Methodology for mobile devices characteristics recognition - CiteSeerX

International Conference on Computer Systems and Technologies - CompSysTech’07

Methodology for mobile devices characteristics recognition Evgeniya Georgieva, Tsvetozar Georgiev Abstract: This paper describes a methodology for mobile devices characteristics recognition. The proposed main stages are: analysis, selection, program realisation, implementation and evaluation. The basic activities for each stage are determined. The methods which can be used for mobile device recognition are examined. The proposed methodology is used successfully during the development of a system for mobile foreign language learning. Key words: Mobile Learning, Mobile Device Recognition, Education.

INTRODUCTION The mobile learning (m-Learning) is one of the most advanced trends in the education area. One of its main features is that it is realized by the use of mobile devices (Notebook computers, Personal Digital Assistants (PDAs), smart phones or cell phones). These devices differ vastly from each other by their hardware and software capabilities – processor power, memory size, screen resolution, operating system, web browser, supported script languages, supported file formats, etc. The existing m-Learning can be divided in three main groups – off-line m-Learning, where in the mobile device memory a specially developed learning content or stand-alone application is loaded and there is no need of a permanent wireless connection to Mobile Learning System (MLS); on-line m-Learning, where the learner realizes a permanent wireless connection to such system; m-Learning where both on-line and off-line mobile learning is ensured (the access to one part of learning materials is on-line while the access to the remaining materials is off-line). Very important for the realization of the second and third group m-Learning is the correct recognition of the users’ mobile devices characteristics. This problem is topical because on the one hand new models of mobile devices and new versions of web browsers appear continuously and on the other hand it is necessary the efficiency of the mobile learning systems with these devices and web browsers to be supported. In the literature sources different solutions are described but they do not cover all aspects of problems. For example in [1, 3, 4] methods for mobile devices characteristics recognition used in a particular system are examined, but they do not concern the problem of actualization of the supported devices and eventually the use of new methods for device recognition. The purpose of this paper is to substantiate a methodology for mobile devices characteristics recognition which to be used in the development process of mobile learning systems, as well as to support their efficiency with new devices. LAYOUT One of the most important stages of the operation of each MLS is adaptation of the learning content depending on the user device characteristics. The big variety of mobile devices leads to the use of different methods for verification and determination of their characteristics. That’s why the adaptation stage must be preceded by the stage of characteristics recognition. They depend on the type of mobile device (Notebook, PDA, smart phone or cell phone), the operating system (Windows Mobile, Palm OS, Apple OS X, Blackberry OS, etc.), the web browser (micro browser), etc. METHODOLOGY The proposed methodology for mobile devices characteristics recognition includes the following stages (Fig.1):

- IV.2-1 -


• • • • •

Analysis; Selection; Program realization; Implementation; Evaluation.

Fig.1. Methodology for mobile devices characteristics recognition

1. Analysis stage During this stage an analysis of existing mobile devices, web browsers and methods for mobile devices recognition must be done. The HTTP headers values for different mobile devices also can be investigated using corresponding web sites [8, 9, 11]. If the purpose is to update existing MLS an analysis of new models of mobile devices, new versions of web browsers and new methods must be done. A study of the potential users must be done in order to estimate if the supported by the MLS mobile devices cover the possessed by the users and if there is need to support new devices. - IV.2-2 -


2. Selection stage The first step which must be done is to define the types of mobile devices which will be supported - Notebooks, PDAs, smart phones, cell phones. During this selection the potential users, the mobile devices they posses and prefer to use, must be taken into account. When mobile devices like Notebooks, PDAs or smart phones must be supported by the system, it is necessary to select and test several of the most often used web browsers because they have different functional capabilities [12]. Table 1 shows different types of mobile devices, their operation systems and some of the popular web browsers which can be used. Table 1 Mobile device Notebooks

PDAs

Smart phones Cell phones

Operation system Windows Linux Windows Mobile Palm OS Linux BlackBerry Windows Mobile Symbian Apple OS X RTOS

Web browser Internet Explorer, Mozilla Firefox, Opera, Netscape, Amaya Mozilla Firefox, Opera, Netscape, Konqueror, Amaya MS Mobile Internet Explorer, Minimo, Opera Mobile, PIE Plus, ftxPBrowser, MultiIE, NetFront, ThunderHawk, Deepfish WebPro, Xiino, Minuet Browser, Universe NetFront BlackBerry Internet Explorer, Opera Mini, ThunderHawk, Deepfish WebViewer, Opera, ThunderHawk, NetFront Safari Micro browser, Compact NetFront Plus

