Leveraging big traffic data
to create a web service
which alerts users of
potential traffic congestion
Donna Thomas
Jacob Rettig
Justin Lawrence
CMSC 668
October 1st, 2012
Project
Description
Using Big Data sets, we are mining for potential
congested traffic patterns which may impair
one’s timely commute during rush hour. When
we discover potential congested traffic
patterns, our web service will send SMS and
Email notifications to service subscribers.
Users
•
NYC Tri
-
State
Area
Users
Users stuck in traffic
Users querying traffic conditions
Link and Event driven
Civic responsibility
Scenarios
User Inputs:
•
Registration for accounts
•
Registration for traffic alerts
•
Search for alerts by
o
X miles from City/Address
o
X miles from Latitude/Longitude
o
Path between point A and B
Output to Users:
•
List of traffic alerts of interest
•
Alerts on Google Maps
•
Alerts sent to registered users via
o
email, SMS text, etc.
Functional Requirements
Technologies and Hardware Used
HADOOP
MapReduce
Apache Tomcat
WSDL
JAX
-
RPC/XML
-
RPC
SOAP
AXIS
Google Maps
API
TRANSCOM data set
SMTP Server
BlueGrit
Cluster
Data sources
TRANSCOM
Google Maps
Our project’s design
Based on project requirements:
Bluegrit
Cluster, using SOAP in the Cloud
Services and Network Architecture
•
UMCP
CapWIN
•
I
-
95 Corridor
•
TRANSCOM/Xerox
•
INRIX
•
Dr. Kalpakis
-
Traffic Models
•
Dr.
Finin
-
Twitter
(
TweetCollector
+
TweetGobbler
)
•
Dr. Sherman
-
CapWIN
(UMCP
collaboration)
Related Works
•
User Login
•
Basic Authentication
•
Register Alerts
Security
•
After
-
class meetings to discuss ideas and
direction
•
Skype for remote meetings and
discussions
•
Microsoft SkyDrive for creating
collaborated documents
Team Approach
•
Midterm:
o
Design Database schema and begin to pull data from TRANSCOM
o
Design
MapReduce
queries
o
Develop querying and polling services
o
Create SMTP server for notifications
o
Integrate output with Google Maps API
•
Final:
o
Finalized Project Report
o
Provide Demonstration
Performance and Results
•
Big data analysis interpretation
•
Event driven path analysis
•
Getting access to traffic data
Challenges
•
Communicate with data providers (Donna)
•
Register to receive data from data providers (Donna, Justin and
Jacob)
•
Installation/setup of:
o
Hadoop
(Justin), AXIS (Jacob), Tomcat (Jacob), HDFS (Justin), HBASE (Justin),
MapReduce
(Justin), SMTP (Justin)
•
Security: (Jacob)
o
SOAP authentication headers, web GUI authentication
•
Create ontology/schemas types:
o
HBASE (Justin), SOAP messages (Donna)
•
Data Ingest service(s):
o
TRANSCOM (Jacob, Justin, Donna)
•
User registration services: (Donna)
o
user accounts, traffic alerts registration
•
Querying services (using
MapReduce
): (Justin)
o
Querying traffic data, Traffic alert polling
•
Messaging service to send: (Justin)
o
emails, SMS texts, RSS, SOAP
•
Web GUIs: (Donna, Jacob, Justin)
o
Google Maps, User Services, Querying Services
•
Testing: (Donna, Jacob, Justin)
•
Writing the Paper: (Donna, Jacob, Justin)
Responsibilities
Allow people travelling through the New York tri
-
state
area to avoid traffic congestion by leveraging
event and link driven data from TRANSCOM.
Summary
Technical Data:
Google Maps APIs
http://code.google.com/apis/maps/index.html
TRANSCOM dataset
http://www.xcom.org
WebServices
–
Axis
http://axis.apache.org/axis/java/install.html
Credits/References
Research/Publications:
Barry, Keith. "The Future of In
-
Car Technology."
Car and Driver
.
N.p
., 1 Apr.
2012. Web. 01 Oct. 2012. <http://www.caranddriver.com/features/the
-
future
-
of
-
in
-
car
-
technology>.
"CATT Homepage, Clark School of Engineering, University of Maryland."
CATT
Homepage, Clark School of Engineering, University of Maryland
. Center of
Advanced Transportation Technology,
n.d
. Web. 01 Oct. 2012.
<http://catt.umd.edu/>.
Chan, Alice. "Mercedes
-
Benz Dashboard
Crowdsources
Parking Spots For
Drivers Via Twitter
-
PSFK."
