Hotel Front Desk Visitor Reception Image Dataset
#Object Detection #Image Recognition #People Counting #Intelligent Visitor Flow Analysis #Hotel Automation Services #Guest Recognition and Management
- Records
- 500 records
- Size
- 1.3G
- Format
- JPG
- Provider
MOBIUSI INC- Updated
- v1.02026-11-05
AI Analysis & Value Prop
Currently, hotel lobbies commonly face challenges in managing visitor flow during peak periods effectively. Relying on manual records is inefficient and prone to errors. Existing solutions primarily use traditional surveillance but lack adequate utilization and intelligent analysis capabilities. This dataset aims to promote the development of intelligent management systems to address technical issues such as automatic visitor flow recognition and visitor service efficiency optimization. Data collection is conducted through high-definition cameras deployed at the hotel front desk, covering a variety of visitor behavior scenarios to ensure environmental diversity. Multiple rounds of annotation and expert consistency checks are used to ensure data annotation quality, executed by a team with computer vision and hotel management experience, totaling 20 people. Data preprocessing includes image cleaning, normalization, and enhancement, finally stored in classification and annotation form in JPG format.
Overview
Dataset Insights
Preview
Sample Examples
90dafea8**.jpg|640*768|117.39 KB
cf97666e**.jpg|640*480|96.35 KB
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| visitor_count | int | The number of visitors identified in the image. |
| visitor_gender_distribution | json | Gender distribution of visitors identified in the image, including genders and respective counts. |
| visitor_age_group | json | The age group distribution of visitors identified in the image, such as children, adults, and elders. |
| visitor_emotion | json | The emotional states of visitors identified in the image, such as smiling, angry, calm, etc. |
| staff_presence | boolean | Whether there are front desk staff present in the image. |
| queue_length | int | The number of queued visitors identified in the image. |
| time_of_day | string | The time of day when the image was captured, such as morning, afternoon, or evening. |
| luggage_count | int | The number of luggage pieces identified in the image. |
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
- In which scenarios is this dataset mainly used?
- The Hotel Front Desk Visitor Reception Image Dataset is primarily used to enhance smart visitor flow analysis, optimize service efficiency, and improve customer experience at hotel front desks.
- How does this dataset support smart visitor flow analysis?
- The dataset provides images of front desk visitor receptions, aiding in training computer vision models to recognize and analyze visitor flow patterns and customer behaviors.
- What business advantages can be gained by using this dataset?
- By utilizing this dataset, hotels can improve their service processes, enhance operational efficiency, and provide more personalized guest experiences, thereby increasing customer satisfaction and loyalty.
- What is the object detection functionality of this dataset?
- The object detection functionality of the dataset can be used to identify people, items, and activities in the front desk area, assisting front desk staff in more effective guest management and service scheduling.
- Can this dataset be used for training machine learning models?
- Yes, the Hotel Front Desk Visitor Reception Image Dataset is particularly suitable for training machine learning models to enhance the accuracy of target detection and recognition.
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Cite this Work
@dataset{Mobiusi2026,
title={Hotel Front Desk Visitor Reception Image Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/9896192bfee9bb41599f81321294ae07?dataset_task_cate_id=7},
urldate={2026-02-04},
keywords={Hotel AI Front desk, Visitor Reception Image, Object Detection Dataset, Hotel Intelligence},
version={1.0}
}Using this in research? Please cite us.
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