Enterprises

This project focuses on developing AI analysis and real-time interpretation technologies for physiological signals from medical devices, with emphasis on high-accuracy feature extraction and multi-class model construction for ECG and related physiological data to enhance cardiovascular anomaly detection. The system integrates signal preprocessing algorithms, AI classification models, edge real-time inference architecture, and a cloud data platform, enabling secure transmission and low-latency synchronization via Bluetooth and 5G communication. It collects and analyzes ECG data in real time, proactively notifying medical personnel or caregivers upon detecting abnormalities, while supporting high-resolution medical data visualization and 3D dynamic imaging for telemedicine, clinical education, and surgical assistance. Key workstreams include physiological signal analysis and feature extraction, ECG multi-class AI model development and optimization, signal denoising and preprocessing algorithm design, edge inference system development, medical data encryption and communication security, Bluetooth and 5G integration, cloud-based medical analytics platform construction, and 3D dynamic medical imaging system development. The overall architecture complies with medical regulations and data security standards, with model validation and version control workflows to strengthen the independence and commercialization potential of domestic medical AI technologies.

This project focuses on developing core technologies for intelligent agent AI systems, establishing a multimodal data analysis and edge inference platform with autonomous decision-making capabilities. The system integrates physiological signals, behavioral data, and contextual information through a hierarchical AI architecture—where the upper layer handles semantic understanding and decision logic, while the lower layer manages real-time signal analysis and low-latency inference—forming an embedded intelligent agent system for end devices. Via 5G and private network communication technologies, the system receives and analyzes data in real time, proactively delivering decision recommendations and alerts upon detecting anomalies or specific conditions. The technology emphasizes model compression, low-power edge computing, and data security encryption/decryption to ensure real-time performance and information security, while supporting standardized API interfaces for cross-system integration. Future applications include healthcare, sports health management, and smart venue scenarios, enhanced by real-time data visualization and immersive interactive technologies to strengthen intelligent decision support and advance industry digitalization.