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Context Acquisition Based on Load Sensing

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Four industrial load cells each can detect forces of up to 500N. ... bottle, a magazine and a cable reel, totalling an overall weight of about 34kg. ... – PowerPoint PPT presentation

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Title: Context Acquisition Based on Load Sensing


1
Context Acquisition Based on Load Sensing
  • Albrecht, Martin, Kristof, Adrian, Hans-W
  • Lancaster University

Presenter Shih-yen 2005/04/19
2
Introduction
  • Context-aware computing aims to embody
    information about the situation in which people
    interact with computational process.
  • Load sensing though has some properties that
    appear to be well suited for context acquisition
    in ubiquitous computing.
  • Related work SmartFloor

3
Determine 2-D position of objects on surface
  • Four industrial load cells each can detect forces
    of up to 500N.
  • The conditioning units are in turn fed to a
    standard 16-bit Analog to Digital Converter (ADC)
    which links to the serial line of the PC.
  • each load cell can be read 4 times a second. The
    resolution of load sensing in this setup is
    approximately 16g.
  • our driver software only calculates the position
    of objects between 100g and 100Kg (objects less
    than 100g are ignored).

4
Algorithm
5
Algorithm (cont.)
Table 135cm 75cm
6
Proof-of-concept
  • Every day object
  • 500ml water bottle (530g)
  • Two litre water jar(2kg)
  • the centre of the object as its position.
  • Accuracy 2
  • x 4cm
  • y 2cm

7
Real Environment
  • Tablecloth ,a TV-set, a book, a 2 litre water
    bottle, a magazine and a cable reel, totalling an
    overall weight of about 34kg.
  • cm level accuracy.
  • irrespective of
  • objects already
  • on the surface.

8
Detect Interaction Event
  • d threshold of weight A average value
  • D indicator of change
  • Putting an object on the surface
  • As dlt Ae
  • Ds lt e
  • Dm gt De
  • Removing an object from the surface
  • As d gt Ae
  • The same
  • Knocking an object over
  • (DmgtF and Dm gtDs and Dm gtDe).
  • As-Aeltd

9
Proof-of-concept
  • 70 events, 94 correct, 6 missed, no event were
    misclassified.
  • E1,E4 place on E2 knock over E3 remove

10
Living Laboratory
11
Application
  • Object reminder
  • Tracking position and estimate activities

12
Conclusion
  • The weight information is useful context.
  • The position of objects on the surface can be
    determined with high accuracy and reliability.
  • The reported experiments also highlight the
    applicability in everyday settings
  • future work
  • identification, positioning and event detection
  • develop algorithms that account for complex
    interactions
  • with multiple objects on surfaces
  • object tracking across multiple surface
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