Mercedes
-
Benz Dashboard
Crowdsources
Parking Spots For Drivers Via Twitter
-
PSFK
.
N.p
., 12 Mar. 2012. Web. 01 Oct.
2012. <http://www.psfk.com/2012/03/mercedes
-
benz
-
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-
parking
-
spots.html>.
Chang, Fay, Jeffrey Dean, Sanjay
Ghemawat
, Wilson C. Hsieh, Deborah A.
Wallach, Mike Burrows,
Tushar
Chandra, Andrew
Fikes
, and Robert E.
Gruber. "
Bigtable
: A Distributed Storage System for Structured Data."
OSDI'06: Seventh Symposium on Operating System Design and
Implementation
(2006): 1
-
14. Web. 30 Sept. 2012.
<http://static.googleusercontent.com/external_content/untrusted_dlcp/r
esearch.google.com/en/us/archive/bigtable
-
osdi06.pdf>.
Credits/References
Chouffani
,
Reda
. "4 Questions to Ask Before Starting a Big Data Initiative."
CIO
.
N.p
., 21 Aug. 2012. Web. 01 Oct. 2012.
<http://www.cio.com/article/714309/4_Questions_to_Ask_Before_Starting_
a_Big_Data_Initiative>.
Das
Sarma
,
Anish
,
Lujun
Fang,
Nitin
Gupta,
Alon
Halevy,
Hongrae
Lee,
Fei
Wu,
Reynold
Xin
, and Cong Yu.
Finding
Realted
Tables
. Proc. of SIGMOD ’12,
Scottsdale, Arizona, USA.
N.p
.: ACM, 2012. 1
-
12. Print.
Harris, Derrick. "How
Facebook
Made It Possible to Geo
-
tag Everything
â
Cloud Computing News."
GigaOM
.
N.p
., 9 Mar. 2012. Web. 01 Oct.
2012. <http://gigaom.com/cloud/why
-
every
-
location
-
tag
-
on
-
facebook
-
is
-
big
-
data
-
in
-
action/>.
Holt, Kris. "Toyota Lets Drivers Tweet from the Dashboard."
Daily Dot
.
N.p
., 28
Sept. 2012. Web. 01 Oct. 2012. <http://www.dailydot.com/news/toyota
-
corolla
-
twitter
-
dashboard/>.
Horvitz, Eric. "Predictive Analytics for Traffic."
Microsoft Research
.
N.p
.,
n.d
.
Web. 1 Oct. 2012. <research.microsoft.com/en
-
us/projects/
clearflow
/default.aspx>.
Credits/References
Kuehnhausen
, Martin, and Victor S. Frost.
Transportation Security
SensorNet
: A
Service Oriented Architecture for Cargo Monitoring
. Rep. no. ITTC
-
FY2010
-
TR
-
41420
-
22.
N.p
.: University of Kansas Information & Telecommunications
Technology Center, 2010. Print.
Mazaré
, Pierre
-
Emmanuel, Olli
-
Pekka
Tossavainen
,
Alexandre
M.
Bayen
, and
Daniel B. Work. "Trade
-
offs between Inductive Loops and GPS Probe
Vehicles for Travel Time Estimation: A Mobile Century Case Study."
Trade
-
offs between Inductive Loops and GPS Probe Vehicles for Travel Time
Estimation: A Mobile Century Case Study
.
N.p
.,
n.d
. Web. 1 Oct. 2012.
<https://netfiles.uiuc.edu/dbwork/www/pdf/TRB12.pdf>.
Newcomb, Doug. "
Inrix
|
Autopia
| Wired.com."
Wired.com
.
Conde
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Digital, 05 June 0012. Web. 01 Oct. 2012.
<http://www.wired.com/autopia/tag/inrix/>.
Ovide
,
Shriva
. "Tapping 'Big Data' to Fill Potholes."
Tapping 'Big Data' to Fill
Potholes
. Wall Street Journal, 12 June 2012. Web. 1 Oct. 2012.
<online.wsj.com/article/SB10001424052702303444204577460552615646874.
html>.
Staff,
Datanami
. "What It Takes to Deliver Real
-
Time Traffic Info
-
Datanami
."
What It Takes to Deliver Real
-
Time Traffic Info
-
Datanami
.
Datanami
, 01
Aug. 2012. Web. 01 Oct. 2012.
<http
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-
08
-
01/what_it_takes_to_deliver_real
-
time_traffic_info.html>.
Credits/References
?
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