Safeguarding Port Operations

The port terminal implemented a sophisticated Port Safety Management System, utilizing Python, Tensorflow, Keras, Pandas, computer vision algorithms, and real-time data analysis with Redis, training the AI system to recognize PPE usage, enforce access control, optimize traffic management, and identify unsafe

Mobile Damage Detection

Two different detectors were implemented to address screen and back panel defects. The screen defect detector was built using techniques like adaptive thresholding, shape detection, Hough Transform, and morphological operations. Meanwhile, the back panel detector leveraged technologies such as Pytesseract and

Revamping Customer Service

The solution encompassed adaptive algorithms for Queue Analysis, a weighted scoring system for Handling Time Metrics, OpenAI's capabilities for generating comprehensive reports and automated communication, alongside AI methodologies prioritizing timely responses and identifying low answer rates, all integrated with advanced data

Sports Coaching App

The solution leveraged a PyTorch-based cloud-deployed AI engine for in-depth analysis of 133 body joints, facilitating performance feedback, player tracking, and key modules for Object Detection, Object Tracking, and Pose Estimation, powered by Python, PyTorch, MMCV, Time Series Analysis, Kubeflow, Google