On the next step the characteristics of mobile devices which influence on the learning content adaptation have to be selected. The main characteristics on which the correct adaptation depends are: • Screen resolution. This is a very important characteristic during the process of adaptation because at present there is big variety of screen resolutions – from small ones of the cell phones to the large ones of Notebooks [5]. • Screen mode (portrait or landscape). Many new PDA devices support switching over between portrait and landscape screen mode. That’s why it is important to determine not only the screen resolution but the screen mode too. • Supported markup and script languages. The determination of these characteristics is important especially for adaptation of (X)HTML web pages which use JavaScript, because not all web browsers for PDAs and smart phones support all JavaScript functions (for example MS Internet Explorer and MS Deepfish [10]). The mobile phones which respond to the standard WAP 1.x support WML and WMLScript, while those of them which respond to the standard WAP 2.0 support XHTML. • Supported multimedia file formats. In order to play appropriate multimedia elements on a mobile device with a particular web browser it is important to determine which of them are supported. The method/methods for recognition of the defined mobile devices characteristics have to be selected too. Currently, servers and proxies can determine the identity of a particular device using the request header field in the HTTP protocol. In addition there are three alternative methods: the W3C Composite Capabilities/Preferences Profiles (CC/PP), the WAP User Agent Profile (UAPROF) standard and Wireless Universal Resource File (WURFL). • HTTP User-Agent Header The web browsers and servers use the HTTP protocol to transfer information on the WWW. It includes a mechanism for content presentation which browsers can accept. The server decides what kind of information to send depending on the device profile. Each

- IV.2-3 -


HTTP request includes Accept Header [13], which indicates the types of data, which the browser can accept. In addition to the Accept Header the client sends User-Agent Header [13]. It identifies the client device and contains information about the browser, operating system and sometimes hardware information. As the number and the kind of devices, which have internet connection, constantly grow up, the need of content designed to different devices also grows up. That’s why the information from User-Agent Header is not sufficient. • Composite Capabilities / Preferences Profiles (CC/PP) The specification Composite Capabilities/Preferences Profiles (CC/PP) from World Wide Web Consortium [6] documents a standard way, which allows devices to transmit their configuration details and capabilities (screen resolution, audio characteristics, frequency band) to web servers. CC/PP specification provides universal profile that describes the devices’ characteristics. CC/PP is designed to be independent. The connected specifications as UAPROF, unlike CC/PP, define a variety of dictionaries describing the devices’ characteristics. • WAP User Agent Profile (UAPROF) Another way to identify the user device profile is using the User Agent Profile [14] specification. It is a specific CC/PP dictionary describing mobile devices and defining an effective way for CC/PP content transition via wireless nets. Mobile phones conformed to UAPROF specification provide CC/PP description of their characteristics on a server. Content servers, gateways and proxy servers can use this information and optimize the content for the device of a consumer. The information is in XML format. When a mobile device sends request to server, it also sends an URL address to its mobile profile. This is carried out by adding of X-Wap-Profile Header to the request. This header indicates the server where to find the device profile. The content server extracts the necessary information for the client from device profile repository and can store it, so that it can be used later. WAP gateway or HTTP proxy must support working of UAPROF header. • Wireless Universal Resource File (WURFL) The mobile device profile can be identified using the open source project Wireless Universal Resource File (WURFL) [15]. It is a configuration file containing information about the features of mobile devices offered on the market. The main goal of the developers of this file is to support maximum information for existing wireless devices that have an access to WAP pages. WURFL project has some advantages compared to UAPROF: 1) WURFL file can be stored on a server and it is not necessary to be accessed remotely; 2) Each device characteristics can be shaped. 3. Program realization stage This stage includes the program realization of the selected method/methods for mobile devices characteristics recognition. Since the proposed methodology is intended for systems which support on-line learning, the recognition must be realized from the server side and for the logic description has to be used a selected script language (PHP, JSP, ASP, etc.). The recognition can be realized using the algorithm shown in Fig.2. Initially verification about a particular device type (for example Notebook) is done. If its characteristics are not recognized it is accepted that this is other device type and it is verified. The process continues until the mobile device and its characteristics are recognized. The profile of the recognized device type should be able to be sent as a parameter to the module for learning content adaptation of MLS. The program realization is accompanied with the experimental investigations with the selected mobile devices, web browsers and characteristics. During these tests web sites which return information about some device characteristics [7] can be used in order to verify the correct operation of the program. An analysis if the selected characteristics are recognized has to be done. Otherwise another recognition method has to be applied and programmed. - IV.2-4 -


