A Mobile Expert System Application for Solving Personal Computer Problems.pdf

Selçuk-TeknikDergisi ISSN 1302-6178 Journal of Selcuk-Technic
Cilt 15, Sayı:3-2016 Volume 15, Number:3-2016
173
A MOBILE EXPERT SYSTEM APPLICATION FOR SOLVING PERSONAL
COMPUTER PROBLEMS
RawaShorshSDEEK1
,Rıdvan SARAÇOĞLU1, *
1
Yüzüncü Yıl University, Electrical-Electronics Engineering Department, Van Turkey
rawaise@gmail.com, *ridvansaracoglu@yyu.edu.tr
Abstract
For the time being, the smartphone is the most popular device in the world a
device that is still in development. Today everyone has a personal smartphonedevice.
Thecapability of these smartphones is to run a variety of all kinds of applications, make
user’s use it most of the time as well as for their daily tasks. The aim of this study is to
develop an expert system running on android smartphones in order to solve computer
problems. This approach is an accurate method to provide solution to computer
problems. Design and implementing this expert system is to detect problem by asking
users question and offers solution depending on user’s answer.Theoutput solution will
provide description with images to be clearer for users to understand what their issue in
fact is.
Keywords: Expert Systems, Mobile Application, Rule Based Systems.
KİŞİSEL BİLGİSAYAR PROBLEMLERİNİN ÇÖZÜMÜ İÇİN BİR MOBİL
UZMAN SİSTEM UYGULAMASI
Özet
ġu anda, hala geliĢtirilmekte olan akıllı telefonlar dünyadaki en popüler
cihazlardır. Bugün herkes kiĢisel bir akıllı cihaza sahiptir. Buakıllı
telefonların,kullanıcıların zamanlarının büyük bir kısmında hatta gündelik iĢlerinde
kullandıkları çok çeĢitli uygulamalar çalıĢtırma kabiliyetleri vardır. Bu çalıĢmanın
amacı bilgisayar problemlerini çözmek için android akıllı telefon üzerinde çalıĢan bir
uzman sistem geliĢtirmektir. Bu yaklaĢım bilgisayar problemlerine çözüm sağlamak için
doğru bir yöntemdir. Bu uzman sistemin tasarım ve gerçekleĢtirilmesi,kullanıcılara
sorular sormak suretiyle problemleri tespit etmek ve kullanıcı kullanıcıların cevaplarına

174
dayalı çözümler sunulması biçimindedir. Çıktıyı oluĢturan çözüm, kullanıcılar için
problemin aslında ne olduğunun anlaĢılmasını sağlayan Ģekilli tanımlayıcı bilgiler
sağlayacaktır.
Anahtar Kelimeler: Uzman Sistemler, Mobil Uygulama, Kural Tabanlı Sistemler.
1. Introduction
Mobile applications (commonly referred as “apps”), are considered to be one of
thefastest growing trends in Information Systems industry [1]. Users enjoy the varietyof
features that mobile apps can provide quickly and without introducing
unnecessarycomplexity into their designs. As a result, mobile apps present a more
popular interface forinteraction with business systems than using web applications via
Web Browser [1].
This technology shared between humans rapidly and still in development, there
are numerous applications that allow people to do almost everything they want. The
widespread penetration of smartphones globally offers tremendous opportunity and
synergy with classical understanding of education. In addition, in today’s world we
know what addicts people to technology; what makes them check smartphones ten times
during dinner. In 2011 Angry Birds was the first software application of any kind to
reach 1 billion downloads. Angry Birds reached a billion devices. By comparison, the
total number of televisions in American homes in 1960 numbered just 52 million [2, 3].
Mobile applications (a.k.a. apps) are software systems implemented to run on
smartphonesand other handheld devices. Apps have different genres, from games to
utilities, from productivitytools to browsers and are implemented using a variety of
programming languages [4].
2. Materials andMethods
2.1. Expert System
Expert systems (ES) are intelligent software applications that provide advice to
its users through a dialog or a conversation conducted between the user and the ES
application [5]. Mobiles are no doubt the most widely used means of communication for
its ease of use, ease of handling, and increasing capabilities. Most of the mobiles

