Underground Parking Lot Empty Slot Detection Dataset
#object detection #image recognition #computer vision #parking management #traffic monitoring #smart city
- Records
- 500 records
- Size
- 1.3G
- Format
- JPG
- Provider
MOBIUSI INC- Updated
- v1.02026-11-04
AI Analysis & Value Prop
With the acceleration of urbanization, the management of underground parking lots has become increasingly complex, with low space utilization and traffic congestion being common problems. Existing manual management and traditional surveillance cameras cannot monitor empty slots in real-time and efficiently, incurring high costs and with limited accuracy. This dataset aims to assist in identifying and detecting empty slots in underground parking lots using deep learning technology, improving parking management efficiency and user experience. Images are collected from high-definition cameras installed on the ceiling of parking lots, covering various weather and lighting conditions. Quality control involves multiple rounds of manual annotation and consistency checks to ensure the consistency and accuracy of each annotation. The annotation team consists of 12 experts with backgrounds in traffic management and computer vision. Preprocessing stages include data cleaning, denoising, and normalization, using the latest image enhancement techniques to augment the samples. Data is stored in JPG format, organized into folders classified by time and location.
Overview
Dataset Insights
Preview
Sample Examples
7d45e1e0**.jpg|1079*1397|321.00 KB
cde88605**.jpg|1080*1400|246.60 KB
ec7233bd**.jpg|1439*1031|168.14 KB
66bf2a1d**.jpg|2268*1080|382.96 KB
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| parking_space_id | string | A unique identifier for the parking space. |
| is_vacant | boolean | Indicates whether the parking space is vacant. |
| vehicle_presence | boolean | Indicates the presence of a vehicle in the parking space. |
| confidence_level | float | Confidence level of the vacant parking space detection, ranging from 0 to 1. |
| bounding_box | string | Coordinates of the bounding box for the detected parking space area. |
| parking_layout | string | Describes the layout of parking spaces within the parking lot. |
| lighting_condition | string | Responsibly indicates the lighting condition, such as daytime or nighttime. |
| camera_angle | string | Denotes the angle at which the camera is installed. |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use
Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization
No PII, no real company names, simulated scenarios follow industry standards
Compliance System
Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs
FAQ
Frequently Asked Questions
- What is the underground parking lot empty space detection dataset?
- The underground parking lot empty space detection dataset is an image dataset used for detecting and identifying empty parking spaces, aimed at improving parking management efficiency.
- How does this dataset contribute to the development of the traffic sector?
- The underground parking lot empty space detection dataset helps improve traffic conditions, enhance parking efficiency, and improve user experience by providing accurate empty space information.
- What are the main applications of the underground parking lot empty space detection dataset?
- This dataset is mainly used in parking management systems, smart city planning, and traffic optimization to help drivers quickly find parking spots by detecting empty spaces.
- What are the characteristics of the image modality in the underground parking lot empty space detection dataset?
- The image modality features of the dataset include multi-angle and variable lighting condition images of parking lots, covering different types of parking situations to ensure the robustness of detection algorithms.
- How to use this dataset to improve parking management efficiency?
- By using the underground parking lot empty space detection dataset to train machine learning models, real-time detection of empty parking spots can be achieved, thereby improving parking management efficiency.
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Cite this Work
@dataset{Mobiusi2026,
title={Underground Parking Lot Empty Slot Detection Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/6a3f0662719aa2e731b45231865461f7?dataset_scene_cate_type=1},
urldate={2026-02-04},
keywords={underground parking, empty slot detection, image recognition dataset, traffic management dataset, object detection},
version={1.0}
}Using this in research? Please cite us.
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