QingCLoud 轻步云
AI-Powered Health Monitoring Platform
An end-to-end development of an AI health platform featuring a predictive ML model using smart insole data, paired with a suite of multi-platform applications.
Project Overview
QingCLoud (轻步云) is an innovative edge-cloud collaborative AI health monitoring platform. It leverages data captured from smart IoT insoles to predict potential health risks, such as flat feet, clubfoot, or other gait abnormalities.
As the Project Lead and Core Developer, I designed and implemented the full architecture:
- Hardware Integration: Interfacing with smart sensored insoles over Bluetooth/IoT protocols to collect real-time pressure arrays and temporal gait data.
- Machine Learning Backend: Developed predictive models mapping real-time pressure variations to biomechanical health indicators. Optimized inference for fast real-time feedback.
- Multi-platform Application: Developed client-side applications (Mobile app & Web dashboard) for users to visualize their gait data (e.g., foot pressure heatmaps) and receive actionable health reports.
Technical Implementation
Edge-Cloud hybrid architecture. Edge devices (IoT insoles + Mobile App) handle data aggregation and lightweight processing, while the cloud backend handles heavy AI inference and long-term data tracking.
Key achievements
- Led a highly cross-functional team across hardware, AI, and software domains.
- Successfully built and deployed the MVP platform, proving the feasibility of low-cost wearable gait analysis for public health.
- Designed an intuitive UI/UX for visualizing complex pressure heatmaps.