AI-Powered Fare Evasion Detection
Fare evasion is a persistent challenge for public transport operators, leading to significant revenue losses and unfair conditions for paying passengers.
Incoresoft Fare Evasion Detection uses advanced AI video analytics to automatically identify fare evasion incidents in real time — enabling targeted enforcement, data-driven decisions, and sustainable revenue protection.
What Is Fare Evasion Detection?
Fare evasion detection is an AI-based video analytics solution designed to identify passengers who access transport services without valid tickets.
The system analyzes video streams from existing cameras to detect behaviors such as:
- Tailgating behind paying passengers
- Jumping or bypassing turnstiles
- Ducking under barriers
- Unauthorized entry through restricted zones
By detecting these actions automatically, transit authorities can move from random inspections to smart, evidence-based enforcement.
How Incoresoft Fare Evasion Detection Works
The solution combines computer vision, behavioral analysis, and real-time event processing to monitor fare control zones continuously.
Core Workflow
- Video streams are captured from CCTV cameras installed near gates, turnstiles, or access points
- AI models analyze passenger movement and behavior in real time
- Fare evasion events are detected and classified
- Alerts, snapshots, or video clips are generated for operators
- All events are stored for analytics, reporting, and audits
The system works without disrupting passenger flow or requiring additional hardware at every entry point.
Key Features
AI-Based Behavioral Detection
Detects multiple fare evasion scenarios using deep learning models trained on real-world transit environments.
Real-Time Alerts
Instant notifications with visual evidence allow staff to respond immediately or review incidents later.
High Accuracy in Crowded Environments
Designed to operate reliably in peak hours, dense passenger flows, and complex station layouts.
Flexible Deployment
- On-premises
- Edge-based
- Hybrid or cloud-integrated
Advanced Analytics Dashboard
- Number of fare evasion incidents
- Peak times and locations
- Trends by station, gate, or route
- Effectiveness of enforcement actions
Benefits for Transit Operators
Real-time fare evasion detection
Automatically identifies tailgating, turnstile jumping, barrier bypassing, and unauthorized boarding in live video streams.
Cross-zone passenger tracking
Follows passenger movement across gates, platforms, and access points to confirm evasion patterns and reduce false positives.
Smart incident search & analytics
Instantly locate evasion events by time, station, gate, or behavior type — enabling faster review, reporting, and enforcement decisions.
- 01 Detect and classify common fare evasion behaviors in real time (tailgating, turnstile jumping, barrier bypass)
- 02 Monitor fare control zones continuously using existing CCTV near gates, turnstiles, and access points
- 03 Configure custom zones, lines, and rules to match each station layout and enforcement policy
- 04 Generate instant alerts with visual evidence (snapshots or video clips) for operator review
- 05 Reduce false alarms with adaptive logic tuned for crowds, peak hours, and complex passenger flow
- 06 Search incidents by time, station, gate, direction, and behavior type to speed up investigations
- 07 Store events for analytics, reporting, and audits — building a measurable picture of revenue leakage
- 08 Support evidence-based enforcement by highlighting hotspots, peak times, and recurring patterns
- 09 Deploy flexibly (on-premises, edge, or hybrid) without adding hardware at every entry point
- 10 Maintain privacy with configurable anonymization and no biometric identification by default
Benefits for transit operators
Reduce Revenue Loss
Detect fare evasion consistently and systematically instead of relying on random inspections.
Improve Operational Efficiency
Deploy inspectors only where data shows real issues — saving time and resources.
Maintain Passenger Flow
No need for additional physical barriers or intrusive checks.
Ensure Fairness
Protect paying passengers and promote equal access rules.
Data-Driven Decisions
Use real metrics to justify investments, staffing, and policy changes.
How Incoresoft Fare Evasion Detection Works
01
Monitor Continuously: The solution combines computer vision, behavioral analysis, and real-time event processing to continuously monitor fare control zones.
02
Capture Video Streams: CCTV cameras installed near gates, turnstiles, or access points provide live video feeds to the system.
03
Analyze Passenger Behavior: AI models process video streams in real time, analyzing passenger movement and behavior patterns.
04
Detect and Classify Events: Fare evasion actions such as tailgating or bypassing barriers are automatically detected and classified.
05
Generate Alerts and Evidence: When predefined conditions are met, the system generates alerts, snapshots, or video clips for operators.
06
Store and Report: All detected events are securely stored for analytics, reporting, performance tracking, and audit purposes.
Use Cases of Fare Evasion Detection
Metro & Rail Systems
Monitors turnstiles, open gates, and station entry points to detect fare evasion in high-traffic environments.
Bus & BRT Networks
Detects unauthorized boarding through front or rear doors, even in mixed-access and high-volume scenarios.
Light Rail & Trams
Identifies fare evasion on open platforms without physical barriers, maintaining smooth passenger flow.
Transit Hubs & Interchanges
Covers complex passenger movements across multiple access zones with centralized monitoring and analytics.
Fare Evasion Detection vs Traditional Methods
Traditional Inspections |
Incoresoft AI Detection |
|---|---|
|
Random checks |
Continuous monitoring |
|
Labor-intensive |
Automated detection |
|
Limited coverage |
Full-time visibility |
|
Reactive enforcement |
Proactive prevention |
|
No analytics |
Actionable insights |
Applications of Fare Evasion Video AI Solution
Privacy & Compliance
The system is designed with privacy and regulatory compliance in mind:
- No biometric identification by default
- Configurable anonymization options
- Compliance with GDPR and local data protection regulations
Why Incoresoft
Proven Computer Vision Expertise
Incoresoft specializes in AI-driven video analytics, computer vision, and intelligent monitoring systems for real-world environments.
Custom-Tailored Solutions
We adapt detection logic, alert rules, and dashboards to your infrastructure, passenger behavior, and enforcement policies.
Seamless Integration
Easily integrates with:
- Existing CCTV systems
- Transport management platforms
- Security and incident management software
- Data analytics tools
Scalable Architecture
From a single station pilot to city-wide deployments.
Frequently Asked Questions
Fare evasion detection is an AI-based video analytics solution that identifies passengers accessing public transport without a valid ticket. It automatically detects behaviors such as tailgating, gate jumping, or bypassing fare control zones using existing CCTV cameras.
No. The solution works with existing CCTV infrastructure. In some cases, additional cameras may be recommended to improve coverage, but no specialized fare gates or sensors are required.
The system is trained on real-world public transport scenarios and performs reliably in crowded environments, peak hours, and varying lighting conditions. Detection accuracy can be further optimized during deployment and tuning.
Yes. Fare evasion detection is especially effective in open stations and barrier-free environments where traditional turnstiles are not available or practical.
No biometric identification is used by default. The system focuses on detecting behavior, not identifying passengers, and can be configured with anonymization options to comply with privacy regulations
Detected incidents can trigger real-time alerts with snapshots or video clips and are stored in an analytics dashboard for review, reporting, and audit purposes.
Yes. The platform supports integrations with transport management systems, ticketing platforms, security software, and third-party analytics tools via APIs.
Absolutely. It can be deployed at a single station or scaled across an entire city or transport network with centralized management.