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Integrated Architecture for Remote Experimentation MJ. Callaghan, J. Harkin, G. Prasad, TM. MeGinnity, LP. Maguire Intelligent System Engineering Laboratoty, Faculty of Informatics, University of Ulster, Magee Campus, Northland Rd, Deny, N. Ireland, BT48 7JL, UK Email [email protected] Abstract - Embedded systems are an integral part of industrial and domestic electronics necessitating educational institutions and other training providers to offer advanced embedded system courses. Eflective teaching in this area requires an interdependent approach combining theoretical material underpinned by practical laboratory experiments and individualized tutoring. Increasingly the courses on offer include web based distance education packages augmented by the provision of remote experimentation laboratories facilitating distant access’ to campus based physical resources. The degree of functionality and level of user access to remote laboratories has evolved in recent years expedited by advances in web applications and technologies. This paper details our recent work in this area focusing on the development of an architecture for an integrated. remote experimentation laboratory designed to meet the unique requirements of a complex, dynamic learning environment Keywords:Remoteexperimentation, embedded systems.

1 Introduction Remote experimentation offered as part of a web-based learning approach affords a number of critical benefits and for engineering distance education courses it is the only realistic method of performing many experiments. This approach allows remotely located students to complete laboratory assignments unconstrained by time or geographical considerations while in the process developing skills in the use of real systems and instrumentation. Additionally the remote laboratory approach facilitates greater access to expensive specialized test equipment and increases resource utilization. This paper describes recent work on the DIESEL project (Distance Lntemet-Based Embedded System Experimental Laboratory) a three year distance learning project funded by the EPSRC under the Masters Training Program and located at the Intelligent Systems Engineering Laboratory on the Magee campus of the University of Ulster, Northem Ireland. The objective of the DIESEL project is to develop remote-access laboratories for an Embedded Systems Design module on the MSc. Electronics and Software 0-7803-79152-7/03/$17.00 Q 2003 IEEE

Systems course. These remote experimentation facilities will complement and extend the existing Masters course by enabling postgraduate students to conduct practical experiments in Embedded Systems remotely via the Intemet. To date, an integrated collaborative learning environment has being developed and implemented. This environment facilitates co-operative experimentation between groups of geographically dispersed students and is centered around a series of advanced Embedded Systems experiments [3, 51. Aspects of this environment will be discussed in this paper. In addition to this, recent research related to the development of an automated intelligent help facility to aid students in the conduction of remote experiments is summarized and referenced. Section 2 of this paper summarizes our previous work in this area referencing our comprehensive review of the current state of the art in remote access laboratories and their deficiencies. An overview of aspects of an advanced remote-access embedded systems laboratory architecture that addresses the current deficiencies of both the authors’ and other institutes’ work is included. A typical user session is demonstrated and individual components of the environment and their functionality discussed. Section 3 briefly summaries further research which extends the functionality of the remote laboratory by the addition of an architecture for an automated intelligent help system in the context of remote experimentation of embedded systems. Section 4 provides a summary of the paper and discusses future work under development.

2 Integrated Remote Environment Previous work by the authors identified key deficiencies in existing remote experimentation laboratories and a full review is provided in previous publications [7, 3, 51. The main conclusion drawn from this review was that existing web based remote laboratories have tended to be crude in nature with only a fraction of the functionality of desktop based software packages and fail to fully utilize existing hardware and software resources 16, IO]. It was also clear that the effort and redevelopment costs involved in redesigning and adapting existing software tools and hardware equipment with the extra functionality needed for

