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Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
Towards a Holistic Approach for Mobile Application Development in Intelligent Environments
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Towards a Holistic Approach for Mobile Application Development in Intelligent Environments

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"There’s An App for That" -- but how do we actually develop them? While smartphones and tablets are even getting increasingly more popular and their application scenarios are growing, we still develop …

"There’s An App for That" -- but how do we actually develop them? While smartphones and tablets are even getting increasingly more popular and their application scenarios are growing, we still develop them using only a standard integrated development environment. As context-based services and apps do, next to network connectivity, require lots of sensor data, the tools for providing realistic sensor data during development are still immature.

Developing, testing, debugging and evaluating those next-generation context-based apps require sensor data for the mobile device -- acceleration, motion, light, sound, camera and many more sensors are available. Though, the existing development tools do seriously limit application developers by not providing the data at all or only on a very limited scale. Especially for indoor environment with applications such as indoor navigation, seamless interaction between public and private displays and activity recognition and monitoring, realistic sensor data are needed and simulation support during the development phase is essential.

In this paper, we present our work towards a holistic approach for mobile application development in intelligent environments, leveraging the existing development tool chain, facilitating more effective and realistic means for mobile application development at the example of the Android mobile device platform.

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  1. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität München Towards a Holistic Approach for Mobile Application Development in Intelligent Environments Stefan Diewald, Luis Roalter, Andreas Möller, and Matthias Kranz Technische Universität München Beijing, December 9, 2011 10th International Conference on Mobile and Ubiquitous Multimedia (MUM 2011)
  2. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München General Trends for Mobile Computing over 512,000 apps “There’s an approx. 18 billion D/Ls app for that.” over 340,000 apps over 10 billion D/Ls §  “Always connected, personal and contextual” (finally Ubiquitous Computing!!!) §  “Rapid development”: more and more apps being developed, but less and less time for it §  “Rapid innovation”: apps are getting more and more complex and having more and more features à better tools are needed to support better development in less timeü  Source: Appcelerator and IDC: Mobile Developer Report, January 2011 (05.12.2011)ü  Market numbers: http://appshopper.com/ and http://www.appbrain.com/stats/number-of-android-apps (08.12.2011) 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 2
  3. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenMotivation & Contribution§  Improvement of the technical development process by extended debugging capabilities§  Improvement of the application development process by extended prototyping capabilities§  Improvement of the algorithm development process by extended simulation capabilities09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 3
  4. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Outline & Structure §  Introductory example: “MagicPhone” (Wu et al., 2010) as an example for a mobile application for indoor interaction in intelligent environments §  Introduction to ROS (http://www.ros.org - not our contribution, just our tool!) and its key concepts – a robotics middleware, used also for intelligent environments (c.f. Roalter et al., 2011) §  Current state of the art sensor simulation & tools for mobile application development – focus: sensor-data driven and event-driven applications and context-aware applications in indoor environments §  Technical details of our approach §  Examples for mobile interaction supported by the proposed approach §  Outlookü  Jiahui Wu, Gang Pan, Daqing Zhang, Shijian Li, and Zhaohui Wu. MagicPhone: Pointing & Interacting. In Proceedings of the12th ACM International Conference Adjunct Papers on Ubiquitous Computing (Ubicomp 10). ACM, New York, NY, USA, 451-452.ü  Luis Roalter, Andreas Möller, Stefan Diewald, and Matthias Kranz. Developing Intelligent Environments: A Development Tool Chain for Creation, Testing and Kranz - MUM of Smart and Intelligent Environments. In Proceedings of the 7th International 09.12.2011 Prof. Dr. Matthias Simulation 2011 4 Conference on Intelligent Environments (IE 11). pp. 214-221, Nottingham, UK, July 2011
  5. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Modern Applications need Rich Sensor Data §  Physical ubiquitous interaction §  Indoor localization / navigation §  Context-based §  ... Esp. indoor apps are heavily dependent on local and environment sensor data.ü  Image Source: MagicPhone: Pointing & Interacting: http://www.youtube.com/watch?v=6aVnSmY81KA (06.12.2011)ü  Jiahui Wu, Gang Pan, Daqing Zhang, Shijian Li, and Zhaohui Wu. MagicPhone: Pointing & Interacting. In Proceedings of the12th ACM International Conference Adjunct Papers on Ubiquitous Computing (Ubicomp 10). ACM, New York, NY, USA, 451-452. 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 5
