Big Data Integrated Media Systems Center h#p://imsc.usc.edu/
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1 Big Data Integrated Media Systems Center h#p://imsc.usc.edu/ Cyrus Shahabi, Ph.D. Professor of Computer Science & Electrical Engineering Director, Integrated Media Systems Center (IMSC) Viterbi School of Engineering University of Southern California Los Angeles, CA shahabi@usc.edu 1
2 OUTLINE IMSC Background & Overview Vision: Geo- Immersion Big Data IMSC Closing Remarks 2
3 IMSC Background One of the 46 exisnng NaNonal Science FoundaNon (NSF) Engineering Research Centers (29 graduated) - Focuses on MulNmedia ERC emphasis: MulNdisciplinary, Industry Presence Founded by Max Nikias in 1996, graduated in 2007, operanng in self- sustained mode. New management, team & vision in July 2010 Current Management Team 3
4 IMSC Vision: Geo- Immersion Real World Remote Sensing: Satellite & Mul<- Spectral Imagery Aerial Sensing: LiDAR, aerial imagery, UAV video Ground Sensing: Traffic loop detectors, CCTV, pollu<on sta<ons People Sensing: smart phones, GPS, naviga<on Blending the real and virtual worlds: Beyond augmented- We fuse geo- data from the same 9me AND space into ac9onable reality, virtual- reality, knowledge. Beyond integranng data and informanon Towards fusion of human behaviors in both worlds Human Body Sensing Virtual World 4
5 Why Big Data? Big Analy<cs Small Files! Big Data Small Analy<cs Machine Learning, Data Mining, etc. Parallel DBs, Cloud, HPC, Distributed Sys, etc. 5
6 Who Big Data? ApplicaNon: Health, TransportaNon, Energy, etc. Machine Learning, Data Mining, etc. Parallel DBs, Cloud, HPC, Distributed Sys, etc. 6
7 OUTLINE IMSC Background & Overview Vision: Geo- Immersion Big Data IMSC Closing Remarks 7
8 Big Data IMSC Intelligent TransportaNon Big data acquisinon, storage and access Intelligent Surveillance Big data analyncs Intelligent Campus Big data collecnon 8
9 Big Data IMSC Intelligent TransportaNon Big data acquisinon, storage and access Intelligent Surveillance Big data analyncs Intelligent Campus Big data collecnon Prof. James Moore (VSoE) Prof. Genevieve Giuliano (Price School of Policy) Prof. Marlon Boarnet (Price School of Policy) Prof. Hamid Nazerzadeh (Marshall School of Bus.) USC Stevens 9
10 PROBLEM Intelligent TransportaNon Traffic congesnon is a $87.2 billion annual drain on the U.S. economy 1 : 4.2 billion lost hours (one work week for every traveler) billion gallons of wasted fuel (three weeks worth of gas for every traveler) 1 1 Texas TransportaNon InsNtute Urban Mobility Report, 2007 data LocaNon data could save consumers worldwide more than CongesNon costs $713 $600 per commuter billion annually per by year, in extra fuel and wasted Nme: The biggest Los Angeles single 64 hrs, consumer $1,334 benefit will be from Nme and fuel savings San from Francisco locanon- based 50 hrs, $1,019 services tapping into real- Nme traffic and Chicago weather 51 hrs, $1,568 data that help drivers avoid congesnon Washington 74 hrs, $1,495 and suggest alternanve routes. 10
11 Traffic An Data Exclusive Lifecycle: Contract Data Aggregator w LA- Metro Data Type Sample XML File Size (in KB) Variety (gps, video, loop Cycle Duration (in seconds) Minute (in KB) Hourly (in KB) Daily (in KB) Annual (in KB) 3 Years (in KB) sensor, events) bus_mta_inv2.xml , , bus_mta_rt2.xml , , ,882, ,646, cctv_inv.xml , , cms_inv.xml , , cms_rt.xml , , ,183, ,549, event_d7.xml , ,625, ,875, rail_mta_inv.xml , rail_rt.xml , ,204, ,614, rms_inv.xml , , rms_rt.xml , ,423, ,713, ,559,139, signal_inv.xml , , ,294, signal_rt.xml , , ,061, ,847,308, ,541,926, tt_d7_inv.xml , , tt_d7_rt.xml , , ,891, ,673, vds_art_d7_inv.xml , , Velocity vds_art_d7_rt.xml , , ,652, ,956, vds_art_ladot_inv.xml , , ,779, vds_art_ladot_rt.xml , ,395, ,306, ,527,919, vds_fr_d7_inv.xml , ,047, vds_fr_d7_rt.xml , ,039, ,483, ,138,449, Total KB from XML data , , ,057, ,670,968, ,012,906, Volume 11
