IoT Thing To Service Semantic Matching

Nisrine Bnouhanna, Rute C. Sofia und Alexander Pretschner

inProc IEEE Percom 2021 (Best PhD paper award),

März 2021 · DOI: 10.1109/PerComWorkshops51409.2021.9431128


We propose an automated IoT data source (Thing) to service semantic matching mechanism that selects an optimal set of available IoT data sources in order to satisfy service requirements and needs. The main motivation is to provide a better use of data captured via IoT data sources. To achieve this goal, we propose a three-fold approach: (i) modelling service requirements based on existing service descriptions; (ii) automating the selection of an optimal set of Things that best meet the service requirements; (iii) selecting data processing services that provide additional service requirements.

Stichworte: IIoT, semantic technologies, matchmaking