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. 2010 Mar 1;1(1):57-63.
doi: 10.1007/s12652-009-0007-1.

Recognizing independent and joint activities among multiple residents in smart environments

Geetika Singla  1 , Diane J Cook, Maureen Schmitter-Edgecombe
Affiliations

Recognizing independent and joint activities among multiple residents in smart environments

Geetika Singla et al. J Ambient Intell Humaniz Comput. .

Abstract

The pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals experiencing difficulties living independently at home. A primary challenge that needs to be tackled to meet this need is the ability to recognize and track functional activities that people perform in their own homes and everyday settings. In this paper, we look at approaches to perform real-time recognition of Activities of Daily Living. We enhance other related research efforts to develop approaches that are effective when activities are interrupted and interleaved. To evaluate the accuracy of our recognition algorithms we assess them using real data collected from participants performing activities in our on-campus smart apartment testbed.

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Figures

Fig. 1
Fig. 1
The smart apartment testbed. Sensors in the apartment (bottom) monitor motion (M), temperature (T), water (W), door (D), burner (AD), and item use (I)
Fig. 2
Fig. 2
Multi-resident participants performing activities in smart apartment. Person A (upper left) is performing “Fill medication dispenser” activity while Person B (upper right) is performing “Hang up clothes” activity. The sensor events corresponding to these activities is shown in the lower left and is visualized in the lower right
Fig. 3
Fig. 3
A section of an HMM for multi-resident activity data. The circles represent hidden states (i.e., activities) and the rectangles represent observable states. Values on horizontal edges represent transition probabilities and values on vertical edges represent the emission probability of the corresponding observed state
Fig. 4
Fig. 4
Performance of a HMM in recognizing activities for multi-resident data
Fig. 5
Fig. 5
Performance of one HMM for each resident
See this image and copyright information in PMC

References

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