175
nowadays are equipped with top edge technologies that enable the user to communicate
data in high rates, and provide geospatial services that make the user identify his
position on the earth accurately [6].There are two types of expert systems: rule-based
expert systems and knowledge-based expert systems. The main difference between
these expert systems is the knowledge representation in the knowledge base. The
knowledge representation is more significant in expert system because the approach
used to represent knowledge affects the development, efficiency, speed and the
maintenance of the system [7-10].
2.2. Rule based expert system
The rule-based expert system has domain knowledge encoded in the form of
rules from a human expert. A rule is a conditional statement that links given conditions
to actions. In a rule-based expert system, a knowledge base is usually stored in terms of
if-then rules which can be used to reach conclusions. A rule-based expert system is
constructed based on an efficient algorithm called the Rete pattern matching algorithm.
This algorithm matches facts against the patterns in rules to determine which rules have
had their conditions satisfied. Hence it uses a set of rules to analyses information about
a specific class of problems and recommends one or more possible solutions [11-13].
2.3. Knowledge based expert system
The knowledge-based expert system encodes heuristics and rules into decision
making framework. A knowledge-based system uses artificial intelligence techniques in
problem solving methods to support human decision making, learning, and action. The
knowledge base of expert systems contains both factual and heuristic knowledge.
Factual knowledge is the knowledge that is widely shared, typically found in textbooks
or journals, and commonly agreed upon by human experts in that particular domain.
Heuristic knowledge refers to an experiential, logical and judgmental knowledge used to
speed up decision making. Some applications applied by knowledge based expert
systems are: medical treatment, waste management, production management,
knowledge management, financial analysis, etc. [14-18].
2.4. Component of an Expert System
ES or the Knowledge Base Systems (KBS) are main branches of Artificial
Intelligence (AI). An ES can be defined as an intelligent computer program that uses
knowledge and inference procedures to solve problems that are difficult enough to

176
require significant human expertise for their solutions. The knowledge acquisition,
knowledge base, inference engine, explanation facility and the user interface are the
main ES components [19, 20]and figure 1 shows the diagram.
User knowledge engineer
Fig.1 Components ofan Expert System
2.4.1. Knowledge base:
A knowledge base is the heart of an expert system; it contains a collection of
facts and rules which describe all the knowledge about the problem domain. Therefore,
it stores all relevant information, data, rules, cases and relationships used by the expert
systems.A knowledge base is not a database system. Figure 2.4 shows sample rule based
on knowledge base.
2.4.2. Working memory:
Working memory is comparable to a relational database system. It contains
information that is supplied by the end user. This information is used to evaluate
antecedents in the knowledge base. A change in the knowledge base results in creation
of new values, thus the working memory will update its old values.
2.4.3.Inference engine
An inference engine implements the reasoning process of artificial intelligence;
it is an analogy to human reasoning. Its role is to work with the available data from the
system and the user to derive a solution to the problem. The purpose of inference engine
is to seek information and relationship from the knowledge base and to provide answers.
Inference
Engine
External
Programs
Knowledge
Base
Working
Memory
Developer
Interface
User Interface
Explanation
Facility

177
2.4.4. User interface
The user interface controls the dialog between the user and the system. Thus, it
is an intermediary that allows communication between the user and the system. The
purpose of the user interface is to ease the usage of expert system by developers, users
and administrators.
3. Related studies
Makhubele designed and developed a knowledge-based expert system that aims
to provide the patients with medical advice and basic knowledge on diabetes[21].
Liu improved client performance in client/server mobile computing systems, to
identify which of the techniques are most promising and can be adapted to a tourist
application (map viewing on small handheld devices, or other information like buses,
menus, and theatre agendas, traffic and weather, etc.) [22].
Clarke et.al.mentionedtwo emerging technologies that are being incorporated
into organizations at ever-increasing rates are expert systems and multimedia.
Thesetechnologies have been developed independently [23].
Semertzidis produce a new mobile learning application which offer direct
communication between teacher and student, and enhanced patterns of mobile interface
design and tactics for solving common mobile development problems [24].
Minelli implemented SAMOA, A tool that extracts and visualizes software facts
from the source code of apps. The tool provides a catalogue of views, at ecosystem or
single-app granularity, to examine apps from different perspectives [25].
Perssonand Andersson redesign and development of the iPhone application
Crew Alert. The application is intended for use by pilots as a tool for assessment,
logging and reporting of fatigue, to increase safety in the air. It also keeps track of the
user's schedule, and sleep pattern [26].
Albayrak et.al.designed an ES that make the determinations of hardware errors
of the computers with a rule basic approachis designed and developed Delphi7.0
programming language is used for the developmentof the system.This system provided
a help for solving the problemsof thecomputer users in the mostrapidlyand easily [27].

