Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A Complex Event Processing Based Framework for Intelligent Environments
Date
2013-07-19
Author
Avenoglu, Bilgin
Eren, Pekin Erhan
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
176
views
0
downloads
Cite This
The variety and volume of data produced by devices and sensors in Intelligent Environments (IEs) pose difficulties regarding their collection, analysis and delivery. More specifically, extraction of high level information valuable for the users requires specialized analysis techniques. In this study, we present a framework incorporating complex event processing (CEP) and publish-subscribe based messaging for addressing such needs. Within the framework, data are collected from heterogeneous data sources to go through CEP based analysis, and then the results are delivered to interested recipients. The components of the framework are loosely-coupled through the use of event driven architecture (EDA) in the form of a publish-subscribe messaging system. This enables the use of different CEP engines without requiring the modification of other components in the framework. Similarly, new data sources and delivery end-points can be as easily integrated into the framework. A real life prototype implementation is also provided for validation. The prototype includes various event producers such as electret microphone, light, temperature, motion, magnetic, optical sensors, RFID (Radio Frequency Identification) readers, smart phones, and other software systems, which are deployed in a classroom setting. End users receive relevant raw data and high level information according to their preferences, through the use of web and mobile applications. The results suggest the applicability of the framework for IEs. The prototype implementation in the classroom shows that using different event producers helps improve the analysis results and CEP is an appropriate method for data analysis in IEs.
Subject Keywords
Intelligent environments
,
Complex event processing
,
Multi-modal sensors
,
Event-driven architecture
,
Publish-subscribe
URI
https://hdl.handle.net/11511/31941
DOI
https://doi.org/10.3233/978-1-61499-286-8-12
Collections
Graduate School of Informatics, Conference / Seminar
Suggestions
OpenMETU
Core
A visual programming framework for distributed Internet of Things centric complex event processing
Gökalp, Mert Onuralp; Koçyiğit, Altan; Eren, Pekin Erhan (2019-03-01)
Complex Event Processing (CEP) is a promising approach for real-time processing of big data streams originating from Internet of Things (IoT) devices. Even though scalability and flexibility are key issues for IoT applications, current studies are mostly based on centralized solutions and restrictive query languages. Moreover, development, deployment and operation of big-data applications require significant amount of technical expertise. Hence, a framework that provides a higher abstraction level programmi...
A Hybrid Approach for Process Mining Using From to Chart Arranged by Genetic Algorithms LNCS San Sebastian Spain June 2010
Esgin, Eren; Karagöz, Pınar (2010-06-18)
In the scope of this study, a hybrid data analysis methodology to business process modeling is proposed in such a way that; From-to Chart, which is basically used as the front-end to figure out the observed patterns among the activities at realistic event logs, is rearranged by Genetic Algorithms to convert these derived raw relations into activity sequence. According to experimental results, acceptably good (sub-optimal or optimal) solutions are obtained for relatively complex business processes at a reaso...
A Cognitive Routing Protocol for Bio-Inspired Networking in the Internet of Nano-Things (IoNT)
Al-Turjman, Fadi (Springer Science and Business Media LLC, 2020-10-01)
In this paper, we propose a framework for data delivery in nano-scale networks, where numerous wireless sensors are distributed on a human body, small object, tiny plant root, etc. Our framework caters for green energy-efficient applications in the Internet of Nano Things (IoNT) where data is relayed via nano-routers from a multifarious nanonodes towards a gateway connected to a large-scale network such as the Internet. We consider the entire network energy while choosing the next hop for our routed packets...
A Graph Based Big Data Model for Wireless Multimedia Sensor Networks
Küçükkeçeci, Cihan; Yazıcı, Adnan (2016-10-08)
Wireless multimedia sensor networks are of interest to researchers from different disciplines and many studies have been proposed in a wide variety of application domains, such as military surveillance systems, environmental monitoring, fault monitoring and distributed smart cameras in the last decade. In a wireless sensor network, a large number of sensors can be deployed to monitor target areas and autonomously collect sensor data. This produces a large amount of raw data that needs to be stored, processe...
A Mobile sensing framework for audience emotion analysis
Kepucka, Eldjon; Temizel, Alptekin; Department of Information Systems (2014)
The main objective of this thesis is to develop a multi-modal framework which facilitates simple data collection using mobile sensing on smartphones from an audience, for the duration of an experimental study. Current solutions primarily rely on custom mobile sensing platforms which are expensive to develop and complicated to apply. While there are a number of mobile sensing platforms developed for smartphones targeting different domains, such as transportation and air pollution they are not designed to be ...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. Avenoglu and P. E. Eren, “A Complex Event Processing Based Framework for Intelligent Environments,” 2013, vol. 17, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/31941.