Projects
Software Framework for Intelligent Adaptive Management of Complex Facilities
| Code |
Science |
Field |
| T120 |
Technological sciences |
Systems engineering, computer technology |
intelligent control, complex event processing, event stream processing, ECA-rules, semantic Web
Organisations (1)
, Researchers (1)
0112 University of Belgrade, Institute "Mihailo Pupin"
| no. |
Code |
Name and surname |
Research area |
Role |
Period |
No. of publicationsNo. of publications |
| 1. |
08693 |
Sanja Vraneš |
Artificial intelligence |
Head |
2011 - 2019 |
16 |
Abstract
The aim of the project is to embed the newest research results in the field of event processing into coherent, generic software framework that will facilitate the development of applications of integrated, intelligent and adaptive control of complex facilities, including the most critical, infrastructural ones. In the state-of-the art facility, management and control systems, various underlying technical subsystem are being managed in isolation, using independent SCADA systems, usually with the man-in-the-loop, while the most complex, emergency situations are usually fully managed by emergency personnel. The advancements in various areas of IT, especially in event-processing, enable the development of an interoperable, multiparadigm platform that can detect the complex events and simultaneously and synchronously manage all the underlying subsystems automatically. In case of significant uncertainty of complex events’ provenance, the automated reaction is replaced by recommendation/decision support to the operator. Efficiency of developed generic environment will be proven using two completely different use cases, one in airport management, the other in control of complex facility, with local microgrid, connecting on-site renewable energy sources and storages, with ability to buy the missing power from the grid, or sell the excess power back to it. Apart form numerous software solutions, the project’s outcomes will also be 40 publications, 2 patents and 3 PhD theses.