Machine Learning and IoT based Real Time Parking System: Challenges and Implementation

Abstract

There is a tremendous increase in number of vehicles in last two decades. So, it becomes important to make effective use of technology to enable hassle free parking at public and/or private places. In traditional parking systems, drivers face difficulty in finding available parking slots. These systems ignore the fact of parking the vehicles on roads, time management in peak hours, wrong parking of a vehicle in a parking slot. Moreover, the traditional systems require more human intervention in a parking zone. To deal with above said issues, there is an urgent requirement of developing Smart Parking Systems. In this manuscript, the authors propose a Smart Parking System based on IoT and Machine learning techniques to answer the real time management of parking and uncertainties. The proposed solution utilizes smart sensors, cloud computing and cyber physical system. Development of graphical user interface for administrator and end-user is a major challenge as it requires to ensure smooth monitoring, control and security of parking system. Moreover, it needs to establish effortless coordination with an end-user. The proposed system is successful in smartly addressing the challenges such as indicating status of parking slot well in advance to end-user, use of reserved and unreserved parking slots, wrong parking, unauthorized parking, real time analysis of free and occupied slots, detecting multiple objects in a parking slot such as bike in car slot, fault detection in one or more components and traffic management during peak hours. The system minimizes the human intervention and saves time, money and energy.