AI-Powered Tool Management System Development -- 2

I'm seeking a professional who can build an AI assistant for managing various tools within my business. The primary goal is to streamline operations, with a particular focus on: - Tools Management: The AI should oversee our Inventory Management tools, CRM tools, and user identification processes. - Functionality: The AI's capabilities should include automating routine tasks, generating comprehensive reports, and providing real-time notifications. Ideal candidates will have a strong background in AI development, particularly with automation systems, and experience in designing solutions for inventory and CRM tools. Understanding of OCR and transformed models will be a plus. I am looking for someone who can deliver a highly functional, intuitive system that will significantly improve our operational efficiency. ### Objective: To develop an automated tool management system that uses Optical Character Recognition (OCR) and Transformer models (via Hugging Face) for tool detection, with real-time notifications for inventory summaries and tool check-in/out status. Notifications will be displayed on a screen monitor and relayed through a self-hosted 3CX phone system deployed on a Raspberry Pi. ### Key Features: - **Tool Detection:** Use a Transformer-based model to identify tools from images and multiple live cameras. - **OCR Integration:** Extract text (e.g., serial numbers, labels) from tool images for identification. - **Inventory Management:** Maintain a dynamic inventory list with real-time status updates. - **Check-In/Out System:** Track tool movements in and out of the inventory. - **Notifications:** - On-Screen Display: Show inventory summaries and tool statuses on a monitor. - 3CX Phone Integration: Send notifications to users and management via calls or messages. ### Tech Stack: - **Hardware:** Raspberry Pi (for 3CX system) - **Models & Libraries:** Hugging Face Transformers, Tesseract OCR - **Server & Networking:** Local server for processing, 3CX for communication ### Milestone-Based Implementation Details: #### Milestone 1: Initial Setup and Environment Configuration - Set up Raspberry Pi with 3CX phone system. - Configure a local server for handling image processing and notifications. - Install necessary libraries: Hugging Face Transformers, Tesseract OCR, and Flask/Django for API handling. #### Milestone 2: Tool Detection and OCR Integration - Train or fine-tune a transformer model for tool detection. - Integrate Tesseract OCR for text extraction from tool images. - Build a module to capture images and process them for tool recognition and identification. #### Milestone 3: Inventory Management System - Develop a database (e.g., SQLite, PostgreSQL) to store tool details, statuses, and check-in/out history. - Create API endpoints to update and fetch inventory data. - Implement logic to update inventory based on tool detection and OCR results. #### Milestone 4: Notification and Monitoring System - Build a dashboard to display real-time inventory status on a connected monitor. - Integrate with the 3CX API to send notifications via calls or messages. - Add configurable notification rules (e.g., alert when a tool is overdue or inventory is low). #### Milestone 5: Testing, Optimization, and Deployment - Conduct unit tests for each module (detection, OCR, inventory, notifications). - Optimize image processing speed and model accuracy. - Prepare a deployment script to automate server and Raspberry Pi setup. - Run end-to-end tests with real-world tool usage scenarios. ### Deliverables: - Full source code with documentation - Deployment guide for Raspberry Pi and 3CX setup - Testing and validation reports for more information: [login to view URL] -- look for the youtube tool management prototype using yolo3 and resnet, available for modification