Automated detection and mapping of land-cover changes from satellite or aerial imagery for environmental monitoring and urban planning.

Secure face recognition HMI system for personalized user access in industrial environments.

HMI system that uses AI to recognize operators during alerts and show personalized troubleshooting instructions.

Detects critical alarm sounds (e.g., fire alarms) and triggers immediate machine shutdown for safety compliance.

Lightweight real-time people counting model based on quantized YOLOX, optimized for edge devices using LiteRT (TensorFlow Lite) .

Lightweight and quantized PoseNet model for real-time multi-person pose estimation on edge hardware.

High-resolution neural network for accurate keypoint detection in human pose estimation tasks.

Real-time activity recognition using motion sensor data from wearable fitness devices.

Deep learning model to detect presentation attacks in biometric systems, enhancing security against spoofing attempts.

Deep learning system to upscale and enhance low-resolution images while preserving fine details.

A time-series forecasting model designed to predict sensor data patterns in smart buildings, enabling proactive energy management and maintenance.

A lightweight face recognition solution leveraging Edge Impulse’s FOMO model, designed for fast, accurate deployment on edge devices in industrial environments.