Smart Transport Passenger Traffic Monitoring and Analytics Platform

The client faces difficulties in accurately measuring passenger traffic density and flow between different areas, including peak times and crowded locations. This hampers effective route optimization, scheduling, and resource allocation. They lack a comprehensive, low-cost solution to gather real-time traffic and passenger engagement data from smartphones and transit vehicle signals.

A municipal transportation authority or transit provider seeking to optimize route planning, bus stops, and scheduling through passenger traffic analytics.

• Implement a scalable platform to monitor and analyze passenger traffic density across urban transit routes.
• Enable real-time data collection from smartphone signals via WiFi and Bluetooth, as well as vehicle-based signal receivers.
• Utilize spatial databases to evaluate passenger flow patterns in specific areas, times, and bus lines.
• Develop customizable interfaces for data visualization and decision-making dashboards.
• Ensure the solution is accessible across various devices and integrates with external transit management systems.
• Achieve low infrastructure costs while maintaining high measurement accuracy.

• Signal capture from WiFi and Bluetooth for Android and iOS devices within transit environments.
• Deployment of small devices on vehicles to receive and analyze passenger signals.
• Real-time data ingestion and processing pipeline with spatial database support for geographic-specific analytics.
• Customizable analytical dashboards with filters for date, time, day, and transit line parameters.
• Device parameter management console for monitoring and control of signal receivers.
• Integration interfaces for external transit management systems and open WLAN devices.

• External transit route management and scheduling systems.
• Open WLAN device management systems.
• Data visualization and analytics dashboards.
• Device parameter control interfaces.

• High scalability to support city-wide deployment of multiple devices.
• Low-latency data processing and real-time analytics.
• Robust security measures for data privacy and system access.
• High availability and reliability to ensure continuous data collection.
• Cost-effective infrastructure setup to minimize investment expenses.

The proposed system is expected to significantly improve the accuracy of passenger traffic data, enabling the client to optimize bus routes, stops, and schedules with greater precision. This will enhance operational efficiency, reduce congestion, and improve passenger service quality. The solution's scalability and low-cost infrastructure will facilitate large-scale deployment, with the potential for city-wide analytics and smarter transit planning, ultimately leading to more informed decision-making and resource allocation.