Internet Of Medical Things Final Year Projects with Source Code

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Internet Of Medical Things Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Internet Of Medical Things projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.

Internet Of Medical Things Final Year Projects

  1. Attack Detection for Medical Cyber-Physical SystemsA Systematic Literature Review
    This project looks at cyber attacks in hospitals, focusing on medical cyber-physical systems, which include devices connected to hospital networks. The researchers reviewed existing studies to understand how intrusions are detected, what datasets are used, and what gaps exist. They found that most work focuses on detecting unusual activity at the network level, often targeting insider threats. The study suggests creating specialized hospital datasets, improving standards, and developing methods that use medical context to better prevent cyber attacks and protect patients.
  2. An Integrated Scalable Framework for Cloud and IoT Based Green Healthcare System
    This project focuses on creating a smart healthcare system using IoT and cloud technology. Patients can send their health data from wearable devices, and doctors can view it in real-time. The system uses advanced algorithms to analyze the data and provides an easy-to-use interactive interface. It also emphasizes efficiency, scalability, and making healthcare more environmentally friendly.
  3. Deep Learning of Sparse Patterns in Medical IoT for Efficient Big Data Harnessing
    This project focuses on making medical IoT devices more energy-efficient. It uses deep learning to find and keep only the most important data from continuous medical data streams. The system also searches for the best network design to save power while keeping accuracy. This approach can help devices like heart monitors run longer and support better precision medicine.
  4. Modeling of Blockchain Assisted Intrusion Detection on IoT Healthcare System Using Ant Lion Optimizer With Hybrid Deep Learning
    This project focuses on making healthcare IoT systems more secure. It uses blockchain to protect sensitive medical data and detects unauthorized access using smart algorithms. The system combines advanced deep learning methods with optimization techniques to improve accuracy in spotting intrusions. Tests show it works better than existing methods for keeping IoT healthcare systems safe.
  5. Security-Aware Provenance for Transparency in IoT Data Propagation
    This project studies how to make data in an Internet of Things system more transparent and trustworthy. It adds extra security information to track every step of data movement. The system is tested with different cyber-attack situations to see how well it detects problems. This helps users understand risks and make better decisions without slowing down the system.
  6. A Novel Artificial Spider Monkey Based Random Forest Hybrid Framework for Monitoring and Predictive Diagnoses of Patients Healthcare
    This project focuses on detecting diseases like cancer, diabetes, and heart problems at an early stage using smart data analysis. It combines artificial intelligence with a Random Forest algorithm to identify subtle patterns in patient data and make accurate diagnoses. The system also uses secure data encryption to protect patient information. Tests show it is highly accurate, fast, and can help doctors make timely treatment decisions.
  7. A Conformal Leaky-Wave Antenna Design for IoMT-Based WBANs
    This project focuses on improving continuous health monitoring using wearable medical devices. It designs a wireless network system that reliably connects sensors on the body to a central hub. The system uses a special coding method in sensors and a new type of antenna to prevent signal interruptions, even with body movement. Tests show it works better than conventional antennas and is safe for human use.
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