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

Neural network model for forecasting household electricity consumption using historical time series data.

Efficient edge analytics using Qualcomm HW to extract facial attributes for personalization and safety.

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

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