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online access is substantial and beyond the expertise and budget of most teaching institutions. 2.1. Environment components In light of this a generic architecture and access+ontrol methodology for a remote laboratory that addresses the deficiencies of previous approaches was developed. This architecture efficiently integrates the instrumentation and experimental components of the system and is functionally comprised of three distinct but interconnected sections, leaming support resources, remote experimentation facilities and collaborative working and communication tools (Figure 2). A more detailed technical overview of this system is provided in the publication. The leaming support resources include extensive lecture and laboratory notes complete with audio/visual content providing theoretical background material and guidance for experiments. A comprehensive interactive multimedia user help system is available outlining and demonstrating general laboratory operation and the conduction of experiments. A discussion forum bas being added to the environment to allow students to discuss or comment on experiments, results and experiences with other students. A facility is alsoincluded to allow students to hook laboratory access time, either individually or in conjunction with another student for collaborative experimentation. This feature will be extended to allow students to request tutor assistance with experiments when needed. The remote experimentation facilities include the remote desktop feature which allows students to fully access all the resources of the distant workstations. A series of Macromedia Flash based executables provide a user interface front end to the e w n m e n t s which control the switching equipment on the remote workstations (Figure 8). This interface allows students to effectively wire up circuits and to connect test equipment for the taking of measurements or readings. Instrumentation control is provided by a series of virtual instrument interfaces built in Lahview to closely resemble the physical characteristics of a range of test equipment e.g. oscilloscopes, digital multi-meters and function generators (Figure 9). The Labview interfaces allow the student full access and control of the test equipment and instrumentation connected to the remote workstation. To provide feedback to the students during experiments, a series of Lahview interfaces have being designed to connect to data acquisition cards which take readings from a range of peripheral devices e.g. Stepper motors. This is augmented by the use of Web cams to provide visual feedback. The collaborative working, support and communication tools were built using the Macromedia Flash communication server (Figure 10). This aspect of the environment allows advanced interaction between

students or between students and course support staff via audiolvideo and text. The specific features of the communications tools include a general meeting room, a group meeting room and a note room. The general meeting room is open to all students and lecturers to discuss the laboratory experiments and is based around a video conferencing system augmented by whiteboard facilities. The group meeting room is experiment specific and is designed to allow student to work collaboratively either with other students or laboratory support staff as necessary. The note room allows students to record and edit laboratory notes together. 2 2 DIESEL architecture The DIESEL architecture is a distributed application based around the Microsoft .net framework. It is comprised of three main components, the database, the client application and the server application (Figure 3). The database is used to store the list of authorized users, their passwords, the list of bookings made and a list of available experimental workstations. The client application is an executable which when installed on the student’s machine facilitates remote access to the experimental environment. The server apphation is a shell like Framework which calls each of the individual components of the environment together and is located on the experimental workstation.

2.3 User session overview The first stage in accessing the remote laboratory is to install the DIESEL client on the remote machine. The next step is to reserve a time slot on the remote laboratory (Figure 1).

Figure 1. Remote environment online booking system Once this process is completed the user is granted access

to the Remote laboratory in a number of stages. The first stage of this process is to launch the DIESEL client.

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c Remote experimentation

facilities

Collabomtive working and communication tools

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Circuit interface front ends (Circuit setup & manipulation)

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Virtual instrument interfaces (Labview)

Remote assistance and application sharing facility

Laboratory reservation

Webcams (Visual feedback)

Lecture and laboratory notes (AudioNideo) Interactive multimedia user help (Macromedia flash demos)

Instant messaging

Figure 2 DIESEL advanced remote learning environment

Figure 3 Client and booking system overview

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begin to configure the laboratory to cater for the experiment selected. Lecture material and slides appropriate to the experiment will be loaded into the environment and the switching matrix will connect the chosen experimental board to the instrumentation. When the client is loaded the user can select which aspect of the environment to access using a tabbed menu navigation system,(Figure7).

Figure 7. Remote environment navigation system Figure 4. Student launches DIESEL client The next step is to select an experimental range. In this case the user selects the Microcontroller based experiments and then a specific experiment in this range is selected (Figure 4-6).

Figures 8,9 and 10 show the virtual circuit interface, virtual instrument interface and communications components of the environment

Figure 8. Virtual circuit interface Figure 5. Student selects from experimental range

Figure 6. Student selects individual experiment Figure 9. Virtual instrument interface

As the student selects options at each stage of the DIESEL client startup, the workstation being accessed will 4825

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Figure IO. Communications environment This section of the paper presented a collaborative and supported learning environment for remote experimentation. A structured environment for remote experimentation was introduced which included comprehensive teaching and support material and integrated the ability to complete advanced embedded system experiments remotely with the facility of collaborative student experimentation and remote tutoring when required.

