Aido Robot: Sensor Hub and Data Fusion (Simulated)

⚠️ Disclaimer: This is a simulated project developed for educational and demonstration purposes. It is not an actual implementation of the Aido Robot hardware but is intended to showcase the core logic, design architecture, and data fusion principles used in a sensor hub system.

📌 Project Overview

This project simulates the working of a Sensor Hub and Data Fusion System for the Aido Robot — a multi-sensor, intelligent companion robot. It models how various environmental and proximity sensors can be integrated with intelligent data polling, logging, and air quality assessment.

🔧 Technologies Used

• STM32 Blue Pill (STM32F103C6) microcontroller
• Proteus for simulation
• STM32CubeIDE for embedded development
• C (Bare-metal) programming
• External .c/.h module structure

🧠 Key Features

• ✅ Adaptive Sensor Polling based on environmental triggers and thresholds
• ✅ Sensor Power Management using GPIO control to reduce energy consumption
• ✅ Structured Sensor Representation via sensor_t struct for modular design
• ✅ Data Logging with FIFO buffer mechanism for temporary storage
• ✅ Advanced AQI Calculation using pollutant concentration data
• ✅ Sleep/Stand-by Modes to improve overall system efficiency
• ✅ Integration with IR and Ultrasonic Sensors for obstacle detection
• ✅ Modular Codebase structured for scalability and hardware independence

📈 Sensors Simulated

Sensor	Type	Functionality	Polling	Logging
DHT22	Temp & Humidity	Adaptive polling, comfort zone logic	✅	✅
MQ135	Gas Sensor (CO, etc)	Adaptive on fluctuations	✅	✅
BME688	Env. Sensor (Gas, Pressure, Temp, Humidity)	Adaptive	✅	✅
Ultrasonic	Distance	Continuous object detection	✅	❌
IR Sensor	Obstacle detection	Continuous sensing	✅	❌

📊 Air Quality Index (AQI)

AQI is calculated using individual pollutant indexes based on the following formula: $$ I=\frac{(Ihigh​−Ilow​)}{(Chigh​−Clow​)}​×(C−Clow​)+Ilow​ $$ 𝐼 : AQI value
𝐶 : Pollutant concentration
𝐶𝑙𝑜𝑤 , 𝐶ℎ𝑖𝑔ℎ ​ : Concentration range
𝐼𝑙𝑜𝑤 , 𝐼ℎ𝑖𝑔ℎ ​ : AQI range for that concentration

• Based on 24-hour averages for PM2.5
• Based on 8-hour averages for CO, NO2, etc.
• Overall AQI determined by the highest individual AQI

📚 Project Structure

|-- Core/
    |
    ├── src/ 
    │ ├── main.c 
    │ ├── sensor_logger.c
    │ ├── aqi.c
    | |-- DHT22.c
    |
    ├── inc/ 
    │ ├── main.h 
    │ ├── sensor_logger.h
    │ ├── aqi.h
    | |-- DHT22.h
    ├── README.md 

|--- Debug/
    |
    |-- Aido SensorHub.hex 

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📷 Circuit Diagram

Proteus-based schematic showing STM32 Blue Pill and connected sensors.

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🔁 System Flow Chart

A high-level flow diagram of sensor polling, data logging, and AQI processing.

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⚙️ Pin Configuration

GPIO pin mapping of each sensor and peripherals to the STM32 controller.

📂 DHT22 GitHub Repository

Used the external Library for Dht22 from "MrHause":
👉 GitHub Link

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📌 Future Scope

• Real hardware deployment and calibration
• Integration with machine learning models for predictive analytics
• Live AQI display and data cloud sync

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🛠️ Feel free to fork, study, and build upon this simulation.
📩 Contributions and suggestions are always welcome!