OffRoaders - Offroading Automobile Dashboard

figma: https://www.figma.com/proto/pDo1y1gL9sEjM5Ss5cfbjJ/Untitled?page-id=0%3A1&type=design&node-id=0-469&viewport=41%2C2743%2C0.29&t=jAF9OyLRz1E26iMg-1&scaling=min-zoom&starting-point-node-id=0%3A469&mode=design

The purpose of this project is to develop a dashboard application for an offroading vehicle that displays the vitals of the vehicle, provides a roll-over alert system, and incorporates a semi ADAS (Advanced Driver Assistance System) with an intelligent assistant. The application will be built using the Flutter framework and will communicate with an ESP32 microcontroller via IoT technology. Invasive sensors will be used to gather relevant data about the vehicle. The application will consist of three main screens: ADAS assistant, Panel, and Rollover Monitoring.

The primary goals of the dashboard application are as follows:

Display vital information about the offroading vehicle, including speed, RPM, engine temperature, fuel level, and battery voltage.

Provide a roll-over alert system that triggers an alarm and alerts the driver when the vehicle is at risk of rolling over.

Implement a semi ADAS with intelligent features such as lane departure warning, collision detection, and adaptive cruise control.

Create an intuitive user interface with three main screens: ADAS assistant, Panel, and Rollover Monitoring.

Establish communication between the dashboard application and the ESP32 microcontroller using IoT technology.

Utilize invasive sensors to collect accurate and reliable data about the vehicle's performance and environment.

The architecture of the dashboard application will involve the following components:

Flutter Framework: The application will be developed using the Flutter framework, which provides a rich set of UI components and cross-platform compatibility.

ESP32 Microcontroller: The ESP32 will serve as the IoT gateway, responsible for collecting data from invasive sensors and communicating with the dashboard application.

Invasive Sensors: Various sensors will be used to gather data, including speed sensor, accelerometer, gyroscope, GPS module, and temperature sensor.

IoT Communication: The ESP32 will use wireless communication protocols such as Wi-Fi or Bluetooth to establish a connection with the dashboard application.

ADAS Algorithms: The intelligent features of the ADAS assistant, such as lane departure warning, collision detection, and adaptive cruise control, will be implemented using machine learning and computer vision algorithms.

The dashboard application will consist of three main screens:

The ADAS Assistant screen will provide intelligent assistance to the driver during offroading. It will include the following features:

Lane Departure Warning: This feature will detect if the vehicle is deviating from its lane and provide an audible and visual warning to the driver.

Collision Detection: The system will use sensors to detect potential collisions and alert the driver accordingly.

Adaptive Cruise Control: This feature will automatically adjust the vehicle's speed to maintain a safe distance from the vehicle ahead.

The Panel screen will display vital information about the vehicle, including:

Speed: The current speed of the vehicle.

RPM: The revolutions per minute of the engine.

Engine Temperature: The temperature of the engine.

Fuel Level: The amount of fuel remaining in the vehicle.

Battery Voltage: The voltage level of the vehicle's battery.

The Rollover Monitoring screen will continuously monitor the vehicle's roll angle and trigger an alarm if the vehicle is at risk of rolling over. It will include the following features:

Roll Angle Display: A real-time visualization of the vehicle's roll angle.

Roll-over Alert: An audible and visual alarm to alert the driver in case of a potential roll-over situation.

The implementation of the project will involve the following steps:

Setup Flutter Environment: Install and configure the Flutter development environment on the development machine.

Design User Interface: Design the user interface screens for ADAS Assistant, Panel, and Rollover Monitoring using Flutter widgets.

Implement IoT Communication: Develop the necessary code on the ESP32 microcontroller to establish communication with the dashboard application using Wi-Fi or Bluetooth.

Integrate Invasive Sensors: Connect and calibrate the invasive sensors, including the speed sensor, accelerometer, gyroscope, GPS module, and temperature sensor, with the ESP32 microcontroller.

Data Processing: Implement algorithms on the ESP32 to process the sensor data and extract relevant information such as speed, RPM, engine temperature, etc.

Implement ADAS Algorithms: Develop the required machine learning and computer vision algorithms for the ADAS Assistant features such as lane departure warning, collision detection, and adaptive cruise control.

Integrate IoT and ADAS: Establish communication between the ESP32 microcontroller and the ADAS Assistant screen to enable real-time interaction.

Test and Debug: Perform extensive testing and debugging to ensure the proper functionality of the dashboard application, IoT communication, sensor integration, and ADAS features.

Deployment: Deploy the dashboard application on the target device and ensure its compatibility and usability in an offroading vehicle environment.

The dashboard application for the offroading vehicle will provide crucial information to the driver, incorporate intelligent ADAS features, and ensure driver safety. By utilizing the Flutter framework, IoT technology, invasive sensors, and intelligent algorithms, the application will enhance the offroading experience and contribute to a safer and more informed driving experience.