Title: Cardiovascular disease prediction using hybridisation multi perception classifier in secure IoT platform

Authors: M. Safa; A. Pandian; K. Chakrapani; Karpaga Selvi Subramanian; M. Kempanna; D. Arun; K.M. UmaMaheswari

Addresses: School of Computing, SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, Tamilnadu, India ' School of Computing, SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, Tamilnadu, India ' School of Computing, SASTRA Deemed University, Tanjore, 613401, Tamilnadu, India ' Department of Computer Science and Engineering, Bharat Institute of Engineering and Technology, Hyderabad, 501510, India ' Department of AI & ML, Bangalore Institute of Technology, Bangalore, 560004, India ' Iconic Trainer VMware SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, Tamilnadu, India ' School of Computing, SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, Tamilnadu, India

Abstract: The primary purpose of this study is to propose a hybrid fuzzy-based decision tree method for early heart attack prediction using a continuous and remote patient monitoring system. The first planned goal is to create an IoT system that detects an individual's level of stress and uses the information gathered through sensor-linked IoT to help individuals cope with stress. The sensory system detects and monitors other proposed datasets for heart disease patients involved in temperature, blood pressure, pulse oximetry, and stress. The IoT Edge intelligence device senses signals from sensors. It manages and monitors output using the MQTT protocol. The IoT Hub, in collaboration with large-scale devices, generates analytical cardiovascular predictions using streaming analysis and real-time data processing in this suggested system. Predictive models for stress analysis are designed using machine learning methods.

Keywords: cardiac disease prediction; big data analysis; HMPC; hybridisation multi perception classifier; CHD; stress; sensors.

DOI: 10.1504/IJSSE.2025.144566

International Journal of System of Systems Engineering, 2025 Vol.15 No.1, pp.1 - 14

Received: 06 May 2023
Accepted: 18 May 2023
Published online: 21 Feb 2025 *

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