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Contribution to the Setting of an Online Platform on Practical Application for the Science, Technology, Engineering and Mathematics (STEM): The Case of Medical Field

  • Kéba GueyeEmail author
  • Ulrich Hermann Sèmèvo Boko
  • Bessan Melckior Degboe
  • Samuel Ouya
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 916)

Abstract

The objective of this paper is to contribute to the improvement of distance education in medicine by offering a platform for practical work. To do this, we combine the intelligence of WoT with the power of WebRTC. This platform, based on the WebRTC Kurento multimedia server and the Web of Things (WoT), allows teachers and students to do remote labs. Kurento Media Server (KMS) allows you to create media processing applications based on the pipeline concept. The Web of Things (WoT), considered a subset of the Internet of Things (IoT), focuses on standards and software frameworks such as REST, HTTP and URI to create applications and services that combine and interact with a variety of network devices. To prove the relevance of our approach, we described a scenario where the teacher initiates a medical consultation TP with any patient on which sensors are placed. Patient data is visible in real time for all students who follow the teacher’s comments/explanations and also interact. However, our experimental results may be relevant for other STEM disciplines.

Keywords

Practical work E-learning Medicine WoT KMS WebRTC 

Notes

Acknowledgment

The authors kindly thank colleagues who helped them to achieve this paper, especially the members of RTN laboratory.

References

  1. 1.
    Coti, C., Loddo, J.V., Viennet, E.: Practical activities in network courses for MOOCs, SPOCs and eLearning with Marionnet. In: International Conference on Information Technology Based Higher Education and Training, Lisbon, 11–13 June, pp. 1–6 (2015)Google Scholar
  2. 2.
    Elawady, Y.H., Talba, A.S.: A general framework for remote laboratory access: a standarization point of view. In: IEEE International Symposium on Signal Processing and Information Technology, Luxor, 15–18 December, pp. 485–490 (2010)Google Scholar
  3. 3.
    Hashemian, R., Riddley, J.: FPGA e-Lab, a technique to remote access a laboratory to design and test. In: Proceedings of IEEE International Conference on Microelectronic Systems Education: Educating Systems Designers for the Global Economy and a Secure World, San Diego, CA, 3–4 June, pp. 139–140 (2007)Google Scholar
  4. 4.
    Lee, T.H., Lee, H.C., Kim, J.H., Lee, M.J.: Extending VNC for effective collaboration. In: Proceedings of IFOST-2008-3rd International Forum on Strategic Technologies, Novosibirsk-Tomsk, 23–29 June, pp. 343–346 (2008)Google Scholar
  5. 5.
    Tawfik, M., Salzmann, C., Gillet, D., Lowe, D., Saliah-Hassane, H., Sancristobal, E., Castro, M.: Laboratory as a service (LaaS): a novel paradigm for developing and implementing modular remote laboratories. Int. J. Online Eng. 10, 13–21 (2014)CrossRefGoogle Scholar
  6. 6.
    Willems, C., Meinel, C.: Users clients players problem terminal assignment B. Queuing queue terminal assignment problem C. Other methods A. Time slotting time reservation. Int. J. Online Eng. 4, 179–185 (2008)Google Scholar
  7. 7.
    Bochicchio, M., Longo, A.: Hands-on remote labs: collaborative web laboratories as a case study for it engineering classes. IEEE Trans. Learn. Technol. 2, 320–330 (2009)CrossRefGoogle Scholar
  8. 8.
    Magrabi, F., et al.: Home telecare: system architecture to support chronic disease management. In: Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 4 (2001)Google Scholar
  9. 9.
    Lau, C., et al.: Asynchronous web-based patient-centered home telemedicine system, vol. 49, 12 (2002)Google Scholar
  10. 10.
    Zheng, H., Davies, R.J., Black, N.D.: Web-based monitoring system for home based rehabilitation with stroke patients. In: 18th IEEE Symposium on Computer Based Medical Systems (CBMS’05), June 2005, pp. 419–424Google Scholar
  11. 11.
    Chiang, C.Y., et al.: An efficient component-based framework for intelligent home-care system design with video and physiological monitoring machineries. In: Fifth International Conference on Genetic and Evolutionary Computing, Aug 2011, pp. 33–36Google Scholar
  12. 12.
    Pierleoni, P., et al.: An innovative webrtc solution for e-health services. In: IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom), Sept 2016, pp. 1–6Google Scholar
  13. 13.
    Al-Taee, M.A., et al.: Web-of-things inspired e-health platform for integrated diabetes care management. In: IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT), Dec 2013, pp. 1–6Google Scholar
  14. 14.
    Azevedo, J.A., Pereira, R.L., Chainho, P.: An api proposal for integrating sensor data into web apps and webrtc. In: Proceedings of the 1st Workshop on All-Web Real-Time Systems, ser. AWeS’15, pp. 8:1–8:5. ACM, New York, NY, USA (2015). http://doi.acm.org/10.1145/2749215.2749221
  15. 15.
    Garcia, B., Lopez-Fernandez, L., Gallego, M., Gortazar, F.: Kurento: The swiss army knife of WebRTC media servers. IEEE Commun. Stand. Mag. 1(2), 44–51 (2017)CrossRefGoogle Scholar
  16. 16.
    Guinard, D., Trifa, V.: Building the Web of Things. Manning Publications Co (2016)Google Scholar
  17. 17.
    Truică, C.O., Boicea, A., Trifan, I.: CRUD Operations in MongoDB. In: International Conference on Advanced Computer Science and Electronics Information, pp. 347–348 (2013)Google Scholar
  18. 18.
    Chopade, M.R.M., Dhavase, N.S.: Mongodb, couchbase: Performance comparison for image dataset. In: 2017 2nd International Conference for Convergence in Technology (I2CT), Mumbai 2017, pp. 255–258 (2017)Google Scholar
  19. 19.
    Jose, B., Abraham, S.: Exploring the merits of nosql: A study based on mongodb. In: 2017 International Conference on Networks & Advances in Computational Technologies (NetACT), Thiruvanthapuram, 2017, pp. 266–271 (2017)Google Scholar
  20. 20.
    Patil, M.M., Hanni, A., Tejeshwar, C.H., Patil, P.: A qualitative analysis of the performance of MongoDB vs MySQL database based on insertion and retriewal operations using a web/android application to explore load balancing—Sharding in MongoDB and its advantages. In: 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam 2017, pp. 325–330 (2017)Google Scholar
  21. 21.
    Kumar, J., Garg, V.: Security analysis of unstructured data in NOSQL MongoDB database. In: 2017 International Conference on Computing and Communication Technologies for Smart Nation (IC3TSN), Gurgaon, India, 2017, pp. 300–305 (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Kéba Gueye
    • 1
    Email author
  • Ulrich Hermann Sèmèvo Boko
    • 1
  • Bessan Melckior Degboe
    • 1
  • Samuel Ouya
    • 1
  1. 1.LIRT Laboratory, Higher Polytechnic SchoolUniversity of DakarDakarSenegal

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