Globally, intelligent transportation systems utilize traffic predictions. Traffic congestion, route planning, and vehicle dispatching all benefit from accurate traffic forecasts. The road system’s ...

How to Build an Arduino-Based Solar Power Prediction System Using Python & Machine Learning, Part 1 Learn how to build, collect, and analyze real-time data using a low-cost data acquisition device ...

Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries). - aprbw/traffic_prediction ...

By integrating LoRa technology with distributed machine learning, the network connectivity of green intelligent transportation systems can be optimized.

Intrusion-Detection-System-Using-Machine-Learning This repository contains the code for the project "IDS-ML: Intrusion Detection System Development Using Machine Learning". The code and proposed ...

Background Past work has extensively explored the integration of machine learning (ML) and deep learning (DL) in intelligent transportation systems (ITS), focusing on traffic-flow prediction ...

Using machine learning algorithms, the system can detect and track moving cars during normal traffic flow and pinpoint anomalies like congestion, accidents, or pedestrians on the road. He believes ...