  6. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Testing & Development of Mobile Applications §  Context-aware applications depend on multiple sensors’ data at the same time (e.g. accelerometer, gyroscope, location, …) §  Current limitations on multi-sensor simulation possibilities require that currently: •  (much) testing is carried out on real devices •  the tester has to repeat the physical actions (incl. moving around, pointing, …) over and over again in the real world §  Often functions are tested separately (e.g. only one sensor input at a time) which does not allow verification of the complete solution §  Testing in artificial lab environments can only cover a very limited set of scenarios  Virtual Prototyping as potential approach for mobile application development in UbiCompü  Image Source: MagicPhone: Pointing & Interacting: http://www.youtube.com/watch?v=6aVnSmY81KA (06.12.2011) 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 6
  7. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München ROS as Middleware for Distributed Sensor-Actuator Systems §  ROS = Robot Operating System, originates from the robotics domain, but it is also used for intelligent and ambient assisted living environments (intelligent environment as “ImmoBot”, static distributed sensor-actuator system) http://www.ros.org/wiki/vmi-ros-pkg ß Our complete stacks avail. online §  Provides hardware and software abstraction, device drivers, message passing, visualization and simulation tools (2D and 3D), (…) Message Passing system (additionally also a service-oriented comm. system) §  Event-based message generation & handling (somewhat similar to Android!) §  Basic message types e.g. for strings, integers or floats §  Special message types e.g. for images, point clouds or object poses §  Publisher / Subscriber model allows fast interconnection of components §  All kinds of messages can be recorded and replayed. Subscriber 1 Publisher Function SubscriberPublisher msg 09.12.2011 Subscriber n Prof. Dr. Matthias Kranz - MUM 2011 e.g. add noise, rectify, … 7
  8. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Realization of Realistic Simulation with ROS (IE 2011 Paper) Gazebo 3D Simulator (as part of ROS) §  Goal: (more) realistic 3D environments with full texture and lighting support §  Environments can be created by using a modified interior design application (‘SweetGazebo’) §  Objects can be created with common 3D modeling tools such as Blender, Cinema4D or 3ds Max §  Physics simulation: realistic behavior by defining mass, inertia and friction values for objects §  Virtual sensors and actuators can be integrated in ROS via plugins and attached to any object in the simulation. §  ROS connection allows reading out and setting objects’ statesü  Luis Roalter, Andreas Möller, Stefan Diewald, and Matthias Kranz. Developing Intelligent Environments: A Development Tool Chain for Creation, Testing and Kranz - MUM of Smart and Intelligent Environments. In Proceedings of the 7th International 09.12.2011 Prof. Dr. Matthias Simulation 2011 8 Conference on Intelligent Environments (IE 11). pp. 214-221, Nottingham, UK, July 2011
  9. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenCurrent Situation w.r.t. the Development SupportDevelopment Support for Sensor Data at theExample of Android-based Devices (fastest growing OS):§  Position: input of GPS data via e.g. the NMEA protocol  goal: make it easier to input (esp. for indoor env.)§  Camera: test image or test video inclusion via a Client/Server solution – but: - How long would the user actually point a device in a certain direction? - How does this additional code influence the app during development, and when is it removed later? (not transparent to the application) à goal: make it part of the simulator/emulator!§  (Acceleration/Pose/…) Sensor data simulation/generation: artificially generated with an input device with mismatching dimensions (2D mouse vs. 3D orientation), some support on replay/recording of data sets  goal: make it more realistic09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 9
  10. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Current Situation w.r.t. the Development Supportü  Left: Samsung Sensor Simulator, source: http://innovator.samsungmobile.com/image.view.do?serviceId=cmsCnts &attachmentId=11105 (05.12.2011)ü  Right: Live Camera Previews in Android, source: http://www.tomgibara.com/android/camera-source (05.12.2011) 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 10
  11. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Current Situation – OpenIntents Sensor Simulatorü  Image Source: OpenIntents Sensor Simulator: http://code.google.com/p/openintents/wiki/SensorSimulator (05.12.2011) 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 11
  12. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Issues and Problems with Current Development Support §  Physicality of the human as user and of the device in space is often neglected, e.g. movement in an environment, pointing of a device at an object, scanning/touching of a QR or NFC marker, co-location of objects, relation of objects to each other, interrupts during application runtime as standard, not exception, … §  Imperfection and variability of the real world are not really taken into account: à temporal and spatial instability/variability (of sensor data) “ignored” (“spice” of real world challenges – c.f. impressive UbiChallenge presentations!) Examples of what is often neglected/not investigated during mobile app development: •  WLAN connection is ‘always bad’ at a given location (that is, the connection breaks, like in the real world, bursty location updates/jumpy positioning/ suffering localization accuracy indoors; c.f. Kranz et al, 2010), •  places change frequently (like posters at the walls that influence tracking), …ü  M. Kranz, C. people/objectsComparativethe line of sight of a camera, …Localization. 8th IEEE International •  Fisher, A. Schmidt. A walk in Study of DECT and WLAN Signals for Indoor Conference on Pervasive Computing and Communications (PerCom2010). pp. 235-243, Mannheim, Germany, March 2010 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 12