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Intelligent tutoring Circuit Interface

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The architecture and components of the system presented provide students with a comprehensive integrated remote experimentation environment. However autonomous learning environments by nature offer minimal educator assistance and it is inevitable that at some stage of the experimental process context specific help or assistance will be required by the student [2,8]. Figure 11 presents an architecture currently under development for the automated intelligent provision of help and assistance to students in the context of remote experimentation. The system’s operation is centered on a case based reasoning system implemented in Caspian [ 9 ] . The approach taken is to monitor and record status data from a number of sauces (Data acquisition card, circuit connection status) while students are carrying out experiments. When help is requested this data is correlated and used as an input to the reasoning system. Further analysis of this data in the context of the current experiment (Closest case retrieval) will identify possible setup problems and configuration errors and inform the student of possible solutions. Fnrther details on this aspect of the DIESEL project can be found in this publication [4]. Figure 12 shows a typical case representation. In this particular application the experiment involved the reading and witing of values to addresses in RAM on the HCI 1 microcontroller. The problem identified in this instance was that the student neglected to reset the processor resulting in the executing program not king properly initialized. The Flash circuit interface was redesigned and a section added to allow the dynamically updated context specific help to be displayed.

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Case instance [PR_(F)_ICEUT)_ITL_(~~~V_(F)_DBV_o_ Solution is reset processor

Figure 11. System architecture

Figure 12. Case representation 4826

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[2] Brusilovsky, P. (1995) “Intelligent tutoring systems for World-Wide Web”. R. Holzapfel (-4.) Proceedings of Third International WWW Conference, Darmstadt, Dannstadt, April 10-14, 1995, Franrihofer Institute for Computer Graphics, pp. 42-45.

Figure 13 shows the redesigned virtual circuit interface with added remote help facility. This work is in the very early stages at the moment but initial results have being promising. Investigation is currently underway in applying combinations of a range o f intelligent techniques to this problem and of adapting this system for use with more complex experimentation circuitry.

[3] Callaghan, M.1, Harkin, I, McGinnity, T.M, Maguire, L.P “Collaborative Environment for Remote Expmimentation”, 2003 International .Conference Microelectronic systems Education 1 2 lune 2003 Anaheim, California (2003) 157 -162 [4] Callaghan, M.1, Harkin,I, McGinnify, T.M, Mag&, L.P: “Adaptive Intelligent Environment for Remote Experimentation”, To appear 2003 IEEE/WlC International Conference on Intelligent Agent Technology (IAT 2003).

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[SI Callaghan, M.1, Harkin, 1, McGinnity, T.M, Maguire,L.P “An Internet-based Methodology for Remotely Accessed Embedded Systems”, IEEE Conference on Systems, Man and Cybemetics (2002) 157 -162

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Figure 13. Redesigned interface with intelligent help feature

4 Discussion and conclusion A review and discussion of recent work undertaken by the authors in addressing issues related to the implementation of remote access experimental laboratories has been presented. The approach and architectures described offers considerable benefits in t e m of full access to remote resources and cost redevelopment saving. Furthermore the student’s overall experience has been further enhanced and improved by the addition of an intelligent context specific help system which although in the early stages of development shows encouraging results.

Acknowledgements

[6] Gillet D. et al., 2000, “Advancesin Remote Experimentation”, 19th American Control Conference,ACC’2000,ZO -25

[7] Harkin, I. Callaghan, M.]; McGinnity, T.M; Maguire, L.P “An Internet based Remote access Experimental Laboratory for Embedded Systems”, IEE Symposium on Engineering Education, Vol. 1,2002, pp. 18/1 - 6. M., Kato, Y., Touhei, H., and Fukuhara, Y. (1997) “Architecture of an intelligent tutoring system OD the W.El d. Boulay and R. Mizoguchi (eds.) Artificial Intelligence in Edncation: Knowledge and Media in Leaming Systems. (Pmceedings of AI-ED97, World Conference on Artificial Intelligence in Education, Kobe, Japan, 18-22 August I997)Amsterdam: IOS, pp. 39-46.

[XI Nakabayashi, K., Many-,

[9] Pegler, I., & Price, C.J. (1996) “Caspian: A freeware MSB cased reasoning shell”., Proceedingsof the 2nd UK Workshop on CawBased Reasoning. Watson, I. (Ed,), Salford University, salford, UK [IO] Shen H. et al., 1999, “Conductkg Laboratory Experiments over the Internet”,IEEE Trans. on Education, 30,191-199

The authors acknowledge the financial support of the EPSRC (UK) under the Masters training program (Refmewe GRfN26753).

References [I] Brusilovsky, P. (1996) ”Methods and techniques of adaptive hypermedia”. P. B N S ~ O Vand S ~I. ~Visalia (eds.), Spec. lss. on Adaptive Hypenext and Hypermeda, User Modeling and UserAdapted Interaction 6 (2-3), 87-129.

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