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Elevator Riding Device Detection Image Dataset
Synthetic Images & Vision Datasets
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£8,000
About
Description
This dataset focuses on visual detection tasks of riding devices inside residential elevators. It covers four main categories: electric vehicles, balance scooters, electric scooters, and bicycles, with a particular emphasis on electric vehicles (including electric bicycles and electric motorcycles) entering elevators.
Images cover various elevator structures, lighting conditions, and real-world usage scenarios, such as folding bikes, electric vehicles with windshields, and children riding devices. The dataset is suitable for training and evaluating elevator safety detection, riding device recognition, and abnormal access interception models.
Keywords
Phrases: elevator detection, riding device recognition, electric vehicle in elevator, vehicle recognition, safety interception system
Underscored: elevator_detection riding_device_recognition electric_vehicle_in_elevator vehicle_recognition safety_interception_system
Underscored: elevator_detection riding_device_recognition electric_vehicle_in_elevator vehicle_recognition safety_interception_system
Application Scenarios
- AI-based elevator safety recognition systems in residential communities
- Riding device detection model training for elevator access control
- Electric vehicle violation warning systems for elevators
- Visual algorithm adaptation testing for embedded monitoring devices
Scene Description
Elevator Environment
- Cabin Size: standard residential elevator specifications
- Interior Facilities: metal or mirror-finished walls, control panel (with floor buttons), ventilation outlets, built-in surveillance cameras
- Lighting Conditions: primarily LED ceiling lights, with natural light variation during door opening and closing
Collection Conditions
- Camera View: surveillance perspectives installed at elevator ceiling or corners, fully covering riding devices
- Interference Factors: passenger occlusion (≤50%), multiple passengers, spatial overlap
- Special Cases: children riding, folding electric vehicles, riding devices with windshields
Data Attributes
Target Categories and Sample Counts
- Electric Vehicles (electric bicycles and electric motorcycles): 2,000 images
- Balance Scooters: 1,000 images
- Electric Scooters: 1,000 images
- Bicycles: 1,000 images
- Total Samples: 5,000 images
Image Parameters
- Resolution: 1280 × 720
- Color Space: RGB
- Image Format: JPEG / PNG
Sample Characteristics
- Occlusion samples account for approximately 30 percent (passenger occlusion ≤50 percent of device)
- Includes dynamic image sequences during elevator door opening and closing
- Increased coverage of key "entering elevator" scenarios to support model accuracy optimization
Sample Images
Additional Notes & Services
- Usage Policy: Please adhere to all ethical standards and privacy regulations. Preprocessing may be required.
- Actively Maintained: This dataset is continuously updated. Contact us for the latest version.
- Full Customization Available: We can tailor image formats, annotations, and other specs to your project needs.
- Flexible Delivery: We offer split packages and delivery via private server or cloud storage.
- Free Sample Package: Available for qualified buyers to verify data quality.
- Contact Us: For inquiries, customization, or samples, email us at contact4data-project@join-intelligence.com
- Explore All Datasets: Visit our Notion Collection
- Official Website: https://join-intelligence.com/
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£8,000
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