  13. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenRoom for Improvement in the Development Process§  Debugging & testing of interactive systems already during development phase (and not at the end) à not really available as of now (c.f. reviewed simulators)§  Still no (little) realistic statements can be made on usage/performance of apps in real(istic) environments as they are (mostly) not part of the development process! à not really (quickly) testing possible in multiple environments before deployment/extensive real world testing§  Complex interactions such as touching objects or grabbing an image of a display can currently not directly be investigated in the development tools à not really available as of nowChallenges:§  How to provide (better) data (or at least initial data at all)?§  How to more efficiently develop those complex interactive systems (and not only mobile phone software)?§  How to more efficiently prototype multimodal and multimedia systems faster?09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 13
  14. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenProposed Idea: Extended IDE and Development Tool Chain09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 14
  15. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Example: Virtual Camera and Virtual Display Functionality§  Linked ROS sensors and Android sensors in the example: camera and accelerometer.§  Display: Android output that is pushed back to the simulated 3D environment  all simulation no longer part of the application, but the emulator/simulator (question: how do we move/steer/control the device in the simulation? à later!) 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 15
  16. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenSupported Sensors and ActuatorsSensors§  Accelerometer* and Gyroscope§  Camera* and Depth Image Sensor§  Light Sensor§  Proximity Sensor§  GPS§  NFC Reader§  Battery Status A virtual Android device in a realistic 3d simulation of an office.§  …Actuators§  Light Emitting Diodes and Displays*§  Projectors§  Speakers * Currently fully supported by the connected Android emulator, all others are already supported by ROS as well§  …09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 16
  17. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Example 1: Indoor Localization and Physical Interaction using NFC tags and QR codes Real Simulated§  Connect device, install changed §  Install changed version of app version of app, disconnect device §  Perform test: replay recorded data set§  Perform test: walk several meters in (even faster than real-time), variation corridor, take picture or touch NFC can be added automatically, tag e.g. position offset, … 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 17
  18. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Ex 2: Indoor Localization/Tracking using Visual Information Instead of taking various fixed and prerecorded videos, daylight, obstacles, and other properties are simulated in an extended IDE/tool chain.ü  PTAM (Parallel Tracking and Mapping), source: http://www.robots.ox.ac.uk/~gk/PTAM/ (06.12.2011) 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 18 (markerless, feature-based tracking, no a-priori maps, no inertial measurement unit; test implementation)
  19. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Example – Manual Testing of Mobile Applications in the Virtual Environment §  3d input devices like the 3Dconnexion SpaceNavigator or joysticks can be used for 6 degrees-of-freedom controlling §  Mobile device’s accelerometer, gyroscope and magnetometer for 3D + orientation + classic keyboard for 2D navigation (walking through the virtual scene by holding a real Android device for the pose information and steering by the keyboard for the 2D location info.)ü  Image Sources: top: 3Dconnexion – SpaceNavigator: http://www.3dconnexion.de/products/spacenavigator.html (06.12.2011), bottom left: http://alwaysinternet.de/wp-content/uploads/2010/12/google-nexus-s-samsung.jpg (06.12.2011), bottom right: http://www.logitech.com (06.12.2011) 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 19
  20. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Example – (human-inspired robotic) Path Planner and Navigation Stack for Automated (Randomized) Testing §  ROS offers several path planning and navigation stacks (spice for getting slightly different paths on each walk from A to B) §  Autonomic ROS running robots (like the PR2) with laser scanner and/or depth cameras can be used for generating a map §  Random paths can be created by imposing different constraints for the route §  Mobile device could be steered along path e.g. having a fixed pose similar to holding a mobile phone in front user §  Test how applications can adapt to disturbances, variations, …ü  Image Source: ROS package - base planner: http://www.ros.org/wiki/base_planner_cu (07.12.2011) 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 20
