Development of smart visualisation platform for traffic management

Abstract

The necessity of autonomous environmental service vehicles in today's fast-paced, ever-evolving urban landscape cannot be overstated. With increasing urbanization and population growth, the demand for efficient and sustainable waste management and road cleanliness solutions is at an all-time high. Traditional manual methods are often labour-intensive, time-consuming, and prone to human error, making them less than ideal in addressing these challenges.

This report presents the development and implementation of a smart visualization platform for autonomous environmental service vehicles designed to monitor and manage road cleanliness efficiently. The importance of maintaining clean streets and urban environments has been widely acknowledged, with the adoption of autonomous vehicles emerging as a viable solution to improve the efficiency of this process. However, there is a need for effective monitoring and control systems to ensure the optimal performance of these autonomous vehicles in real-world settings.

To address this gap, we propose a smart visualization platform that leverages cutting-edge technologies such as React, Flask, Kafka, MongoDB, and MySQL to create a comprehensive and user-friendly monitoring system. The platform enables the real-time tracking of vehicle status, location, and performance metrics, as well as the assessment of road cleanliness based on collected data.