178
Carse designed a Veterinary Diagnosis Expert System for remote use on mobile
phone, the system given the limitations of screen resolution, processing ability, and the
limited advantage-set of their browsers, as well as in areas with weak cellular coverage.
Under testing, the system could diagnose a series of hypothetical test cases, and avoid
diagnosing a patient under conditions in which it could not confidently do so [28].
4. Implementation
4.1. Used rules in expert system
This ES application designed by android studio platform, the rulesthat has been
used in this application are the knowledge base data stored in cloud server and in
android studio these knowledge basesare called and presentedto usersthrough user
interface, for each result from user if user result is(Yes or No)thevalue will be
update.Therules used in ES is represented inFig 2.
Fig 2. Rules based on expert system on mobile android sample
At the beginning of starting the expert system user will go through some
filtration such as “user’s problem is with laptop or desktop?” or “which operating
system user have installed?” and “in which section you have problem (Hardware,
Software, or Network)?”.
In the application there is a part from ES called “Symptoms” which contain
ready answers stored in local SQLite database user will select symptoms according to
their problems until they will reach to their solution. This is provided if user does not
have internet access on their mobile except only in the first time when they install the
if (Does power flow to your computer ? ,YES) {value = Does screen turn on?}
else if (Does screen turn on? ,YES){ Does your computer restart immediately? }
else if (Does your computer restart immediately? ,NO) {Does screen show blue screen or
error message? }
if( Power flow to your computer ? ,NO) {Try to use another power adapter}
else if (Try to use another power adapter:does this helpful?, NO) { Try to reseat your RAM}
else if (Try to reseat your RAM: does this helpful?, NO) {Try turn on computer without
battery}

179
software this database will be download then they can use it as offline. Figure 4 shows
the sample of symptoms.
Fig 3.shows filtration process before starting ES.
Fig 3. User filtration before starting expert system
Fig.4. Offline symptoms
Parameters that I used in this expert system application are:
- Android studio platform (java)
- Parse server
- SQLite database
The application has two interfaces and figure 5shows the first interface ES
hierarchical structure.

180
Fig.5. the hierarchical structure of our expert system application.
The second interface shows symptoms,table 1 and table 2show the available
symptoms for computer problems in this study.
Table 1: Main Problem symptoms
Computer On Screen Off
Computer On Screen Error
Computer Off Screen Off
Beep Codes
Blue Screens
Network
Others
If user did not find the solution, then the ES request from user to upload the
problem with snap which take by mobile camera then a new problem will be send to
public view mode which is all members can see and according to the knowledge of each
member they can help user’s problem to find a solution. Figure 6 shows the
implementation of Mobile Expert System for solving computer problems.
Laptop Desktop
Computer Problem
Network
Software
Hardware
Network
Software
Hardware
Replace
your RAM
Try to
reinstall
the
program
Your Wi-Fi
driver
needs to
update
Power
Supplyde
ad
Show
missing
files?
NIC card
not working
try to
replace it

181
Table 2: Sub Problem according to main problem
Computer On Screen Off
Ram not working
VGA cable Desktop
Power Cable Desktop
Monitor Cable in Laptop
Graphic card not working
Monitor itself damage
Computer On Screen
Error
Boot MGR Missing
Boot Device Not Found
Windows Failed to start
Windows could not start because the following file is
missing or corrupt
<Windows root>system32hal.dll
Windows could not start because the following file is
missing or corrupt
WindowsSystem32ConfigSystem
Computer Off Screen Off Battery
Cable Connection for Desktop
Power Supply Desktop
Power adapter
Power button
Beeps
AMI: 1short DRAM refresh failure
AMI: 2 short Parity circuit failure
AMI: 3 short Base 64K RAM failure
AMI: 4 short System timer failure
AMI: 5 short Process failure

182
Fig.6. Expert System on android mobile application for solving computer problems
5. Conclusion
This study presented an expert system for solvingcomputer problems
andfaultsrunning on android smartphones. The system supports reasoning on
knowledgeusing an inference engine and a rule-base encompassing troubleshooting
production rules, inaddition to a user and an admin interfaces that simplify operating
and managing the system.TheES has two interface the first one is the expert system
which is decision making question and answer till user reach to its solution,The second
interface issymptoms which is solved computer problem user can select symptoms
according to their problems and find their solution, TheES allows the diagnosis of faults
arising in computers in anaccurate, rapid, systematic, efficient, and automated manner

