A Mobile Expert System Application for Solving Personal Computer Problems (original) (raw)
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Periodicals of Engineering and Natural Sciences (PEN), 2018
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The problem of increasing the efficiency of maintenance and repair is being solved by applying flexible strategies using expert systems implemented in mobile applications. An expert system is a set of programs that accumulates knowledge of specialists in a particular domain and replicates this empirical experience for consultations of less skilled professionals. Mobile application is a modern software which intended for working on tablets, smartphones and other mobile devices. This article deals with a detailed description of the work of the expert system, the rules and facts of work are formed. The output of solutions diagnosing expert system is beeing developed. The implementation of the automatic synchronization of the mobile application with the technical documentation of troubleshooting is scheduled. The improvement of the mechanism for predicting the malfunction and solution as an expert system dialogue with the user is occurred. The organization of work in offline mode in the absence of a network connection has been planned.
A Mobile Based Expert System for Disease Diagnosis and Medical Advice Provisioning
Most developing countries like Nigeria are facing health care challenges caused by inadequate medical personnel, shortage of modern medical equipment and the dearth of modern hospitals in the rural, leading to high mortality rate especially in these rural areas. Statistics have revealed the high number of smartphones in different parts of Nigeria. Hence, a mobile based system could serve as a solution to these problems. Some researchers in this area of study tried to develop different stand-alone and web-based medical diagnostics systems using different approaches, in order to provide easy and fast access to diagnose and provide medical advices. In this paper, a rule based mobile expert system was designed and implemented to proffer diagnosis and medical advices to ten (10) common diseases that are prevalent in Nigeria. The mobile system was implemented on Android operating system technology which is the one the most common mobile operating system in Nigeria presently. The system was evaluated with some users and the results of the evaluation carried out on the system emphasizes its usefulness as an efficient decision support tool in the diagnosis and medical provisioning of the common health problems in Nigeria with a very high success rate from prospective users.
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An expert system service that deals with public problems or wide ranges of users basically requires an alternative medium, which is accessible. This paper proposes interface expansion for Web and WAP based expert system consulting application using an Android application interface. An open and accessible web service is developed to provide an access to the Android application to reach the knowledge base in the form of a decision tree stored in a particular database. The Android application employs HTTP for accessing data in a JSON format through web service. Then, the consultation mechanism would run interactively following an available path in the decision tree model from initial symptom identification to reach a conclusion.
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Bulletin of Electrical Engineering and Informatics, 2023
In recent years, both locally and globally, many citizens are cornered by different diseases which grates a lot of concern in the person, due to the collapse of different medical centers, it is necessary to use information systems. The objective of the research is to develop a mobile application that allows detecting what type of disease a patient suffers from and maintaining communication with the expert in the field using an expert system such as azure machine learning studio that allows detecting the deadliest diseases. For the development of this research, the rup methodology was applied, which allows the use of different techniques where the necessary activities can be carried out with efficient communication. For the validation of this project, a survey was used for the experts with a questionnaire of questions, giving a positive result in the implementation of this project. The result was an acceptance of 83.3% in a high way in their survey responses. In conclusion, this mobile application was successfully designed, benefiting many people and, above all, preventing dangerous diseases that can even lead to death.
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The purpose of this research is to develop an android application named "TANYA MEOW" which can be used by cat owners to detect the diseases that their cats suffer based on visible symptoms. The cat owners need to answer questionnaire to detect what disease is suffering by their cat. The result of the disease is also accompanied by the first treatment that cat owners can do to treat their cats. In addition, this application also has a feature that provides information, tips and tricks in cat care. The research methods used to analyze the development of this application are literature study through books, journals and e-books. Furthermore, observation, distribution of questionnaires for data collection and interviews to ensure data accuracy. We also make comparisons with applications that have similar concepts and features similar to our application. The research method used for the development of this application is waterfall that has five stages, requirements definition, system and software design, implementation and unit testing, integration and system testing and operation and maintenance. The results obtained from this writing show that the owner of the cat can feel the ease in detecting and knowing the disease from their cats who are sick, also getting knowledge on how to take care of cats in a good way.
A Proposed Mobile Based Health Care System for Patient Diagnosis using Android OS
Recent technological advances in mobile communication and rule based expert system together enable new types of healthcare systems. Especially the availability of Android OS based more user friendly GUI and cheap smart phones gives new possibilities for a continuously monitoring of human health status such his/her BP, Glucose level and there physiological parameters data allows an early detection of diabetes that leads other potential dieses. Our proposed healthcare system mainly takes care of patients who suffer from chronic disease like diabetes such person can live normally when the health condition is stable, but in critical condition he/she needs desperate help of doctors and assistance to reduce the probability of deteriorating health conditions. Such chronic patients can perform some simple self healthcare and monitoring functions via mobile phones through our proposed system to know about the probable diseases.
2012
In this paper we will discuss a survey on various work done in different areas using Expert System(ES). Different methods and algorithms are used in different areas to solve the problem. An expert system is created to solve problems in a particular narrow domain of expertise. There are two different ways developers look at application areas for ES i.e. first, functional nature of problem and secondly, the application domain. One of the key characteristics of an ES is the explanation facility. With this capability, an ES can explain how it arrives at its conclusion. This survey is aimed at reviewing the recent scientific aspects of various research done on ES using different techniques like Case Based Reasoning(CBR), Rule-Based, Fuzzy Logic etc. Keywords— Expert System, Case Based Reasoning, CLIPS,
Development of Android-based Rabbit Disease Expert System
International Journal of Engineering & Technology
Many rabbit keepers or breeders are panics when their rabbit has an illness. This paper proposed an expert diagnostic system application for Android-based rabbit disease using the Naïve Bayes method to determine the illness and Certainty Factor for the trust value of the condition by combining the rate of the trust of users and experts due to diagnose the diseases of the rabbit.The testing was using 65 data learning and 160 data learning to test the naïve Bayes method. Furthermore, the certainty factor is using CF user 1 and its variation.The results obtained for 65 data learning is 53%, while 160 data learning is 73%. With the naïve Bayes method, it can be concluded that the more data learning, the better and more accurate the system. The results of conformity with the testing data obtained from the variative CF user value, namely 53% accordingly, 13% inappropriate, 33% near. The effect of compliance with the sample data collected from the CF value of user 1 is 53% appropriate, 7% ...