Modeling Pervasive Context-Aware Mobile Phone

Berhanu, Abebe Dagnaw (2015) Modeling Pervasive Context-Aware Mobile Phone. Masters thesis, Addis Ababa University.

[img] PDF (Modeling Pervasive Context-Aware Mobile Phone)
Berhanu, Abebe.pdf - Accepted Version
Restricted to Repository staff only

Download (1MB) | Request a copy


The IT industry has shown great advancement in building various technological resources in the past few years. Smart phones with ever increasing processing power having the capacity that almost matches personal computers are being built. Although mobile phones have achieved their original purpose of interconnecting people, facilitating business, recreation, intelligence and emergency communication, they have become a main source of distraction for humans. One of the main problems of modern day smart phones is that battery capacity has not shown the same exponential growth like processing power, memory and storage. For modern day people, it is getting increasingly difficult to do our work without the help of mobile phones. Battery consumption is also increasing with our increasing dependency on those devices and it has to be managed. If mobile phones can determine the state of their user by observing different contextual information, it would be easy to adapt the mobile phone to the user’s activities and reduce distraction while preserving battery in the process. In this study, we have proposed and developed a model for a pervasive context-aware mobile phone. Context information is collected from different sources and preprocessed to have a standard metrics. Ontology based context modeling approach has been used to serialize, store and process the context information in the mobile phones. Appropriate context reasoning approaches have been studied and prediction of the user’s activity from the context information collected in context acquisition has been done. A prototype application has been developed using appropriate tools and techniques for the home domain. The prototype application has been tested under different circumstances on different devices and it has been found to be accurate 78% of the time.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Pervasive/Ubiquitous Computing, Context, Context-awareness, Mobile Phones, NFC
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Divisions: Africana
Depositing User: Selom Ghislain
Date Deposited: 18 Sep 2018 09:01
Last Modified: 18 Sep 2018 09:01

Actions (login required)

View Item View Item