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Public Transport Management with Metrici AI

Video analytics, DNN (Deep Neural Networks), AI training, LPR (License Plate Recognition), Line Counter, and Area Counter technologies can greatly enhance public transport systems in cities by improving efficiency, safety, and data-driven decision-making. Here�s how these technologies can be applied:

Traffic Flow Management and Monitoring

LPR for Vehicle Identification:

Track and monitor buses, taxis, or other public transport vehicles in real time.

Identify unauthorized vehicles in dedicated bus lanes or restricted areas.

Inform users about next arrival

Line Counter

Monitor how many vehicles (buses, trams, etc.) cross specific points, such as bus stops or intersections, ensuring schedules are adhered to.

Track congestion in busy areas or intersections to optimize traffic light systems or reroute vehicles.

Area Counter:

Count the number of public transport vehicles or pedestrians within bus stations, terminals, or major transport hubs to ensure smooth operations and safety during peak hours.

Passenger Counting and Flow Optimization

Line Counter for Passengers:

Count passengers boarding and alighting buses, trams, or metro trains at each stop.

Use this data to analyze peak travel times, optimize routes, and schedule services more efficiently.

Area Counter for Crowded Spaces:

Monitor crowd density in bus terminals, metro stations, and waiting areas to prevent overcrowding and improve passenger safety.

Trigger alerts when capacity is exceeded, allowing staff to respond quickly during emergencies or high-traffic events.

Custom DNN Training for Object Recognition:

Recognize and classify passengers, luggage, or mobility aids (e.g., wheelchairs), and automate processes like priority boarding or assistance for disabled passengers.

Safety and Security

AI: Abandoned or suspicious

Detect abandoned objects or suspicious behavior in metro stations, bus terminals, and other public transport areas to prevent security incidents.

Monitor restricted or dangerous areas (e.g., metro tracks) and trigger alerts if people or objects are detected in those zones.

Line Counter for Restricted Areas

Count unauthorized crossings in restricted areas, such as maintenance zones or emergency exits, to ensure public safety.

Identify vehicles or individuals that cross into restricted zones, automatically generating reports or triggering alarms.

AI Training for Anomaly Detection:

Use AI models trained to recognize unusual behaviors, such as loitering or people moving in the wrong direction in transport hubs, to enhance security and prevent accidents.

Optimizing Public Transport Efficiency

Real-Time Vehicle Tracking with LPR

Monitor the movement of public transport vehicles in real time to ensure timeliness, reroute vehicles when necessary, or provide updates to passengers.

Passenger Flow Management

Use passenger counting data from Line Counter and Area Counter to adjust bus, tram or train frequency in real-time, ensuring sufficient transport is available during peak hours.

Predictive Maintenance and Fleet Management:

Integrate AI models to monitor vehicle conditions and detect potential issues before they result in breakdowns, ensuring reliable and uninterrupted service.

Parking and Access Control for Public Transport Vehicles

LPR for Bus Depots and Parking:

Manage bus depots by using LPR to control access, monitor parking spot occupation, and streamline fleet parking.

Ensure that only authorized buses or transport vehicles enter or exit designated areas.

Parking Spot Occupation Monitoring:

Detect available parking spots at bus terminals or transport hubs and guide drivers to vacant spots, reducing waiting times and improving parking efficiency.

Data-Driven Decision Making

AI and DNN for Predictive Analytics:

Analyze patterns from historical and real-time data to predict future transport demands and optimize schedules, routes, and resources accordingly.

Custom DNN Models for Passenger Preferences:

Train AI models to recognize patterns in passenger behavior, such as popular travel times, most-used routes, and preferred transportation methods, allowing transport authorities to improve service and customer satisfaction.

Event and Emergency Management

Crowd Monitoring with Area Counter and DNN:

During large events or emergencies, monitor crowd movement and density in transport hubs, ensuring efficient evacuation or management of large groups of people.

Line Counter for Emergency Exits:

Track the number of people crossing emergency exit lines to ensure safety and prevent overcrowding during evacuations.

Conclusion By integrating video analytics, AI, DNN, LPR, Line Counter, and Area Counter into public transport systems, cities can significantly enhance transport efficiency, passenger safety, and overall system management. These technologies allow real-time monitoring, predictive analysis, and automated processes, leading to smarter, more efficient public transportation networks.

Intensiva United is a Bucharest-based company, founded in 2010. Metrici is our brand name for advanced video analytics solutions, an answer to people and companies needs. Our passion for technology and expertise in computer vision are used by the best partners for making a better place to live in, a safer and smarter city. Metrici has one the widest range of applications based on video analytics and AI technologies so it positioned itself as one of the best companies in the world. Be assured that every edition of our software proposals is always the strongest developed till present as Metrici keeps innovating in accurate recognition.

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+4031 405 69 20

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