Open AccessOntology-based multi-sensor information integration model for urban gardens and green spaces
Author(s) -
Xin Hu,
Qiang Chen,
Mingliang Du
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/615/1/012023
Subject(s) - ontology , ontology based data integration , computer science , process ontology , suggested upper merged ontology , data integration , upper ontology , smart city , information integration , information retrieval , data model (gis) , data science , database , data mining , world wide web , artificial intelligence , internet of things , semantic web , philosophy , epistemology
With the continuous development of smart landscape and the application of IOT technology in urban gardens and green spaces, the environmental data and soil data collected by various sensors are conceptually inconsistent with each other. The information derived from the data is mostly used independently, and the relationship between data and information in the database is relatively simple, and it is impossible to explore deeper associations between information. To solve this problem, a multi-sensor information integration model based on ontology is studied. Based on the characteristics of the perception terminal data of smart garden management, this article analyzes the ontological relationship between various resources of the garden and green space, and builds the ontology description model of the urban garden and green space based on the five-tuple structure of the ontology and the seven-step method to realize the information integration of perception data and the description of the relationship between sensors, this model provides a unified information model for the smart garden system to achieve information sharing. This paper describes the construction of local ontology and the related methods of global mapping, illustrate the construction process of ontology, and conducts ontology reasoning and ontology query according to the result of construction.