On Application of Ontology and Consensus Theory to Human-Centric IoT: An Emergency Management Case Study
2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS) (2015)
Dec. 11, 2015 to Dec. 13, 2015
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DSDIS.2015.64
Involving human in the loop of IoT offers numerous advantages to a wide range of applications including emergency management. However, building a collaborative system that is capable of effectively responding to an emergency in timely manner introduces a number of fundamental challenges. It requires effective discovery of crowds for a given emergency and also successful communication of information across discovered crowds of different domains. In addition, the crowds may not agree on a single solution when group decision making is required. Therefore, consensus management such that consensus is achieved in a timely manner is yet another challenge. In this research, we propose a framework that uses ontology-based discovery and data modelling and consensus theory to tackle the aforementioned issues. We demonstrate the efficiency of the discovery and consensus management approach via a case study and set of experiments, respectively.
Ontologies, Emergency services, Semantics, Cognition, Data models, Interoperability, Vehicle dynamics
A. V. Dastjerdi, M. Sharifi and R. Buyya, "On Application of Ontology and Consensus Theory to Human-Centric IoT: An Emergency Management Case Study," 2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS), Sydney, Australia, 2015, pp. 636-643.