12 TransDec: Big data acquisinon, storage & access Input Traffic Data Data Processing Storage Retrieval, Analysis &VisualizaNon Sensor 4 46 MB/min MB/min TB/Year Sensor 3 Sensor 2 Highway (4313) Arterial (4780) Real- <me Queries & Bus & Rail (2000) Data Cleansing Ramp meter Events & CMS (800/day) Spa<otemporal Indexing Sensor 1 Event LocaNon E.g., Accident impact analysis & predic<on 12
13 Technology Transfer: ClearPath 3 Pending Patents! 13
14 Google OpNon #1 8:00 AM Thursday Source: W Washington Blvd & Beethoven St Des<na<on: USC 14
15 Google OpNon #2 8:00 AM Thursday Source: W Washington Blvd & Beethoven St Des<na<on: USC 15
16 Google OpNon #3 8:00 AM Thursday Source: W Washington Blvd & Beethoven St Des<na<on: USC 16
17 ClearPath 8:00 AM Thursday Source: W Washington Blvd & Beethoven St Des<na<on: USC 17
18 Sample 2012 Research Result Sensor Data AnalyNcs B. Pan, U. Demiryurek, and C. Shahabi, UNlizing Real- World TransportaNon Data for Accurate Traffic PredicNon, IEEE Interna9onal Conference on Data Mining (ICDM), Brussels, Belgium, December 2012 Machine Learning, Data Mining, etc. 18
19 VOA: March 6, 2013 hop:// technology- clearpath/ html 19
20 Big Data IMSC Intelligent TransportaNon Big data acquisinon, storage and access Intelligent Surveillance Big data analyncs Intelligent Campus Big data collecnon Prof. Gerard Medioni (VSoE) Prof. Ram NevaNa (VSoE) Prof. Antonio Ortega (VSoE) Prof. Yan Liu (VSoE) Prof Jon Taplin (Annenberg School of Comm) Prof. Carolee Winstein (Keck School of Medicine) Prof. Murali Annavaram (VSoE) USC DPS, CREATE, CTSI, CiSoq, AMI 20
21 Intelligent Surveillance Janus: SpaNotemporal fusion of unstructured intelligence 21
22 Video AnalyNcs at Scale Face detecnon & recogninon Event detecnon (e.g., abandoned bag) UNlizing Intel Viewmont co- processor for real- Nme analysis 22
23 Text AnalyNcs (Tech Transfer) With Prof. Craig Knoblock (ISI) 23
24 iwatch Health Monitoring and EvaluaNon of Parkinson's Disease PaNent Performance using Kinect Data CollecNon: Provides data sense and communicanon capabilines that enables real- Nme data acquisinon in various selected modalines Denoise: Remove noise from the raw data ClassificaNon: Define and classify the performance of the panent User Interface: Enables efficient management of the panent performance 24
25 (2) Kinect sensors + 1 digital camera skeleton data has 15 features Principle Component Analysis 25
26 Sample 2012 Research Result Human AcNviNes AnalyNcs H. Shirani- Mehr, F. Banaei- Kashani, and C. Shahabi, Efficient Reachability Query EvaluaNon in Large SpaNotemporal Contact Datasets, 38th Interna9onal Conference on Very Large Databases (VLDB), Istanbul, Turkey, August Parallel DBs, Cloud, HPC, Distributed Sys, etc. 26
27 Big Data IMSC Intelligent TransportaNon Big data acquisinon, storage and access Intelligent Surveillance Big data analyncs Intelligent Campus Big data collecnon Prof. Burcin Becerik- Gerber (VSoE) Prof. Bhaskar Krishnamachari (VSoE) Prof. Dennis McLeod (VSoE) Prof. François Bar (Annenberg School of Comm) Prof. Nonny De La Pena (School of CinemaNc Arts) 27
