| Title |
Event Detection for Urban Dynamic Data Streams |
| ID_Doc |
42926 |
| Authors |
Nechifor, S; Stefan, I; Fischer, M; Puiu, D |
| Title |
Event Detection for Urban Dynamic Data Streams |
| Year |
2016 |
| Published |
|
| DOI |
10.1109/ICDMW.2016.113 |
| Abstract |
This paper presents a framework for processing the data generated by Smart City sensors and IoT data streams in real-time. The scope of processing is to detect various event patterns from the raw data. The framework is extensible because at any moment new data sources can be registered or new specific event detection mechanism can be deployed. The framework offers a HTTP interface which can be used to provide details about each data stream. In order to connect to the heterogeneous data source end points and fetching the observations a concept of simple adaptable data wrappers is introduced. Having the streams registered into the framework, the domain expert can deploy (using a Java API) the event detection mechanism. The domain expert (maybe with some help from an application developer) has only to develop the data wrappers and event detection modules. Once the modules are developed, they can be deployed any time and on any numbers for different sensors of the same type, respective similar events to be detected. |
| Author Keywords |
|
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000401906900008 |
| WoS Category |
Computer Science, Information Systems; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
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