

Add a real-time occupancy layer to every parking space with Vision AI for parking occupancy. Built for the operations where one missed space-level count on a busy event day, undetected ADA violation blocking an accessible spot, missed overstay in a paid zone, or wayfinding gap steering drivers to a full deck can mean lost revenue, ADA complaint exposure, a public trust erosion event that ends in a city council review, or a driver experience failure that pushes users to a competing app. Whether you're powering a city-wide smart parking dashboard, a private garage revenue optimization system, an event venue wayfinding app, an EV charging station availability feed, or a mobility startup's occupancy API, Roboflow extends space-level detection to every parking space in view of a camera, on the security cameras and pole-mounted overheads your operation already runs.
Real-Time Space-Level Detection:
Enforcement, Compliance, and Revenue:
Analytics, Planning, and Product Integration:
Bring intelligence to every parking space today. Stop occupancy blind spots from becoming lost revenue, ADA violations, wayfinding failures, or enforcement gaps.
What is parking occupancy AI?
Parking occupancy AI uses computer vision to detect vehicles and count empty and occupied spaces in real time from overhead cameras, pole-mounted CCTV, garage entrance cams, drone survey footage, and mobile scanners. The system classifies space state (empty, occupied, reserved, ADA accessible, EV charging), tracks vehicles from entry to exit, computes dwell time and overstay indicators, and feeds occupancy to wayfinding signage, mobile parking apps, dynamic pricing engines, and city dashboards over standard APIs. Smart cities, private garage operators (SP+, LAZ Parking, Standard Parking), airport parking, university and hospital parking, event venues, and mobility startups use it to lift utilization, capture missed enforcement revenue, verify ADA compliance, and power white-label parking apps.
Can Vision AI detect occupancy accurately at scale across mixed camera angles and lighting conditions?
Yes. Occupancy detection across a real parking lot is a hard multi-condition problem — camera angles vary by pole height and roof mount, lighting swings from full sun to shadow to overnight IR, vehicles range from compact to oversized truck, weather adds rain glare and snow cover, and the same lot needs to detect ADA, EV, and reserved-spot violations from a single feed. Roboflow models are trained on your actual lot geometry, camera positions, and lighting conditions and adapt to seasonal changes without recalibration. Deployed alongside existing in-ground sensors (Nedap SENSIT, Cleverciti, IEM) or LPR systems (Amano McGann, Passport Labs, ParkMobile), the vision layer catches what single-modality sensors miss.
Does parking occupancy AI support ADA compliance, GDPR/CCPA privacy, and municipal parking codes?
Yes. Roboflow models can be trained against your specific ADA accessible-spot verification requirements (per Section 4.6 of the ADA Standards for Accessible Design), GDPR and CCPA privacy requirements for license plate capture and retention (with on-device blurring and short-retention options), PCI DSS for payment integration audits, IEEE 2413 for smart city IoT interoperability, ISO/IEC 27001 for information security, and your city's specific municipal parking code. The system produces records that support ADA complaint defense, data subject access requests, city council reviews, and standard parking enforcement audit trails.
Can it integrate with our wayfinding signage, parking apps, dynamic pricing engines, LPR systems, and payment gateways?
Yes. Roboflow Inference exposes a standard API supporting common smart parking and mobility platforms. Integrations flow into wayfinding signage (Skidata, Amano, TIBA), mobile parking apps (ParkMobile, PayByPhone, Passport Labs), dynamic pricing systems, enforcement platforms (Genetec, Milestone XProtect), LPR systems (Amano McGann, Nedap SENSIT, INRIX), and payment gateways (Stripe, Square) through REST, MQTT, WebSocket, and direct database writes. Models support audit trails for GDPR/CCPA data subject requests, ADA compliance verification, and PCI DSS payment integration audits.