it.

This project proves you don’t need a full software engineering background to build that pipeline. You need to know what to ask for and how to read the errors.


System Architecture

ESP32 Dev Module
│
├── Reads IMU (accel_x/y/z, gyro_x/y/z)
├── Syncs clock via NTP → pool.ntp.org
├── Builds JSON payload with 13-digit epoch timestamp
└── HTTP POST ──► /api/v1/telemetry
                    │
                    ├── X-API-Key header check
                    ├── Pydantic schema validation
                    ├── Replay attack timestamp check
                    └── SQLite INSERT → returns record_id
sequenceDiagram
    participant ESP32
    participant NTP as pool.ntp.org
    participant API as FastAPI (Replit)
    participant DB as SQLite

    ESP32->>NTP: Sync clock on boot
    NTP-->>ESP32: Unix epoch (ms)
    loop Every 5 seconds
        ESP32->>API: POST /api/v1/telemetry + X-API-Key
        API->>API: Validate key → schema → timestamp
        API->>DB: INSERT record
        DB-->>API: record_id
        API-->>ESP32: 201 Created {record_id: 286}
    end

The Payload Schema

This is the exact JSON structure the Pydantic model expects. Any deviation returns HTTP 422.

{
  "device_id": "esp32-node-01",
  "firmware_version": "1.0.0",
  "timestamp_ms": 1781670054657,
  "imu": {
GitHub에서 전체 README 보기

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