An Intelligent IoT Based Healthcare System Using Fuzzy Neural Networks

TLDR

Healthcare in developing countries faces shortages of quality hospitals and specialists, and conventional store‑and‑forward telemedicine suffers from delays, high costs, and infrastructure demands. The paper proposes an IoT‑based, machine‑learning–driven healthcare system to address these limitations. The system collects patient data through IoT sensors, processes it with a medical decision‑support algorithm, and delivers low‑cost, real‑time health assessments that guide users to nearby hospitals. Experimental results demonstrate that the prototype is efficient, intelligent, and provides proof of concept for remote health care delivery.

Abstract

Healthcare facilities in modern age are key challenge especially in developing countries where remote areas face lack of high-quality hospitals and medical experts. As artificial intelligence has revolutionized various fields of life, health has also benefited from it. The existing architecture of store-and-forward method of conventional telemedicine is facing some problems, some of which are the need for a local health center with dedicated staff, need for medical equipment to prepare patient reports, time constraint of 24–48 hours in receiving diagnosis and medication details from a medical expert in a main hospital, cost of local health centers, and need for Wi-Fi connection. In this paper, we introduce a novel and intelligent healthcare system that is based on modern technologies like Internet of things (IoT) and machine learning. This system is intelligent enough to sense and process a patient’s data through a medical decision support system. This system is low-cost solution for the people of remote areas; they can use it to find out whether they are suffering from a serious health issue and cure it accordingly by contacting near hospitals. The results of the experiments also show that the proposed system is efficient and intelligent enough to provide health facilities. The results presented in this paper are the proof of the concept.