  21. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenExample – Testing with different Light Conditions§  Light conditions can be varied in the 3d simulation.§  Light direction, color and intensity can be adjusted.§  Shadows and reflections are supported.§  Additional distortion can be applied to the virtual camera image.Can be used for testing image/vision-basedapplications.Example: Checking under which conditions ordistances a designed marker is still readable.09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 21
  22. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenSummary of the Potentials of the Proposed Approach§  Multi-sensor simulation in a (more) realistic & easy-to-create 3d environment.§  Sensor data can either be generated automatically, or by a human moving the mobile device in the intuitive 3D simulated virtual environment.§  ‘Randomized’ automatic test cases can make use of available components (e.g. route planning algorithms) and data sets (biasing of positions and other sensor values)§  Recording and replaying of all sensors and states (via ROS messages) allows detailed debugging.§  Connection to a hardware emulator allows debugging end-user versions of mobile applications (no additional source code necessary, that is, no added code that changes the app’s behavior)§  Pushing back the mobile’s displays’ content enables realistic usage of mobile applications in the simulated environment09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 22
  23. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenOutlook – To Dos for the Future§  Verification and analysis of the tool chain / approach: •  Survey and test with professional developers is planned •  Compare development time within the scope of our research-oriented teaching: students will develop various indoor localizations systems with and without tool chain support •  Analyze and compare the types and amount of errors made with normal and proposed approach§  Evaluation of realism of the simulated sensors: metrics need to be defined§  Exploration of new interaction potentials: fast prototyping of mobile interaction with e.g. robots and intelligent environments (home automation systems), possible due to their ROS support§  Extension for other (physical) interaction approaches, esp. Tangible User Interfaces09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 23
  24. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenOutlook – Further possible Application Areas§  Public and private displays§  2d and 3d touch interfaces§  Tangible User Interfaces (I like cubes)09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 24
  25. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Outlook – 2D Tabletop Interactions with a Mobile Device Mixed physical-digital interactions: §  Displays: either external or mobile device as pocket table §  Physical Objects (e.g. Tangible User Interfaces) §  NFC (Near Field Communication) tagged objectsü  Image Source: reacTable: http://www.reactable.com/ (07.12.2011) 09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 25
  26. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenQuestions? ? ? ? ??09.12.2011 Thank you- MUM 2011 much for your kind attention! Prof. Dr. Matthias Kranz very 26
  27. Prof. Dr. Matthias Kranz www.vmi.ei.tum.deFachgebiet Verteilte Multimodale Informationsverarbeitung Technische Universität München
  28. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität München m.de i.ei.tu m.de w ww.vm nz@tu atthia s.kra m09.12.2011 Thank you- MUM 2011 much for your kind attention! Prof. Dr. Matthias Kranz very 28
  29. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenCombination of the Real and Simulated World at theExample of Indoor Localization Systems Environment Real Simulated Real world test, most Ground truth, testing of Real effort and time controlled effects consumingMobile Device Real effects, but no Fast evaluation of Simulated working prototpye algorithms, everything necessary controllableROS can be used to connect real and simulated components.09.12.2011 Prof. Dr. Matthias Kranz - MUM 2011 29
  30. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität München Thank you for your attention! Questions? ? ? matthias.kranz@tum.de www.vmi.ei.tum.de/team/matthias-kranz.html04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 30
  31. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenPaper Reference•  Please find the associated paper at: https://vmi.lmt.ei.tum.de/publications/2011/MUM11_preprint_v2.pdf•  Please cite this work as follows:•  Stefan Diewald, Luis Roalter, Andreas Möller, Matthias Kranz. 2011. Towards a Holistic Approach for Mobile Application Development in Intelligent Environments. In: Proceedings of the 10th International Conference on Mobile and Ubiquitous Multimedia (MUM 2011), Beijing, China, pp. 73-80, December 201104.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 31
  32. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenIf you use BibTex, please use the following entryto cite this work: @InProceedings{MobileSimulation11, author = {Stefan Diewald and Luis Roalter and Andreas M{"o}ller and Matthias Kranz}, title = {{Towards a Holistic Approach for Mobile Application Development in Intelligent Environments}}, booktitle = {Proceedings of the 10th International Conference on Mobile and Ubiquitous Multimedia}, series = {MUM 11}, location = {Beijing, China}, publisher = {ACM}, pages = {73--80}, numpages = {8}, month = dec, year = {2011}, address = {New York, NY, USA}, ISBN = {978-1-4503-1096-3}, url = {http://doi.acm.org/10.1145/2107596.2107604}, doi = {10.1145/2107596.2107604}, acmid = {2107604}, keywords = {Android, ROS, intelligent environment, middleware, mobile devices, simulation, smart phones, virtual environment}, }04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 32

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