2 research outputs found
Field evaluation of a mobile app for assisting blind and visually impaired travelers to find bus stops
Purpose: It is reported that there can be considerable gaps due to GPS
inaccuracy and mapping errors if blind and visually impaired (BVI) travelers
rely on digital maps to go to their desired bus stops. We evaluated the ability
of a mobile app, All_Aboard, to guide BVI travelers precisely to the bus-stops.
Methods: The All_Aboard app detected bus-stop signs in real-time via smartphone
camera using a neural network model, and provided distance coded audio feedback
to help localize the detected sign. BVI individuals used the All_Aboard and
Google Maps app to localize 10 bus-stop locations in Boston downtown and
another 10 in a sub-urban area. For each bus stop, the subjects used the apps
to navigate as close as possible to the physical bus-stop sign, starting from
30 to 50 meters away. The outcome measures were success rate and gap distance
between the app-indicated location and the actual physical location of the bus
stop. Results: The study was conducted with 24 legally blind participants (mean
age [SD]: 51[14] years; 11 (46%) Female). The success rate of the All_Aboard
app (91%) was significantly higher than the Google Maps (52%, p<0.001). The gap
distance when using the All_Aboard app was significantly lower (mean [95%CI]:
1.8 [1.2-2.3] meters) compared to the Google Maps (7 [6.5-7.5] meters;
p<0.001). Conclusion: The All_Aboard app localizes bus stops more accurately
and reliably than GPS-based smartphone navigation options in real-world
environments
Metadata record for: HIT-COVID, a global database tracking public health interventions to COVID-19
This dataset contains key characteristics about the data described in the Data Descriptor HIT-COVID, a global database tracking public health interventions to COVID-19. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON forma