Welcome to NAVYA, a futuristic embedded system that blends vision, voice, and environmental awareness to enhance driving safety and user interaction in smart vehicles.
NAVYA transforms conventional car systems by integrating:
- Blind spot detection & Real-time Camera mirroring via side cameras
- Ambient light signaling for object proximity
- Voice-activated assistant
Made for AOSP (Android Open Source Project) platforms — designed with embedded innovation in mind.
A smart enhancement for traditional side mirrors.
- Side Camera Integration: Mirrors are enhanced with high-definition side-mounted cameras.
- Real-Time Object Detection:
- Uses computer vision to detect nearby vehicles or obstacles in blind spots.
- Draws a green circular safety indicator on the display when an object is too far.
- Draws a yellow circular warning indicator on the display when an object is too closer.
- Draws a red circular warning indicator on the display when an object is too close indicate there are a danger.
- On-Screen Feedback: Drivers get intuitive visual alerts, reducing the chance of missing threats.
Because your eyes shouldn't be the only way to sense danger.
- LED Ambient Lighting Strip embedded near the display or window frame.
- Context-Aware Color:
- Default: Cool ambient tones.
- Red Warning Glow: When an object approaches dangerously close, the ambient light turns red to give a clear visual cue even in peripheral vision.
- Perfect for low-visibility or high-speed driving conditions.
Mirrors are outdated. Live digital vision is here.
- Screen Mirroring of the side cameras.
- Built using Android’s SurfaceView or CameraX for efficient, low-latency rendering.
- Seamless integration with AOSP UI layers.
Your car listens, understands, and talks back.
- Wake Word Detection: Say
"HiCar"to activate the assistant. - Voice Response:
- Assistant greets back with
"Hi, [User]".
- Assistant greets back with
- Built using Android's Vosk API and Text-to-Speech (TTS) engine.
- Potential for extended functionality: Navigation, weather updates, or media control.
- Android Open Source Project (AOSP)
- TensorFlow Lite – for real-time object detection
- CameraX / SurfaceView – for rendering side camera feeds
- Android Vosk / TTS – for voice commands and replies
- HAL + GPIO Control – for LED hardware integration
- VHAL (Vehicle HAL)
- SELinux – to enforce security policies on camera/light access
NAVYA/
│
├── app/
├── camera/
├── voice_assistant/
├── ambient_light/
├── hardware/
└── sepolicy/
- Abdallah Salah Mohammed
- Aliaa Ahmed Mortada
- Mostafa Mohammed Mohammed
- Mousa Mahmoud Salah
- Youssef Mostafa Mohammed
- AOSP Project Team – Embedded Systems & Android Automotive Engineers
- SOME/IP Communication for supporting Two-Cameras
- Send SOS message when crash happened
- Bare-Metal Programming and CAN Bus Protocol and simulate turn signal
- Gesture controls for touchless interaction
- Companion mobile app for status and control
| ID | Requirement Description |
|---|---|
| SRS-FUNC-001 | The system shall detect objects in the blind spot using side-mounted cameras and computer vision. |
| SRS-FUNC-002 | The system shall display visual safety indicators (Green/Yellow/Red) based on object proximity. |
| SRS-FUNC-003 | The system shall mirror the side camera feeds on the digital display in real time. |
| SRS-FUNC-004 | The system shall provide ambient light warnings using an LED strip based on object proximity. |
| SRS-FUNC-005 | The system shall activate the voice assistant via a wake word ("HiCar"). |
| SRS-FUNC-006 | The voice assistant shall respond using TTS and perform limited interactions like greeting the user. |
| SRS-FUNC-007 | The system shall enforce security access to camera and LED using SELinux. |
| ID | Requirement Description |
|---|---|
| SWRS-FUNC-001 | App shall run as a privileged system app in AOSP and use SurfaceView or CameraX for camera feed. |
| SWRS-FUNC-002 | TensorFlow Lite shall be used for object detection in real-time on camera frames. |
| SWRS-FUNC-003 | Vosk API shall be used to detect wake word and speech-to-text conversion. |
| SWRS-FUNC-004 | Android TTS engine shall be used to reply back to the user. |
| SWRS-FUNC-005 | App shall control the GPIO-based LED strip using HAL or JNI interface. |
| SWRS-FUNC-006 | SELinux policies shall restrict access to camera and GPIO control to the NAVYA system app only. |
| SWRS-FUNC-007 | App shall draw proximity circles using Android Canvas or OpenGL overlay. |
NAVYA aims to redefine the driver experience by combining safety, intelligence, and interaction — built fully on embedded Android technologies.