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John K.S. Lau & Assoc Prof C.K. Tham , ECE, NUS
E-mail: {elelksj, eletck}@nus.edu.sg
Hidden Markov Models for
Abnormal Event Processing in
Transportation Data Streams
IEEE ICPADS’12 International Workshop on Scalable
Computing for Big Data Analytics (SC-BDA)
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Motivation
How to leverage computationally expensive model in
detecting abnormal events in real-time?
2
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Contributions
•Application of Hidden Markov Models (HMM) in
identifying not only hidden meaningful events but also
abnormal events. The focus in this work is on
abnormal events.
•Event-Driven Architecture (EDA) for decoupling of
HMM computations from real-time event processing.
3
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Event-Driven Architecture (EDA)
4
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Abnormal Event Processing (AEP)
5
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Abnormal Event Processing (AEP)
6
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Abnormal Event Processing (AEP)
•SELECT tmin, tmax FROM [table name] WHERE [unique
identifier]
– tmin and tmax pre-computed via HMM based on most
recent data. Normal event is within tmin <= t <= tmax.
•SELECT * FROM [stream name] HAVING duration <
tmin OR duration > tmax
– Any incoming event is flagged abnormal in real-time.
7
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Experimental Results
8
HMM
Find highest
probability
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Experimental Results
9
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Experimental Results
10
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Experimental Results
11
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Experimental Results
12
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
Future Works
•Ability to detect more meaningful hidden states such
as accident, heavy rain, flood, etc. besides just general
anomaly.
•Application of Map-Reduce in HMM computations.
13
Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams
JKS Lau & CK Tham
THANK YOU
Questions?
14

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Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams

  • 1. John K.S. Lau & Assoc Prof C.K. Tham , ECE, NUS E-mail: {elelksj, eletck}@nus.edu.sg Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams IEEE ICPADS’12 International Workshop on Scalable Computing for Big Data Analytics (SC-BDA)
  • 2. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Motivation How to leverage computationally expensive model in detecting abnormal events in real-time? 2
  • 3. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Contributions •Application of Hidden Markov Models (HMM) in identifying not only hidden meaningful events but also abnormal events. The focus in this work is on abnormal events. •Event-Driven Architecture (EDA) for decoupling of HMM computations from real-time event processing. 3
  • 4. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Event-Driven Architecture (EDA) 4
  • 5. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Abnormal Event Processing (AEP) 5
  • 6. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Abnormal Event Processing (AEP) 6
  • 7. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Abnormal Event Processing (AEP) •SELECT tmin, tmax FROM [table name] WHERE [unique identifier] – tmin and tmax pre-computed via HMM based on most recent data. Normal event is within tmin <= t <= tmax. •SELECT * FROM [stream name] HAVING duration < tmin OR duration > tmax – Any incoming event is flagged abnormal in real-time. 7
  • 8. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Experimental Results 8 HMM Find highest probability
  • 9. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Experimental Results 9
  • 10. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Experimental Results 10
  • 11. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Experimental Results 11
  • 12. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Experimental Results 12
  • 13. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham Future Works •Ability to detect more meaningful hidden states such as accident, heavy rain, flood, etc. besides just general anomaly. •Application of Map-Reduce in HMM computations. 13
  • 14. Hidden Markov Models for Abnormal Event Processing in Transportation Data Streams JKS Lau & CK Tham THANK YOU Questions? 14