IoT Smart Health

Course Title: IoT Smart Health

Course Code: [27022-COs-CS]
Category: Internet of Things (IoT), Healthcare Technology

🧩 Introduction

The intersection of IoT (Internet of Things) and healthcare is transforming how we monitor, manage, and deliver health services. This course explores the foundational principles and real-world applications of IoT in smart health systems. Participants will learn how to design, prototype, and evaluate IoT-enabled health monitoring and diagnostics systems using modern sensors, communication protocols, and data analytics platforms.

Module 1: Introduction to IoT and Smart Healthcare

• Definition of the Internet of Things (IoT)

• Applications of IoT in healthcare

• Benefits and challenges of using IoT in healthcare

Module 2: Components of IoT Healthcare Systems

• Smart devices and medical sensors

• Gateways and communication protocols (e.g., MQTT, HTTP)

• Cloud storage and data analytics

Module 3: Wearable Devices

• Types of wearable devices in healthcare

• Remote health monitoring

• Integration with smartphone applications

Module 4: IoT Healthcare Platforms

• Using platforms like Google Cloud IoT, AWS IoT, Azure IoT

• Device and data management on cloud platforms

• Integration with AI technologies for health data analysis

Module 5: Security and Privacy in IoT Health

• Protecting health data (Data Security)

• Compliance with healthcare regulations (e.g., HIPAA, GDPR)

• Identity management and authentication of smart devices

Module 6: Networks and Protocols

• Communication technologies (WiFi, Bluetooth, Zigbee, LoRa)

• Secure communication protocols

• Choosing the right protocol for healthcare applications

Module 7: Practical Applications and Projects

• Building a health monitoring system using sensors

• Developing health apps for smartphones

• Implementing AI-based health data analysis models

🎓 Learning Outcomes

Upon successful completion, learners will be able to:

• Build and deploy IoT systems for remote health monitoring

• Collect and analyze real-time physiological data

• Design secure, cloud-connected medical IoT devices

• Prototype wearable health systems and mobile alerts

• Understand the integration challenges with healthcare standards

⏱️ Time Frame

• Duration: 6 Weeks

• Sessions: 12 Sessions (2 sessions/week, 2 hours each)

• Final Project Submission: Week 6

🧭 Course Format

• Mode: Hybrid (Online + Lab-based Sessions)

• Structure:

   Introduction to IoT and Healthcare Needs, Sensors & Microcontrollers for Health Monitoring, Data Communication & Cloud Platforms, Security & Privacy in IoT Health Systems, Case Studies & Industry Applications,  Capstone Project + Evaluation

• Tools and Software

  • Hardware: Arduino, Raspberry Pi, ESP32 with health sensors

  • Software:

    • IoT Platforms: Google Cloud IoT, AWS IoT, Azure IoT

    • Programming Languages: Python, C/C++

    • Data Analytics: Jupyter Notebook, Pandas, Matplotlib

    • AI/ML Frameworks: TensorFlow, Scikit-learn (optional)

    • Communication: MQTT clients, Wireshark for packet analysis

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  Teaching Methodology

  • Lectures with slides and real-world examples

  • Hands-on labs and demos

  • Group discussions and case studies

  • Project-based learning with milestones

  • Guest lectures from industry experts (optional)

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  Assessment and Evaluation

  • Quizzes and Assignments: After each major module

  • Lab Exercises: Hands-on sensor integration and cloud data management

  • Midterm Test: Covering theoretical and practical knowledge

  • Final Project:

    • Design and implementation of a functional smart health IoT system

    • Presentation and demonstration

    • Written report including architecture, challenges, and results

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  Additional Resources

  • Research papers and articles on IoT healthcare trends

  • Online tutorials for cloud platforms

  • Open datasets for health monitoring and analysis

  • GitHub repositories with example codes

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