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System Integration ​

Assignment ​

  • Design and document the system integration for your final project

System Integration Process Navigation ​

This is a record of the project production process, covering the complete process from design, processing, programming to testing. Click on any item below to jump to the corresponding detailed page:

Motivation ​

Modern vehicles are equipped with advanced autonomy and driver assistance, yet human physiological and emotional states remain critical to safe driving. This system integrates biometric data—including stress levels and mood —to dynamically assess the driver’s readiness for takeover. When elevated stress is detected, the system issues alerts like "High stress detected: relax and prepare for vehicle handover," or delays manual control to ensure the driver is calm before takeover. Integrating physiological awareness into driver monitoring not only improves takeover timing but also helps protect drivers from making unsafe decisions during critical handovers.

Idea Sketch ​

A stress and mood detection device designed for autonomous vehicles, capable of uploading data to the cloud and providing feedback to the user, enabling safer takeover decisions. By continuously analyzing emotional and stress signals, the system predicts driver readiness for manual control, offering proactive interventions and real-time guidance to ensure a smooth transition from autonomous to manual driving.

Design Sketch (for right and left sides):

Right Side: The right side of the illustration is divided into three key sections: the air vent-mounted holder, the dual-sided magnetic sensor module, and the smartphone. These components magnetically attach to each other, enabling modular assembly. The sensor device can magnetically attach to the phone for stress and mood detection even when the driver is holding the phone, ensuring continuous monitoring and adaptability between mounted and handheld use.

Left Side: The left side presents early-stage product sketches, iterating on the form factor and aesthetic of the monitoring device, blending ergonomic considerations with technical functionality.

This product consists of the following five components:

  • XIAO ESP32S3: Controls sensors for stress and mood detection.
  • Sodium-Selective Electrode: Measures salivary sodium levels to assess stress.
  • LED Lamp Beads: Visually indicate stress or mood levels.
  • Camera Module: Captures facial expressions for mood analysis.
  • ​​Wi-Fi:​​ Enables wireless data transmission between sensors and the IoT platform for real-time monitoring and visualization.

Project development Gantt chart ​

This Gantt chart outlines the project management timeline for the driver stress and mood monitoring device. It illustrates task progress across key phases, from CAD design and circuit development to 3D printing, PCB assembly, mechanical integration, functional verification, software tuning, and user experience optimization. The timeline highlights each task's duration, providing a clear visual roadmap to guide the development process from start to final validation and media production.

Project Tasks and Timeline Overview ​

The development of this driver stress and mood detection system is divided into two main stages, each focusing on different sensing strategies and hardware integration. Stage 1 centers on visual emotion recognition using a camera module, while Stage 2 expands the system's capability by incorporating a sodium ion biosensor for stress assessment and cross-verification. The system outputs include LED light feedback and an IoT-connected mobile interface for takeover strategy suggestions.

Stage 1: Visual Emotion Detection and System Framework (May 15 – June 5) ​

Step 1: Design & Preparation (May 15 – 21) ​

  • CAD Design: Designing sensor housings and the overall form factor using Fusion 360.

  • Circuit Design (PCB): Designing and simulating PCB layouts to support camera-based mood sensing and LED output indicators. /<image

Step 2: Fabrication (May 22 – 25) ​

  • 3D Printing: Printing PLA enclosures for housing the camera module, LEDs, and magnetic mounting hardware.

  • PCB Assembly: Soldering ESP32S3 breakout boards and verifying Wi-Fi data communication between modules.

Step 3: Assembly & Alpha Testing (May 26 – June 5) ​

  • Mechanical Integration: Magnetically assembling the device for easy mounting to the car’s air vent and aligning camera placement.

  • Functional Verification: Testing facial emotion detection, LED mood response, and Wi-Fi latency for transmitting takeover readiness alerts to mobile UI.

Stage 2: Biosensor Integration and Data Cross-Validation (June 5 – June 13) ​

Step 4: Biosensing & Sensor Calibration (June 3 – 7) ​

  • Sodium Ion Sensor Setup: Integrating a solid-state Na⁺ sensor for saliva-based stress monitoring.
  • Sensor Fusion: Cross-validating biosensor readings with camera-detected facial data to ensure reliable driver state estimation.

Step 5: Refinement & UX Optimization (June 7 – 10) ​

  • Software Enhancement: Refining facial recognition logic and implementing data fusion algorithms on the ESP32.

  • User Interface Tuning: Enhancing the output screen UI and mobile feedback interface to reflect stress severity and takeover recommendations.

Step 6: Final Validation & Media Production (June 10 – 13) ​

  • System Validation: Full-system testing with real inputs to simulate takeover conditions and evaluate output responses.

  • Demo & Documentation: Producing a short video demonstration and compiling final technical documentation for submission.

Material BOM List ​

NameQtnCost (in CNY)Vendors
Epoxy Resin127.00Taobao
Vehicle-mounted magnetic bracket114.70Taobao
430 magnetic conductive stainless iron plate25.88Taobao
Magsafe transmitter magnet112Taobao
32GB memory card125.9Taobao
3M adhesive patch magnet13.5Taobao
MAIXCAM camera module1244Taobao
xiao esp32s3150Taobao

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