IoT based malaria website model using Digital Binary Code : A Mathematical Study

There has been a major increase in research on digitizing the disease’s tracking systems. In the scientific community, automated screening for malaria is one of the detection methods that is becoming very common. Although the Fourth Industrial Revolution (4IR) has gained widespread acceptance, the treatment for malaria, one of the deadliest and most enduring diseases, has not evolved. Contextualization of malaria monitoring systems must be established at the national or regional level, and this requires process integration with other protocols. This study suggests a digital malaria monitoring system for a country or region in Africa. The development of a distinctive model for forecasting disease spread, grounded in the dynamics of various types of malaria, represents a significant benefit of this digital system. We analyze the SITRR (susceptible-infected-treated resistant-recovered) epidemic model of the illness’s spread to produce a mathematical forecast and to define the design of the diagnosis system.