AI-Enabled Diabetic Foot Care: A Cloud-Based IoT Ecosystem for Real-Time Monitoring and Recommendation

This paper presents innovative healthcare features on the Internet of Things (IoT) for monitoring and preventing diabetic foot complications. We propose an Information System (IS) architecture that integrates multi-modal sensors, which include temperature, pressure, and gyroscope sensors and enables early detection and management of diabetic-related foot issues. The system is structured in two layers. The data acquisition and orchestration tiers collect, process and visualize data from various sensors using an ESP32 microcontroller through a mobile application, performing cloudbased processing and storage under robust security features. The system leverages artificial intelligence-guided Large Language Models to provide personalised health recommendations. The paper aims to develop an IoT framework offering real-time diabetic-related foot care products and services intending to improve patient outcomes and clinical validations. This comprehensive approach addresses the challenges of diabetic foot care by providing real-time monitoring, data analysis, and user-friendly health metrics visualization