Research Article
Towards an Ontology development for automated applications in Smart City environment of SmartME Project
@INPROCEEDINGS{10.4108/eai.25-10-2016.2266527, author={Nidhi Kushwaha and OP VYAS and Carlo Puliafito and Ranjana Vyas}, title={Towards an Ontology development for automated applications in Smart City environment of SmartME Project}, proceedings={10th EAI International Conference on Performance Evaluation Methodologies and Tools}, publisher={ACM}, proceedings_a={VALUETOOLS}, year={2017}, month={5}, keywords={linked open sensor data semantic web sensor iot prot\^{e}g\^{e} smart city big data lod data processing linked data smartme}, doi={10.4108/eai.25-10-2016.2266527} }
- Nidhi Kushwaha
OP VYAS
Carlo Puliafito
Ranjana Vyas
Year: 2017
Towards an Ontology development for automated applications in Smart City environment of SmartME Project
VALUETOOLS
ACM
DOI: 10.4108/eai.25-10-2016.2266527
Abstract
Cities are becoming everyday smarter, with an increasing multitude of electronic nodes distributed throughout the territory. These range from rather simple ones, such as sensors/actuators, but also smartphones, to more complex ones, such as data centers and workstations. Citizens may have a central role in consuming, but also producing the data. The consequence of all this is that the amount of data collected is enormous and these data need to be properly processed in order to make the most of them. Unfortunately, there are several challenges in data processing, but exploiting the Semantic Web technologies and linking data among them is the right way to face them. This paper introduces the SmartME project developed by the University of Messina, Italy, and discusses the technologies and approaches that can be utilized to properly manage the collected data. In this paper, we are working towards the incorporation of semantic layer with the SmartMe project of University of Messina. In this, our contribution is to build logic for maintaining sensors and their collected information and query them in more meaningful way for getting accurate results. Also, we have presented a way of modifying a previously developed ontology, SSN, and customized it for our purpose.