183
relieving human technicians from theburden of regularly scheduled maintenance tasks
and routine support issues.
Acknowledgments
TheauthorsaregratefulforthesupportprovidedbyYüzüncüYılUniversity.
References
[1] Eddy N., 2011, Cloud Computing: Cloud, Mobile Apps, Public Storage Are Top IT
Trends for 2012 and Beyond: Gartner, http://www.eweek.com/c/a/Cloud-
Computing/Cloud-Mobile-Apps-Public-Storage- Are-Top-IT-Trends-for-2012-and-
Beyond-Gartner-130060/ [Access Date: 17.06.2016]
[2] Heriksen E., 2012, Angry Bids will be bigger than Mickey Mouse and Mario. Is
there a sucess formula for apps? Retrieved May 22, 2013, from MIT: The
Entrepreneurship Review: http://miter.mit.edu/
[3] Lefky, A., 2007, Number of Televisions in the US. Retrieved May 23, 2013, from
The Physics Factbook: http://hypertextbook.com/facts/2007/TamaraTamazashvili.shtml
[4] MinelliR., 2012, “Software Analytics for Mobile Applications”
[5] Allahverdi N., "UzmanSistemler. BirYapayZekaUygulaması", Atlas
Press, Ġstanbul, 248 p., 2002.
[6] Patel S. N. ,Abowd G. D.,Beyond Mobile Telephony: Exploring Opportunities for
Applications on the Mobile Phone Handset, University of Washington, Tech. Rep.,
August 2003.
[7] Tiwari M., Mishra B., 2011, Application of Cluster Analysis in Expert System – A
Brief Survey, 8, 342-346.
[8] Pilay K., Maunder E.,Naidoo K., 2009, Dietary intake and metabolic control of
children aged six to ten with type 1 diabetes mellitus in KwaZulu-Natal,South Africa
Journal Clinical Nutrition,22, 95-98.
[9]Adlassnig K., 2001, The Section on Medical Expert and Knowledge-Based Systems
at the Department of Medical Computer Sciences of the University of Vienna Medical
School, Artificial Intelligence in Medicine,21, 139-146.

184
[10] Bolloju N., Schneider C., Sugumaran, V., 2012, A knowledge-based system for
improving the consistency between object models and use case narratives,expert
systems with applications,39, 9398-9410.
[11] Clarke, K., O'Moore, R., Smeets, R., Talmon, J., Brender, J., Mcnair, P., Nykanen,
P., Grimson, J. AND Barber, B., 1994, A methodology for evaluation of knowledge-
based systems in medicine,Artificial Intelligence in Medicine,6, 107-121.
[12] Chen Y., Hsu C., Liu L., Yang S., 2012,Constructing a nutrition diagnosis expert
system, Expert Systems with Applications,39, 2132-2156.
[13] Alonso F., Caraça-Valente J.P., González A.L., Montes C., 2002, Combining
expert knowledge and data mining in a medical diagnosis domain,Expert Systems with
Applications,23, 367-375.
[14] Dogantekin E., Dogantekin A., Avcı, D.,Avcı, L., 2010,An intelligent diagnosis
system for diabetes on Linear Discriminant Analysis and Adaptive Network Based
Fuzzy Inference system: LDA-ANFIS, Digital Signal Processing,20, 1248-1255.
[15] Gomez F., Hull R., Karr C., Hosken B.,Verhagen W., 1992, Combining factual and
heuristic knowledge in knowledge acquisition,Telematics and Informatics,9, 297- 311.
[16] KeleĢ A., KeleĢA.,Yavuz U., 2011, Expert system based on neuro-fuzzy rules for
diagnosis breast cancer,Expert Systems with Applications,38, 5719-5726.
[17] VanRemoortere P., 1979, Computer-based medical consultations: MYCIN: E.H.
Shortliffe: Published by North-Holland, Amsterdam and N.Y., Mathematics and
Computers in Simulation,21, 385-386.
[18] Durkin J., 1990, Application of Expert Systems in Sciences, 9, 171-179.
[19] Al-Taani A. T., 2005,An expert system for car failure diagnosis. World Academy
of Science, Engineering and Technology, 1:12, 457-560.
[20] Giarratano J. C., 1993, CLIPS User’s guide. NASA Technical Report, Lyndon B
Johnson Center.
[21] Makhubele K.,2012, A Knowledge Based Expert System for Medical Advice
provision.
[22] Liu J, 2002,Mobile Map: A Case Study in the Design & Implementation of a
Mobile Application.

185
[23] Clarke D. E., Turban E., Wang P., 1994,Integrating expert systems and multimedia
for improved troubleshooting of the city of Los Angeles's computer hardware, Expert
Systemswith Applications,7: 3,441-449.
[24] SemertzidisK., 2013,Mobile application development to enhance higher education
lectures.
[25] MinelliR., 2012, Software Analytics for Mobile Applications.
[26] PerssonA.,AnderssonJ., 2013, Mobile Applications Design in Fatigue Risk
Management.
[27] AlbayrakM., TasdemirS., AllahverdiN.,2006, Expert System Approach to
Determine the Computer Hardware Failure, Proceedings of the Intern, AMSE
Conference, 28-30 August 2006, Konya, pp.559-563.
[28] Carse S.,2013, "A Veterinary Diagnosis Expert System for Remote Use".

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