Smart Learning Services Based on Smart Cloud Computing Svetlana Kim, Su-Mi Song and Yong-Ik Yoon Department of Multimedia Science, Sookmyung Women’s University, Chungpa-Dong 2-Ga,Yongsan-Gu 140-742, Seoul, Korea Communication: Smart Learning Services Based on Smart Cloud Computing ; Sensors 2011, 11(8), 7835-7850 Present : 陳政宇 Date：2012/06/01

Abstract Context-aware technologies can make e-learning services smarter and more efficient a service architecture model is needed We suggest the elastic four smarts (E4S) smart pull, smart prospect, smart content, and smart push The E4S focuses on meeting the users’ needs provides personalized and customized learning services

Outline 1. Introduction 2. Smart Cloud Computing 3. The SCC 4. Implementation 5. Conclusion

1. Introduction(1/4) Traditionally e-learning were limited Smart learning offers personalized contents, easy adaptation , convenient communication environment and rich resources still not complete

1. Introduction(2/4) For example To resolve this problem not allocate necessary computing resources difficulty in interfacing and sharing data with other systems duplication and low utilization of existing teaching resources To resolve this problem use cloud computing to support resource management

1. Introduction(3/4) cloud computing environment provides the necessary foundation integration of platform and technology integrates teaching and research resources distributed over various locations anywhere at anytime

1. Introduction(4/4) the existing cloud computing technologies are only passively responsive to users’ needs. propose a smart cloud computing (SCC) model for smart learning contents through the E4S SCC can provide customized contents to each user

2. Smart Cloud Computing(1/3) The SCC for short based on E4S has the capability to provide a smart learning environment. encourages learning system standardization and provides a means for managing it.

2. Smart Cloud Computing(2/3) A traditional e-learning system can display single content on a single device or multiple contents on one device.  The SCC can deliver s-learning to the users so they can use multiple devices to render multi learning contents.  The multi learning contents can be played in different devices separately to form a “virtual class”.

2. Smart Cloud Computing(3/3)  For this, the SCC uses context-aware sensing. Sensing through the location and IP address of each device. Each customized learning contents may differ in modality (i.e., text-based, audio, video, etc.), capability (i.e., bandwidth), and timing (i.e., types of synchronization).

3. The SCC 3.1. Context-Aware Module 3.2. The Elastic 4S (E4S) System 3.2.1. Smart Pull 3.2.2. Smart Prospect 3.2.3. Smart Content 3.2.4. Smart Push

3.1. Context-Aware Module(1/3) The context-aware model must automatically deduce the actual situation from the user’s behavior. based on a hybrid situation that consists of the user situation and the physical situation. includes static factors and dynamic factors that describe the hybrid situation.

3.1. Context-Aware Module(2/3)

3.1. Context-Aware Module(3/3)

3.2. The Elastic 4S (E4S) System 3.2.1. Smart Pull 3.2.2. Smart Prospect 3.2.3. Smart Content 3.2.4. Smart Push

3.2.1. Smart Pull(1/3) The Smart Pull identifies a right action service in fusion learning DB based on the user action in context model. The fusion learning DB consists of various multimedia learning materials such as video, text, PPT and image scattered in different learning DB.

3.2.1. Smart Pull(2/3) For Example a user action in the context model requests the topic of “multimedia” The Smart Pull extracts a related action of “multimedia” in fusion learning DB

3.2.1. Smart Pull(3/3)

3.2.2. Smart Prospect(1/3) The Smart Prospect is mainly responsible for describing the contents in ActionNo time, memory, resolution and supported application types. To access the information in ActionNo, the Smart Prospect uses a Semantic Description using of UVA (Universal Video Adaptation) model that has been developed by Yoon

3.2.2. Smart Prospect(2/3) The UVA model The Semantic Description uses the video content description in MPEG-7 standard and MPEG-21 multimedia framework. The Semantic Description provides the accurate and meaningful information for the fusion content. uses XML, ontology and Resource Description Framework (RDF) that help define fusion content clearly and precisely. also represents systematic information about the contents.

3.2.2. Smart Prospect(3/3) The role of the ontology formally describe the shared meaning of vocabulary used. describes the basic fusion learning contents of some domain (e.g., history of science). includes the relations between these concepts and some basic properties. Based on the ontology, all learning content in the ActionNo are associated each other. For example, the description of the video content used in semantic description can be related to the scenes of video.

represents playback time of the entire video content indicates supporting types for some application, such as video, image, PPT or text. specifies memory and resolution information of video content, respectively represents the playback time of a shot in the video content

3.2.3. Smart Content (1/3) The Smart Content generates the fusion content for the user’s device using the harmony adaptation. The harmony adaptation has two steps Fusion Content Adaptation presents the synchronization among the fusion contents in ActionNo. Device Synchronization process performs the process of synchronization between devices.

3.2.3. Smart Content (2/3) The process of synchronization between multiple devices creates a channel for each device the fusion contents can be played on multi devices at the same time The Device Synchronization uses SyncML (Synchronization Markup Language) to set the synchronization between devices.

3.2.3. Smart Content (3/3) The SyncML an international standard language matching data between different devices and applications at any network company . Through the synchronization between devices, the adapted contents can be used in Smart Push step.

3.2.4. Smart Push (1/2) As for the content delivery, the situation analyzer will be used. the situation analyzer uses the physical situation information to find the related details of the contents and devices If the details of a device and contents are the same, a link can be established

3.2.4. Smart Push (2/2) The Smart Push delivers a complete set of smart contents to the user using terminal’s AP (Access Point) and MAC-Address

4. Implementation (1/2) fusion content generation and synchronization shows a synchronization of the video and audio can be played in the preview the progress of the synchronization shows the synchronization with other fusion media

4. Implementation (2/2) delivered the synchronized fusion media to two different devices

5. Conclusions In this paper, we have introduced the use of context-awareness for user behavior and a way to deliver the corresponding contents to the users. As a future work, the protocols for smart cloud computing and domain specific ontology will be investigated.