Fig.2. Activity diagram of device recognition process

4. Implementation stage On this stage the program realization of the selected methods for mobile devices characteristics recognition is integrated in a Mobile Learning System. Fig.3 shows a user request for learning content via mobile device and how this request is processed by the system. This figure depicts also the interaction between the module for device capabilities recognition and the module for learning content adaptation.

Fig.3. Device recognition module as a part of Mobile Learning System

5. Evaluation stage This stage includes the evaluation of Mobile Learning System efficiency with different devices. The purpose is to verify if the mobile device recognition is correct. If the particular device type is not correctly identified the realization of the recognition algorithm must be analyzed and revised. CONCLUSIONS AND FUTURE WORK The realization of mobile devices characteristics recognition is a serious challenge if a Mobile Learning System will support different types of mobile devices. In this case many and different factors must be taken into consideration. The proposed methodology makes - IV.2-5 -


this realization easier defining a clear actions sequence. It is successfully used during the development of module for mobile devices recognition which ensures an appropriate learning content adaptation in the system for mobile foreign language learning FLAGMAN. The methodology can be used not only for devices recognition by a new developed MLS, but also when an existing one has to support new mobile devices. REFERENCES [1] Ally, M. et al, An Intelligent Agent for Adapting and Delivering Electronic Course Materials to Mobile Learners, www.mlearn.org.za/CD/papers/Ally-an intelligent.pdf. [2] Georgieva, E., Ts. Hristov, Design of an e-Learning Content Visualization Module, Proceedings of the Third International e-Learning Conference, September 7-8, Coimbra, Portugal, 2006, pp.201-204. [3] Muller, J. et al, Developing Web Applications for Mobile Devices, Proceedings of the First International Conference on Distributed Frameworks for Multimedia Applications (DFMA'05), Besançon, France, 2005, pp.346-350. [4] Tong, M. et al, A Novel Content Adaptation Model under E-learning Environment, fie.engrng.pitt.edu/fie2006/papers/1094.pdf. [5] Yoo, H., S. Cheon, Visualization by information type on mobile device, Proceedings of the 2006 Asia-Pacific Symposium on Information Visualisation - Volume 60, Tokyo, Japan, 2006, pp.143-146. [6] Composite Capability/Preference Profiles, http://www.w3.org/TR/CCPP-structvocab/. [7] HTTP Header Viewer, http://www.ericgiguere.com/tools/http-header-viewer.html. [8] List of Browser User-Agents for Nokia devices, http://wiki.forum.nokia.com/index.php/Known_USER-AGENTS_(Mobile_ID). [9] List of User Agent Strings, http://www.useragentstring.com/pages/ useragentstring.php. [10] Microsoft Deepfish, http://labs.live.com/deepfish/. [11] Mobile Browser ID (User-Agent) Strings, http://www.zytrax.com/tech/web/ mobile_ids.html. [12] Pocket PC Web browsers – the complete roundup, http://www.aximsite.com/boards/ showthread.php? p=780770. [13] Tutorial about Detecting User Agent Types and Client Device Capabilities, http://www.developershome.com/wap/detection/. [14] User Agent Profile Approved Version 2.0, www.openmobilealliance.org/ release_program/ docs/UAProf/V2_0-20060206-A/OMA-TS-UAProf-V2_0-20060206-A.pdf [15] WURFL, http://wurfl.sourceforge.net/. ABOUT THE AUTHORS Evgeniya Georgieva, MSc, Department of Computing, University of Rousse, Phone: +359 82 888 577, E-mail: [email protected] Assoc. Prof. Tsvetozar Georgiev, PhD, Department of Computing, University of Rousse, Phone: +359 82 888 276, E-mail: [email protected]

- IV.2-6 -