Architecture and Mechanism of mymetro

Data Collection and Processing:

• Data Sources: Integration with APIs of transportation companies, IoT sensors, weather services, and other external sources.

• ETL Processes: Extraction, Transformation, and Loading of data into a centralized repository for further analysis.

AI and Machine Learning:

• Predictive Models: Utilization of regression models and neural networks to forecast congestion and delays.

• Dynamic Route Optimization: Application of machine learning algorithms to update routes in real-time based on current data.

Route Optimization:

• Routing Algorithms: Implementation of algorithms to find optimal routes considering multiple factors (travel time, congestion, weather conditions).

• Personalization: Customization of routes based on individual user preferences, such as minimizing transfers or selecting less congested routes.