Week 3 - Sep 18 - 24
Below is the overall layout/ plan of the traffic predictor project
Module 1: Traffic prediction with machine learning on an added advantage of mass storage capability of the STM32 Nucleo-64 development board
|Nucleo L476RG board||Mbed Compiler/ VS Code|
|GPS sensor||GMaps API|
|Wi-Fi Expansion board||MATLAB & Arduino (Mobile Application)|
This holds the key functionality of the project. Data will be collected from user such as,
The collected data is machine learned to develop a pattern with time & traffic in a particular location. This will help users avoid traffic.
Module 2: Auto-pilot mode with predefined speed using Sensor Expansion board
Components: Module1's components +
|Sensor Expansion board|
While on traffic one would easily get bored up. Enabling an auto-pilot mode with a predefined speed from data collected & real-time feed will help one relax.
Module 3: Speed adjustment with correspondence to current vehicular movement and real-time traffic
Components: Module1, 2's components +
The real-time feed is obtained through calculating the position of other vehicles from our vehicle. This is used for adjusting the speed of the vehicle.