Paper Contents
Abstract
RoadSense An AI driven traffic prediction application leverages artificial intelligence and machine learning to provide accurate,real-time traffic forecasts, offering a powerful tool for urban traffic management and planning. By utilizing data from various sourcesincludingsensors, GPS data, historical records, and external inputs like social media and event schedulesthe application predicts traffic patterns, volume,and speed with high accuracy. Through advanced models such as Long Short-Term Memory (LSTM) networks and Graph Neural Networks(GNNs), it effectively captures both temporal and spatial dynamics of urban traffic. The web-based interface provides a user-friendly dashboardfor visualizing current and forecasted traffic conditions, allowing traffic managers, urban planners, and commuters to make informed decisions.
Copyright
Copyright © 2024 R. Swetha Sri. This is an open access article distributed under the Creative Commons Attribution License.
