Background



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tarix07.08.2018
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Background

  • Background

    • Pervasive computing
    • Positioning needs
    • Related works




PSAQL in our platform PerSE to express user intensions:

  • PSAQL in our platform PerSE to express user intensions:

  • USE sunrise.ppt ON BASE notebook WITH SERVICE projector





Among localization and distance measuring methods are:

  • Among localization and distance measuring methods are:

    • Global Positioning Systems
    • Radio Frequency (RF) delay measurement
    • Association to nearest Access Point
    • Received RF signal strength


Background

  • Background

    • Pervasive computing
    • positioning needs
    • Related works


Learning phase: data is collected, classified to create the prediction model

  • Learning phase: data is collected, classified to create the prediction model

  • Prediction phase: Location prediction based on the real-time data values



A person holding a PDA moves around the rooms in the building including meeting halls, offices, common rooms, printing rooms and corridors

  • A person holding a PDA moves around the rooms in the building including meeting halls, offices, common rooms, printing rooms and corridors



For each tracking point i in room k, we have a vector with the signal strength values from the APs and a label corresponding to the literal name of the place (room) where the point is situated.

  • For each tracking point i in room k, we have a vector with the signal strength values from the APs and a label corresponding to the literal name of the place (room) where the point is situated.



Signal strength values are classified for pattern identification using data mining tool (MCubiX implementation of the decision tree algorithm).

  • Signal strength values are classified for pattern identification using data mining tool (MCubiX implementation of the decision tree algorithm).





Background

  • Background

    • Pervasive computing
    • positioning needs
    • Related works


The size of the PMML file containing the model generated after about 4 hours of tracking experiment using three devices is about 320 KB (200rules) and it is within the storage range of mobile devices.

  • The size of the PMML file containing the model generated after about 4 hours of tracking experiment using three devices is about 320 KB (200rules) and it is within the storage range of mobile devices.

  • Using a cross validation, the results are very encouraging with the error rate below 5%, corresponding to a 95% hit rate.





Consider a scenario where Dave is given a multimedia entertainment service on his PDA while he is in the common room for the tea break.

  • Consider a scenario where Dave is given a multimedia entertainment service on his PDA while he is in the common room for the tea break.



Location prediction combined with context information to determine David’s intension in proactively.

  • Location prediction combined with context information to determine David’s intension in proactively.



Background

  • Background

    • Pervasive computing
    • positioning needs
    • Related works






Background

  • Background

    • Pervasive computing
    • positioning needs
    • Related works
  • Model for indoor location detection

    • Learning phase
    • Prediction Phase
  • Experimental results and usage scenario

  • Conclusions and future work



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