AI-Based Automated Counting & Data Logging System
This system provides crucial operational data, accurately identifies items, slashes processing times, and eliminates costly manual errors.
Developed an AI-powered system for automated counting and data logging of unordered object collections. Using image-based object detection, the system accurately identifies and counts individual items without manual input, reducing errors and improving efficiency in real-time Operations
99.95% Counting Accuracy Achieved
Significantly reduced human error in counting tasks through reliable AI-driven object detection.
Increased Operational Efficiency
Automated counting eliminated the need for manual tracking, reducing processing time by over 40%
Technologies Used
- Pythoncore programming language for AI model development and system integration.
- OpenCVfor real-time image processing and object segmentation.
- TensorFlowfor training and deploying deep learning-based object detection models.
- YOLO / SSD Modelspre-trained or custom-trained models for fast and accurate object detection.
- Raspberry Pi / NVIDIA Jetson / Cloud VMfor edge or cloud-based deployment depending on performance needs.
