AI-driven Hotel Reception Camera System
Budget: ₹12,500 – ₹37,500 INR
Project Overview
We are developing an advanced AI-powered camera monitoring system for hotel reception areas to prevent revenue leakage, track staff activity, and create intelligent customer profiles.
The system will integrate with CCTV cameras and use AI-based face recognition to monitor visitor interactions, identify revenue mismatches, and generate actionable reports.
We are looking for an experienced AI developer, computer vision expert, or full-stack AI team who can build and deploy a production-ready solution.
⸻
Main Objectives
• Detect every visitor entering reception
• Recognize hotel staff members
• Automatically create customer profiles
• Track complete customer–staff interaction history
• Prevent revenue theft and unrecorded bookings
• Generate automated alerts and reports
⸻
Core Features Required
1. Face Recognition System
• Detect and recognize staff faces
• Recognize repeat customers
• Auto-create profile for new visitors
• Store captured photo and visit history
• Real-time detection via CCTV feed
⸻
2. Customer Profile System
Each profile must include:
• Name (manual entry option)
• Phone number
• Photo (auto-captured)
• Visit history
• Room booked
• Amount charged
• Staff who handled booking
⸻
3. Staff Monitoring
• Track which staff handled which customer
• Time spent per interaction
• Detect suspicious behavior
• Alert if customer interaction exists but no booking entry
⸻
4. AI Theft Prevention Logic
Examples of system intelligence:
• Customer detected at reception but no booking entry
• Room occupied but not billed
• Same staff handling multiple unrecorded customers
• Revenue mismatch detection
Alerts should be sent via:
• Email
• WhatsApp
⸻
5. Web Dashboard
Admin dashboard must include:
• Live camera view
• Daily visitor count
• Staff activity logs
• Customer profiles and history
• Revenue mismatch alerts
• Search and filter functionality
⸻
6. Reports (Exportable)
• Daily revenue report
• Staff performance report
• Customer visit history
• Suspicious activity report
• Export to PDF and Excel
⸻
7. Hardware Integration
System must support integration with CCTV cameras such as:
• Hikvision
• Dahua Technology
• TP-Link
• CP Plus
Or recommend compatible AI camera hardware.
⸻
Preferred Technology Stack
• Backend: Python or Node.js
• AI and Computer Vision: OpenCV, Face Recognition, TensorFlow
• Database: Firebase or PostgreSQL
• Frontend: React or Angular
• Cloud: Google Cloud Platform or Amazon Web Services
⸻
Deliverables
• Fully working AI system (production-ready)
• Web dashboard (admin panel)
• Camera integration setup
• Installation guide
• Camera configuration guide
• Staff training session
• Complete source code
• Deployment documentation
⸻
Security and Privacy Requirements
• Data encryption (at rest and in transit)
• Role-based access control
• Full audit logs
• GDPR-style compliance
• Secure cloud deployment
⸻
Ideal Freelancer Profile
• Strong experience in AI and Computer Vision
• Prior work in face recognition systems
• Experience with CCTV RTSP integration
• Experience building SaaS dashboards
• Cloud deployment expertise
• Ability to provide architecture proposal before development
⸻
To Apply, Please Include
1. Portfolio of similar AI or Face Recognition projects
2. Proposed architecture
3. Estimated timeline
4. Estimated cost
5. Suggested improvements
⸻
We are building this as a scalable system that can later expand across multiple hotel properties. Serious and experienced developers only.
We are developing an advanced AI-powered camera monitoring system for hotel reception areas to prevent revenue leakage, track staff activity, and create intelligent customer profiles.
The system will integrate with CCTV cameras and use AI-based face recognition to monitor visitor interactions, identify revenue mismatches, and generate actionable reports.
We are looking for an experienced AI developer, computer vision expert, or full-stack AI team who can build and deploy a production-ready solution.
⸻
Main Objectives
• Detect every visitor entering reception
• Recognize hotel staff members
• Automatically create customer profiles
• Track complete customer–staff interaction history
• Prevent revenue theft and unrecorded bookings
• Generate automated alerts and reports
⸻
Core Features Required
1. Face Recognition System
• Detect and recognize staff faces
• Recognize repeat customers
• Auto-create profile for new visitors
• Store captured photo and visit history
• Real-time detection via CCTV feed
⸻
2. Customer Profile System
Each profile must include:
• Name (manual entry option)
• Phone number
• Photo (auto-captured)
• Visit history
• Room booked
• Amount charged
• Staff who handled booking
⸻
3. Staff Monitoring
• Track which staff handled which customer
• Time spent per interaction
• Detect suspicious behavior
• Alert if customer interaction exists but no booking entry
⸻
4. AI Theft Prevention Logic
Examples of system intelligence:
• Customer detected at reception but no booking entry
• Room occupied but not billed
• Same staff handling multiple unrecorded customers
• Revenue mismatch detection
Alerts should be sent via:
⸻
5. Web Dashboard
Admin dashboard must include:
• Live camera view
• Daily visitor count
• Staff activity logs
• Customer profiles and history
• Revenue mismatch alerts
• Search and filter functionality
⸻
6. Reports (Exportable)
• Daily revenue report
• Staff performance report
• Customer visit history
• Suspicious activity report
• Export to PDF and Excel
⸻
7. Hardware Integration
System must support integration with CCTV cameras such as:
• Hikvision
• Dahua Technology
• TP-Link
• CP Plus
Or recommend compatible AI camera hardware.
⸻
Preferred Technology Stack
• Backend: Python or Node.js
• AI and Computer Vision: OpenCV, Face Recognition, TensorFlow
• Database: Firebase or PostgreSQL
• Frontend: React or Angular
• Cloud: Google Cloud Platform or Amazon Web Services
⸻
Deliverables
• Fully working AI system (production-ready)
• Web dashboard (admin panel)
• Camera integration setup
• Installation guide
• Camera configuration guide
• Staff training session
• Complete source code
• Deployment documentation
⸻
Security and Privacy Requirements
• Data encryption (at rest and in transit)
• Role-based access control
• Full audit logs
• GDPR-style compliance
• Secure cloud deployment
⸻
Ideal Freelancer Profile
• Strong experience in AI and Computer Vision
• Prior work in face recognition systems
• Experience with CCTV RTSP integration
• Experience building SaaS dashboards
• Cloud deployment expertise
• Ability to provide architecture proposal before development
⸻
To Apply, Please Include
1. Portfolio of similar AI or Face Recognition projects
2. Proposed architecture
3. Estimated timeline
4. Estimated cost
5. Suggested improvements
⸻
We are building this as a scalable system that can later expand across multiple hotel properties. Serious and experienced developers only.