RPI Vision AI for Industrial User and Tool Management
Budget: $250 – $750 USD
I'm looking for a robust Vision AI solution based on Raspberry Pi (RPI) tailored for an industrial site. This system should handle both user identification and tool check-in/-out.
Key Features:
- User Identification: The preferred method for identifying users is through ID card scanning. The system should be able to efficiently read and process ID cards to facilitate seamless entry and monitoring.
- Tool Management: The Vision AI should also oversee tool check-in and check-out. It should accurately identify tools being checked-out, used, returned, and their current status.
- Alarm notice to the management of its status
- Real-time Notifications: Implement a system that sends real-time notifications to administrators when unusual activity or tool misuse is detected.
- Tool Usage Analytics: Provide detailed analytics and reporting on tool usage patterns and user activities to help optimize tool inventory and availability.
- Multiple ID Formats: Allow the system to support various types of ID cards (RFID, magnetic stripe, smart cards) for user identification.
- Mobile App Integration: Develop a mobile application that allows users to check in/out tools using their smartphones and view their tool usage history.
Skills and Experience:
- Proficiency in Raspberry Pi and Vision AI technology is essential.
- Prior experience in implementing such systems in an industrial environment will be advantageous.
- Skills in developing efficient ID card scanning systems are highly desirable.
- Understanding of tool management systems will be a plus.
This project aims to enhance security and efficiency in our industrial site, making user and tool management more streamlined and effective.
The system should include a touchscreen display for ease of use. The Vision AI solution should integrate seamlessly with the existing ERP system for streamlined operations. The system should partially integrate with existing security systems, selectively interfacing with essential components only. Real-time notifications should be sent via SMS to administrators. The system should utilize an SQL database for storing user, tool, and activity data. The system should include audible alarms to notify management of its status. The system should be capable of operating in extreme temperature conditions. The system should achieve a high accuracy rate of 99% or above in tool identification.
Key Features:
- User Identification: The preferred method for identifying users is through ID card scanning. The system should be able to efficiently read and process ID cards to facilitate seamless entry and monitoring.
- Tool Management: The Vision AI should also oversee tool check-in and check-out. It should accurately identify tools being checked-out, used, returned, and their current status.
- Alarm notice to the management of its status
- Real-time Notifications: Implement a system that sends real-time notifications to administrators when unusual activity or tool misuse is detected.
- Tool Usage Analytics: Provide detailed analytics and reporting on tool usage patterns and user activities to help optimize tool inventory and availability.
- Multiple ID Formats: Allow the system to support various types of ID cards (RFID, magnetic stripe, smart cards) for user identification.
- Mobile App Integration: Develop a mobile application that allows users to check in/out tools using their smartphones and view their tool usage history.
Skills and Experience:
- Proficiency in Raspberry Pi and Vision AI technology is essential.
- Prior experience in implementing such systems in an industrial environment will be advantageous.
- Skills in developing efficient ID card scanning systems are highly desirable.
- Understanding of tool management systems will be a plus.
This project aims to enhance security and efficiency in our industrial site, making user and tool management more streamlined and effective.
The system should include a touchscreen display for ease of use. The Vision AI solution should integrate seamlessly with the existing ERP system for streamlined operations. The system should partially integrate with existing security systems, selectively interfacing with essential components only. Real-time notifications should be sent via SMS to administrators. The system should utilize an SQL database for storing user, tool, and activity data. The system should include audible alarms to notify management of its status. The system should be capable of operating in extreme temperature conditions. The system should achieve a high accuracy rate of 99% or above in tool identification.