Paper Info
Title
Automated Discovery of Network Cameras in Heterogeneous Web Pages
Abstract
AbstractReduction in the cost of Network Cameras along with a rise in connectivity enables entities all around the world to deploy vast arrays of camera networks. Network cameras offer real-time visual data that can be used for studying traffic patterns, emergency response, security, and other applications. Although many sources of Network Camera data are available, collecting the data remains difficult due to variations in programming interface and website structures. Previous solutions rely on manually parsing the target website, taking many hours to complete. We create a general and automated solution for aggregating Network Camera data spread across thousands of uniquely structured web pages. We analyze heterogeneous web page structures and identify common characteristics among 73 sample Network Camera websites (each website has multiple web pages). These characteristics are then used to build an automated camera discovery module that crawls and aggregates Network Camera data. Our system successfully extracts 57,364 Network Cameras from 237,257 unique web pages.
Year
DOI
Venue
2022
10.1145/3450629
ACM Transactions on Internet Technology
Keywords
DocType
Volume
Web indexing, web crawling, web scraping, service discovery and interfaces, sensor networks, data streaming, multimedia streaming, network cameras, web cameras
Journal
22
Issue
ISSN
Citations 
1
1533-5399
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Ryan Dailey192.02
Aniesh Chawla200.34
Andrew Liu300.34
Sripath Mishra400.68
Ling Zhang500.34
Josh Majors600.34
Yung-Hsiang Lu700.68
George K. Thiruvathukal800.34