Utilizing the Internet of Things to develop a
real-time feedback training application with
individual feedback
Contact: Jan Markendahl (janmar@kth.se), Mårten Sundquist (msundqu@kth.se)
Introduction
The Internet of Things market is developing quickly as the cost and availability of sensors are
developing favorably, mobile internet is becoming ubiquitous and the success of the
smartphone ecosystem is continuing. The Kista startup company WEMEMOVE
(http://www.wememove.com/) has developed a patent-protected analysis engine for
movement classification and interpretation that will soon be commercially launched. The first
commercial application will be adapted to cross country skiing. The next application for
WEMEMOVE will be a personalized training application with chest-mounted sensor
combined with both real-time feedback and post-processing qualitative movement analysis
using a cloud-based analysis and classification engine.
The Master Thesis will be include studying, analyzing and developing the personalized
training application of WeMeMove. The student is expected to make contributions in both
technological and market development aspects.
The thesis work will take part at the WEMEMOVE office in Kista with supervision from both
WEMEMOVE and KTH.
Figure 1. Actors involved in the service based on the WEMEMOVE solution.
Problem formulation and main tasks
The main question for the Master Thesis is to verify the basic functions and the end-user
value of the application. The following subtasks are expected to be performed:
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Literature study of existing personalized training solutions. Which radio network
systems are used? Which IT and communication platforms are used?
Which business models are used? How is the market developing?
Try out and evaluate an existing early version prototype.
Describe the WeMeMove personalized training system and suggest enhancements
Implement (including programming, test and verification) some of the suggested
enhancements.
Make a trial of the enhanced application and verify the end-user value
References:
[1] WHO Physical activity [Internet]. [cited 2015 Apr 23]. Available from:
http://www.who.int/topics/physical_activity/en/
[2] Kohl HW, Craig CL, Lambert EV, Inoue S, Alkandari JR, Leetongin G, et al. The
pandemic of physical inactivity: Global action for public health. Lancet. Elsevier Ltd;
2012;380(9838):294–305.
[3] Chesbrough, H. & Rosenbloom, R. S., 2002. The role of business model in capturing value from
innovations: Evidence from Xerox Corporation’s technology spin-off companies. Industrial and
Corporate Change, 11(3), pp. 529-555
[4] European Commission. (2013). Europe’s policy options for a dynamic and thrustworthy
development of the Internet of Things. European
Communications Networks, Content & Technology.
Commission,
Directorate-General
of
[5] Leminen, S., Westerlund, M., Rajahonka, M., & Siuruainen, R. (2012). Towards IOT Ecosystems
and Business Models. In S. a. Andreev (Ed.), Internet of Things, Smart Spaces, and Next Generation
Networking. Lecture Notes in Computer Science (Vol. 7469, pp. 15-26). Springer-Verlag.
[6] M Kranz, A. M. (2012). The mobile fitness coach: Towards individualized skill assessment using
personalized mobile devices. Pervasive and Mobile Computing 9 (2013) , 203-215.
[7] Porter, M. E. (2014). How Smart, Connected Products Are Transforming Competition. Harvard
Business Review November 2014.