AuraOrb

Abstract

One of the problems with notification appliances is that they can be distracting when providing information not of immediate interest to the user. In this paper, we present AuraOrb, an ambient notification appliance that deploys progressive turn taking techniques to minimize notification disruptions. AuraOrb uses eye contact sensing to detect user interest in an initially ambient light notification. Once detected, it displays a text message with a notification heading visible from 360 degrees. Touching the orb causes the associated message to be displayed on the user's computer screen.We performed an initial evaluation of AuraOrb's functionality using a set of heuristics tailored to ambient displays. Results of our evaluation suggest that progressive turn taking techniques allowed AuraOrb users to access notification headings with minimal impact on their focus task.

Assessing the perceptibility of smartphone notifications in smart lighting spaces

“…8, a different picture emerges in the pruned dataset, as the response times between all ALS settings appear similar, except AL3 (which had the fewest extreme response time events). Repeating the same analysis for the pruned dataset, we find that a Friedman two-way analysis of variance, showed that the observed differences are statistically significant (χ 2 (3) = 15.360, p < 0.01). Further pairwise examination with posthoc Bonferroni-corrected Wilcoxon Signed Rank tests, resulting in a p-value threshold of p = 0.008, confirmed that the differences were statistically significant between AL1-AL3 (Z = 3.383, p = 0.001), AL2-AL3 (Z = 3.733, p = 0.000) and AL3-AL4 (Z = 2.993, p = 0.003), thereby concluding that the slow pulsing light is actually the least noticeable of the four combinations (all others having no statistically significant differences).…”

“…In our case, the dependent variable was "Modality", since we try to predict the desired modality depending on the other context attributes. For experiment 1 participants, the final model rejects the null model hypothesis (χ 2 (52) = 808.042, p < 0.01) and demonstrates a good model fit (Pearson χ 2 (144) = 77.655, p = 1.00). However, the pseudo R 2 value is 0.399 (Nagelkerke), showing that only part of the variance in declared preferred modality is explainable by the contextual factors Task, Location, Social and Application Type.…”

“…To examine the results for statistical significance, we used nonparametric tests, due to the non-normal distribution of the data. Firstly, with regard to single modalities (A, L, V or S), a Friedman tests shows that a statistical significance between the mean response times exists (χ 2 (3) = 33.336, p = 0.00). Following post-hoc Wilcoxon signed rank tests, with a Bonferroni correction setting the significance level at p < 0.0083, we find statistically significant differences between V-A (Z = −3.807, p = 0.00), L-A (Z = −4.184, p = 0.00), S-V (Z = −3.538, p = 0.00) and S-L (Z = −3.700, p < 0.00).…”

“…However, the pseudo R 2 value is 0.399 (Nagelkerke), showing that only part of the variance in declared preferred modality is explainable by the contextual factors Task, Location, Social and Application Type. Looking further, likelihood ratio tests show that three out of these factors have a significant impact on the modality, namely Application Type (χ 2 (36) = 610.616, p < 0.01), Social (χ 2 (8) = 100.359, p < 0.01) and Location (χ 2 (4) = 13.215, p = 0.01), while the user Task seems to have no impact at all (χ 2 (4) = 5.023, p = 0.285). The results are slightly different for experiment 2 participants.…”

“…However, there are gaps in all of the surveyed papers therein: either the systems presented are evaluated in preliminary trials with very few participants (e.g. [2]), or there are, at best, limited comparisons between alternative designs for the perceptibility of conveying simple notifications (e.g. in [30] it is argued that blinking or animated lights should be used, but only blinking vs. static light was actually examined).…”