AN INTELLIGENT PRIORITY-BASED TELEMEDICINE ALGORITHM FOR REAL-TIME EMERGENCY HEALTH MANAGEMENT IN MILITARY ENVIRONMENTS

n military environment especially in the battlefield duration the timely medical treatment is saving life, but the conventional telemedicine scheme is relay on first-come, first-served (FCFS) scheduling which causes the failed treatment for the emergency patient. To overcome such a scenario many other methods were proposed with latest technologies still the need of novel method to save such a people. This article is address the same , by proposing the novel algorithm proposes an Intelligent Priority-Based Telemedicine Algorithm (IPTA) which is assumed as a wearable device with the modern technologies of sensors, Internet of Thing and Machine learning to predict the soldiers vital parameters such as heart rate, oxygen saturation, blood pressure, and body temperature are continuously monitored and analyzed through machine learning–based predictive analytics to estimate each soldier’s health criticality. This proposed framework automatically identified the soldiers body condition and assign the priority to meet the telemedicine doctor. This experiment was tested using the simulation tools of MATLAB using Python and OMNET++ for connectivity related Quantitative and qualitative metric comparison with the traditional methos of FCFS, Rule Based and Fuzzy logic methods. Quantitative results expose proposed IPTA framework shown the improvements in accuracy (91.6%), resource utilization (91%), and packet delivery ratio (94%), latency (85 ms) and average response time (2.9 s). Also, system throughput increased by 31%, and survival probability improved by 24%.