Datasets:
File size: 2,524 Bytes
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license: mit
task_categories:
- robotics
- time-series-forecasting
language:
- en
tags:
- robotics
- embedded-systems
- ultrasonic
- autonomous-robot
- PIC16F877A
pretty_name: Robot Sensor Telemetry Dataset
size_categories:
- n<1K
---
# Robot Sensor Telemetry Dataset
## Description
This dataset contains real-time sensor telemetry collected from an autonomous robot built for CIE-349/408 Embedded Systems at Zewail City University of Science and Technology (Spring 2026).
The robot uses a PIC16F877A microcontroller reading 4x HC-SR04 ultrasonic sensors at 250ms intervals. Telemetry is streamed over UART to an ESP32 NodeMCU, forwarded via UDP to a Raspberry Pi 3B, and served to a Flutter mobile app over HTTP.
## Dataset Structure
| Column | Type | Description |
|--------|------|-------------|
| timestamp_ms | int | Milliseconds since robot boot |
| front_cm | int | Front ultrasonic sensor distance (cm) |
| rear_cm | int | Rear ultrasonic sensor distance (cm) |
| left_cm | int | Left ultrasonic sensor distance (cm) |
| right_cm | int | Right ultrasonic sensor distance (cm) |
| motor_state | string | Current motor command: FORWARD/BACKWARD/TURN_LEFT/TURN_RIGHT/STOP/IDLE |
| face_verified | bool | Whether biometric face recognition lock is verified |
| tilt_warning | bool | MPU6050 tilt > 30 degrees detected |
| fall_detected | bool | MPU6050 tilt > 60 degrees detected |
## System Architecture
The robot operates as a 4-tier distributed pipeline:
1. **PIC16F877A** — Hard real-time controller, reads sensors via Timer1, drives motors via PWM
2. **ESP32 NodeMCU** — WiFi bridge, forwards UART telemetry to Raspberry Pi over UDP
3. **Raspberry Pi 3B** — Flask server, face recognition security gate, UDP auto-discovery
4. **Flutter Android App** — Mobile dashboard with D-pad control and radar display
## Face Recognition Security
Motor commands are blocked unless a verified face is detected by the `face_recognition` library (dlib-based deep learning model) running on the Raspberry Pi. Face encodings are stored persistently in a `.pkl` file (biometric database).
## Safety Features
- Software obstacle cutoff: front sensor < 10cm → force STOP
- Tilt/fall detection via MPU6050 accelerometer
- Biometric lock: commands blocked until face verified
## Team
- Nouran Essam (202300627)
- Menna Khaled (202301665)
- Shrooq Amin (202300112)
Zewail City University of Science and Technology — CIE-349/408 Spring 2026
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