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README.md

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+# FlowCast: Precision Forecasting of Passenger Flows and Public Transit Demand
+
+## Overview
+
+FlowCast is an advanced, scalable system designed to forecast passenger flows and public transportation demand using cutting-edge machine learning algorithms. By integrating historical data with real-time inputs, the system delivers high-precision predictions to enhance urban transit management. FlowCast is designed for smart cities, leveraging both on-premise and cloud-based infrastructures to optimize public transportation systems dynamically.
+
+## Features
+
+- **Advanced Algorithms**: Leverages a hybrid approach combining machine learning models (e.g., Random Forest, Neural Networks) for precise demand forecasting.
+- **Real-Time Data Integration**: Supports real-time data collection and analysis from various sources (e.g., sensors, ticketing systems).
+- **Scalability**: Architected to scale with increasing data volumes using modern microservices and cloud-native technologies.
+- **User Interface**: A frontend interface for visualizing predictions, trends, and insights for city planners and transport authorities.
+- **REST API**: Provides an API for real-time predictions, data input, and integration with external systems.