AI-assisted HMI that detects operator presence during machine alerts and provides contextual troubleshooting information.

Real-time detection of critical alarm and emergency sounds for industrial safety applications.

Real-time people detection and counting for industrial and monitoring applications.

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

Efficient single-camera depth estimation using quantized MiDaS v2 model optimized for edge AI deployment.

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

Short-term electricity consumption forecasting based on historical time-series data.

Classifies physical activities in real time from wearable motion sensor data.

Detects face presentation attacks and verifies liveness from RGB images to strengthen biometric authentication systems..

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

Detects faces and performs face recognition using a lightweight Edge Impulse pipeline designed for edge devices.

Identifies or verifies speakers from voice recordings using robust ECAPA-TDNN speaker embeddings.

Detects and maps land-cover changes from multi-temporal satellite or aerial imagery for environmental monitoring and urban analysis.

AI vision application to detect human falls in real time for safety, elderly care, and industrial risk monitoring.

Classifies human actions from video sequences to support activity understanding, workflow analysis, and safety applications.

Energy-efficient object detection optimized for edge platforms with power and thermal constraints.

Bridging the Field and Digital: Universal Connectivity, Zero Latency, and On-Device Machine Learning for Industry 5.0.