Multi-modal Neural Network for Traffic Event Detection

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

8 Citations (Scopus)

Abstract

Cities are composed of complex systems with Cyber, Physical, and Social (CPS) components. The advances in the Internet of Things (IoTs) and social networking services help people understand the dynamics of cities. Traffic event detection is an important while complex task in transportation modeling and management of smart cities. In this paper, we address the task of detecting traffic events using two types of data, i.e. physical sensor observations and social media text. Unlike most existing studies focused on either analysing sensor observations or social media data, we identify traffic events with both types of data that may complement each other. We propose a Multi-modal Neural Network (MMN) to process sensor observations and social media texts simultaneously and detect traffic events. We evaluate our model with a real-world CPS dataset consisting of sensor observations, event reports, and tweets collected from Twitter about San Francisco over a period of 4 months. The evaluation shows promising results and provides insights into the analysis of multi-modal data for detecting traffic events.

Original languageEnglish
Title of host publication2019 IEEE 2nd International Conference on Electronics and Communication Engineering, ICECE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages26-30
Number of pages5
ISBN (Electronic)9781728147840
DOIs
Publication statusPublished - Dec 2019
Event2nd IEEE International Conference on Electronics and Communication Engineering, ICECE 2019 - Xi'an, China
Duration: 9 Dec 201911 Dec 2019

Publication series

Name2019 IEEE 2nd International Conference on Electronics and Communication Engineering, ICECE 2019

Conference

Conference2nd IEEE International Conference on Electronics and Communication Engineering, ICECE 2019
Country/TerritoryChina
CityXi'an
Period9/12/1911/12/19

Keywords

  • LSTM
  • deep learning
  • multi-modal network
  • recurrent neural network
  • traffic event detection

Cite this