SMART TRAFFIC CROSSING AND ADVANCE PARKING MANAGEMENT SYSTEM USING IOT

Abstract

IoT and AI are in the greatest demand these days and are likely to have the dominant future. Smart cities are being demanded more and more, and IoT is one of the major facilitators towards making this vision a reality. IoT is being heavily developed so that efficient urban infrastructure can be built. Cities are plagued with several issues, such as inadequate parking area, risk of transport, and constant traffic jams. The tempo of contemporary life requires easy and efficient transport, which the present infrastructure cannot supply. Passengers are thus compelled to suffer from extended delays caused by traffic congestion even when traveling solo, which equates to excessive fuel usage and time wastage. Parking has also emerged as an issue of utmost concern for the majority of automobile owners. In response to these problems, we introduce an IoT solution. The thesis outlines an algorithm that will decongest traffic and improve the parking system. This entails a license number plate (LNP) recognition algorithm based on grayscale image processing and morphological operations for optimal identification. We also incorporate cutting-edge IoT sensor technology and AI, in the shape of a fuzzy logic system, to regulate traffic. Cars are regulated in time slots to facilitate smooth traffic. Our system also includes a cloud-based smart parking system that identifies empty spaces through IoT modules. We can now integrate AI-driven methods to track over-speed as traffic speed, road accidents, and automated emergency reporting on traffic. Data protection and security initiatives further render our IoT-based platform a deserving vehicle for intelligent traffic control and parking in modern urban environments.