Context Management for Supporting Context-aware Android Applications Development
Author(s) -
Hanan Elazhary,
Alaa Althubyani,
Lina Qadir Ahmed,
Bayan Alharbi Alharbi,
Norah Mutlaq Alzahrani,
Reem Almutairi
Publication year - 2017
Publication title -
international journal of interactive mobile technologies (ijim)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.316
H-Index - 16
ISSN - 1865-7923
DOI - 10.3991/ijim.v11i4.6952
Subject(s) - computer science , android (operating system) , context management , mobile device , context (archaeology) , raw data , context awareness , mobile computing , process (computing) , ubiquitous computing , human–computer interaction , world wide web , embedded system , operating system , programming language , philosophy , paleontology , linguistics , biology , phone
Building context-aware mobile applications is one of the most ambitious areas of research. Such applications can change their behavior according to context or perform specific tasks in specific contexts. Regardless of the application, all context-aware mobile applications share the need to retrieve and process context information. This paper presents a Context Management tool for the Android platform (ACM). ACM allows easy access to internal on-board mobile sensors and hardware features extracting corresponding raw data. Raw context is processed into higher-level more human-readable context that is provided seamlessly to the mobile applications. Different methods are used for this purpose including fuzzy classifiers. Since different mobiles have different sensors and hardware features, ACM can adapt to the mobile device by deactivating access to unavailable ones. Information regarding the available sensors and hardware features and their specifications can also be queried. Additionally, applications can request notifications regarding context change or specific context values. In addition to providing developers with supporting classes and methods, ACM is accompanied by an application that allows developers to examine its functionality and capabilities before using it. The application can be also used to examine the readings of the different sensors in different situations and thus calibrate them as needed. Additionally, it can be used to modify and personalize default interpretations of raw context values to high-level ones. ACM has been tested empirically and the results show extreme interest of context-aware mobile application developers in its promising capabilities and that it is conducive to facilitating, speeding up and triggering development of many more of such applications.
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