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.

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

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.

A training pipeline for customizing YAMNet to recognize new environmental or industrial sounds.

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

Recognizes hand gestures over time to enable touchless human–machine interaction on edge devices.

Predicts ground settlement around tunnel boring operations using geotechnical and TBM operational data.

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.

Guided training environment for creating and preparing custom Face Recognition models, with optimized deployment and inference on SECO hardware.

Transcribes spoken audio into text using Wav2Vec2 for edge-based speech recognition applications.

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