IoT Based Vehicle Parking Model with Mobile Apps Software

Abstract

In this 21st century, the progression of the modern world has come to the age of revolution industry 4.0. Almost every technology are coping with IoT concept to provide ease to humanity. Although the progression of technology is skyrocketing, it also increases the population of humanity. With this, the community require a more efficient way in managing parking hunting constraint that causes by population increase. This project purpose is to eradicate the burden for parking hunting for train user community using IoT concept. The Mobile app software design to retrieve and sent data of the current number of parking in the parking spot. A model of parking spaces builds with an Arduino Mega and 4 IR proximity sensor 12224 at the parking spot, representing 4 parking slots. The data received have been sent to the cloud database to be retrieved from mobile app software through Arduino Wi-Fi module ESP8266. For the mobile app-software programming, it has been built using Python, where it will be implemented on 2 platforms Jupyter and PyCharm. The best platform will be chosen as the platform to develop mobile app software. The package to develop this software was used KiVy and KiVyMd, which can be coded in Python programing language. For cloud databases, Amazon Web Service (AWS) and Google Firebase were used to store parking spot data and user login data, respectively. Both software and hardware have been tested in sync at the prototype testing phase to check the data obtain accuracy and the mobile app-software performance index.