Identification of Diabetes with Mobile Applications using Cloud Based Expert System

Abstract

The integration of expert systems, mobile intelligence, and the cloud for diabetes diagnosis was the study's main objective. An expert system is a computer programme that makes use of a knowledge base and an inference engine to resolve problems considerably more quickly and effectively than they would otherwise. To lessen the limitations of mobile applications, the cloud has provided developers with a variety of services to create, manage, and deploy. Because of population expansion, ageing, addiction, urbanization, obesity, lack of exercise, and other complex diseases, there are more people with diabetes than ever before. Furthermore, these issues are made worse by a lack of specialists, inaccurate diagnoses, and inadequate medical facilities. Thus, diabetics require ongoing care such as dietary restriction, exercise, and insulin management. A hospital's knowledge was drawn from in order to create the prototype using a purposive sampling technique. Case studies are chosen for testing and assessing the prototype system in order to determine whether or not it is accurate and meets end-user criteria.