Week 8 - Oct 23 - 29


It's almost time to hit the traffic. This blog will cover up the development of login and registration screens, API and integration of the same in the mobile app. Going through my previous blog Traffic Predictor #7 - Into the traffic [Part 2 of 2]  will help in understanding the progress better. Especially the App (Android) part.

Module 1 - Traffic prediction with machine learning

APP (Android)


  • Login Screen

          The home screen will act as the login screen [shown below]. It consists of "username" and "password" fields along with "Login" button and "Register Here" link at the bottom. After successful login a personalized user page will be displayed [shown test version below the login screen], else an alert message would pop up to try again.

App Login Screen

App User Screen

  • Registration Screen

          The registration screen is for registering new users once they fill the "username", "password", "gender" and "country" fields and click "Register" button. On successful registration the user will be redirected to login page, else an alert will be shown to try with another username or simply to try again.

App Registration Page

  • API

          API are "Application Program Interface" are like access keys to already developed software. Mostly these will function like giving inputs and obtaining desired outputs from the API.


               For example, GMaps API.


          In the android app, when the login/ registration button is pressed by the user the data will be converted into JSON object [JSON is a standardized string format].


               For instance, lets consider from the login screen the below JSON contents are passed.


                               username: Dixon124;

                               password: Test;



          This data will be given to Login API which will read the username verify it in the database and then decrypt the stored password to compare it with the JSON input password. Then this will allow user to login. A similar process is followed in Registration API. In this project APIs are written in PHP language.


          The main motive of creating a user login screen for traffic predictor project is to obtain user specific location data for machine learning. This will enable easier classification of data when compared to raw location data from route A to B.



IoT expansion board:


For the purpose of connecting the Nucleo-L476RG board with user mobile through BT Wi-Fi I have made the below shield expansion board BT connection is achieved through HC-05 bluetooth transceiver and Wi-Fi connection is achieved through ESP8266 Wi-Fi transceiver module

custom shield

Progress made so far,

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||   55%

{tabbedtable} Tab LabelTab Content
Entry & Introduction

IoT on Wheels Design Challenge - Traffic predictor and auto pilot mode

Traffic Predictor #1 - The Official Announcement

PlanTraffic Predictor #3 - The Plan
Initial Setup

Traffic Predictor #2 - Quest for the Code Editor

Traffic Predictor #4 - Finally, the kit arrives

Module 1

Traffic Predictor #5 - Machine Learning and Building a case for the kit

Traffic Predictor #6 - Into the traffic [Part 1 of 2]

Traffic Predictor #7 - Into the traffic [Part 2 of 2]

Module 2

Yet to Begin

Module 3Yet to Begin
IntegrationYet to Begin