The healthcare industry is rapidly evolving, with a strong push towards smarter, connected, and proactive care systems. In this session, we’ll explore how IoT and AI technologies are transforming healthcare delivery by enabling real-time monitoring, predictive diagnostics, and seamless integration with existing digital systems.
Learn how to build IoT solutions using open-source hardware like Raspberry Pi or Arduino, connect them with CRM/ERP platforms for real-time data visibility, and use cloud services to filter, store, and analyze patient data. We’ll dive into Pub/Sub messaging models for triggering alerts and explore how to use Python and cloud-based AI models to predict critical health events—like early signs of a heart attack—using real-world data and open-source algorithms.
Through live demos and case studies, you’ll walk away with a clear roadmap for creating impactful IoT + AI healthcare applications.
Introduction to IoT and commonly used healthcare sensors/devices
Cloud services for processing and managing IoT data streams
Real-time patient monitoring through CRM/ERP system integrations
Pub/Sub model for efficient alerting and event-based communication
Developing predictive AI models using Python and deploying them on the cloud
End-to-end architecture walkthrough and discussion