1. RAIL SENSE
Quantifying Mental Engagement of
NYC Subway Rider
ITP GT 2729 QUANTIFIED SELF ABOUT TOWN
MID-TERM PROJECT PERESENTATION
Dimas Rinarso Putro (drp354)
Kania Azrina (ka1531)
2. ITP GT 2729 Quantified Self About Town
Project Proposal Presentation
WHY SUBWAY“Feelings of happiness, life satisfaction and
the sense that one's activities are
worthwhile all decrease with every
successive minute of travel to work.”
(Office of UK National Statistic, 2014).
NYC is
HIGHEST
TRANSIT
RIDERSHIP
in U.S.
Average time
spent in NYC
subway :
48MINUTES
1.5MILLION
commuters
each day
677
MILLION
SUBWAY
RIDERSHIP
vs.
124 million
bus ridership
Source :
http://web.mta.info/nyct/facts/ridership/#chart_s
http://en.wikipedia.org/wiki/List_of_U.S._cities_with_high_transit_ridership
http://www.nydailynews.com/new-york/new-yorkers-havelongest-commute-times-article-1.1426047
3. ITP GT 2729 Quantified Self About Town
Project Proposal Presentation
PROJECT CONCEPT
Brainwave
Sensor
RailSense
App
Mental State
4. ITP GT 2729 Quantified Self About Town
Project Proposal Presentation
RAILSENSE AND THE CITY
Brainwave
Sensor
RailSense
App
Mental State
Subway Rider
Mental States
G
Metropolitan Transit
Authority
MTA Turnstile
Data
DATA ANALYSIS
WEB APPLICATION
Real-Time
Result
Real-Time
Result
NYC Subway Rider
5. ITP GT 2729 Quantified Self About Town
Project Proposal Presentation
WORK FLOW
Brainstorming
Tools Exploration
Proposal Write-up
Application
Development
Deployment
Final
Presentation
1 3
2 4
5
6
6. ITP GT 2729 Quantified Self About Town
Project Proposal Presentation
RAILSENSE APP
7. ITP GT 2729 Quantified Self About Town
Project Proposal Presentation
RAILSENSE AND THE CITY
WEB APPLICATION
8. ITP GT 2729 Quantified Self About Town
Project Proposal Presentation
CHALLENGES LIMITATIONS
Accuracy and calibrations
of the Mindwave sensors.
Power source to
accommodate data
collection for full day
experiments.
Limitations to the number
of sample and the
consistency of the data.
Low penetration potential
for the IOS and sensors to
be natively used by
subway commuters in a
large scale.
Unavailability of GPS in
underground, requires
more user interaction
during the lifelogging.
Multiple other factor that can
affect brain activity are
subject to parameters
beyond the scope of
experiments.
Flood coverage area provides one measure of impact but was not the only way people were affected and does not provide an indicator for a neighborhood’s recovery period.
Rockefeller Foundation, some of the major ways people’s daily lives were impacted included: school closures, home damage, public transit delays, and power outages.
Limited by what data was publicly available, we attempted to define an impact and recovery index and categorize neighborhoods into groups by examining building damage, transportation patterns, and school attendance.