28 Crowdsourcing Geo- Crowdsourcing Outsourcing a set of tasks to a set of worker (e.g., Amazon Mechanical Turk) SpaNal Crowdsourcing Crowdsourcing a set of spa9al tasks to a set of workers SpaNal task: task related to a locanon Workers can perform the spanal tasks by physically traveling to the locanons of tasks E.g., take a picture of Tommy- Trojan before the USC- UCLA game 28
29 IMSC Worker GeoCrowd Requester In Collabora9on w Prof. Zimmermann, NUS SpaNal Crowdsourcing Server (SC- server) 29
30 PBS NEWSHOUR InauguraNon Coverage with IMSC GeoCrowd 15 journalism students cover the streets of Washington DC during the event using Android phones 30
31 AutomaNc Panoramic Picture GeneraNon 31
32 Sample 2012 Research Result SpaNal Crowdsourcing L. Kazemi and C. Shahabi, GeoCrowd: Enabling Query Answering with SpaNal Crowdsourcing, ACM SIGSPATIAL GIS, Redondo Beach, CA, November ApplicaNon: Health, TransportaNon, Energy, etc. 32
33 Big Data IMSC Intelligent TransportaNon Big data acquisinon, storage and access Intelligent Surveillance Big data analyncs Intelligent Campus Big data collecnon MediaQ 33
34 Unmet Need Smartphones can capture high resolunon imagery & video limited storage on the phone (e.g., 64 GB on MicroSD card), unreliable (e.g., lost phone, broken phone) Need for a reliable searchable backend storage solunon E.g., drop- box, Google docs, icloud are very difficult to search as they are file- based systems Users need to be able to share their pictures and videos E.g., media outlets buying image/video coverage of an event from willing parncipants that happen to be in the area, etc. 34
35 MediaQ Keyword search Map- based search Search results With accuracy ranng Time Slider 35 People Search
36 Real- World ApplicaNons: Real Systems: TransportaNon TransDec Security, Health, Energy Janus Social, Urban Real Research: IEEE ICDM 12 (SIGKDD) VLDB 12 (SIGMOD) BigData is REAL! Not a toy problem! GeoCrowd CommercializaNon: ClearPath Geosemble ACMGIS 12 (SIGSPATIAL) MediaQ 36
37 OUTLINE IMSC Background & Overview Vision: Geo- Immersion Big Data IMSC Closing Remarks 37
38 Research Influence 38
39 EducaNon 39
40 InternaNonal CollaboraNon Namseoul University, Korea (Christy Shin) Media Management Research Lab, NUS, Singapore (Roger Zimmermann) Civil and Environmental Engineering, Technion, Israel (Barak Fishbain) Tsinghua University, China (Lin Zhang, Yunhao Liu) Touch Center, NCKU, Taiwan (Kevin Yang) InsNtute of InformaNon Systems and ApplicaNons, NTHU, Taiwan (Von- Wun Soo, Yi- Shin Chen) Hong Kong University of Science & Technology (Lei Chen, Dimitris Papadias) 40
41 In the News 41
42 IMSC Advisory Board 27 Members from Academia, Government & Industry Government: NGA (1) Academia (7) UCSB, UMN, UI, UCB, UCI, Tsinghua, NSU, Tokyo U., RAND Industry (19) BAE (1) Chevron (1) Facebook (1) Google (2) HP (1) IBM (1) Intel (2) Microsoq (2) NEC (1) Northrop Grumman (2) Oracle (2) Samsung (1) 42
43 Industry Sponsorship Status Intel Chevron Microsoq Google HP Labs NGC IBM Qualcomm Vizio Samsung Oracle BAE Facebook ESRI Navteq NEC Amount Raised Year- 1 Year- 2 Year- 3 43
44 IMSC Value Add to its Partners Our vision, expernse, background & experience in Fundamental and applied research MulNdisciplinary research Integrated system development Our test- beds Government/Federal customers Industry Partners Global Reach EducaNonal Presence 44
45 QuesNons? 45
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