Building Intelligent Semantic Educational System (ISES) Based on Ontology and Semantic Web Mining

Smart cities are new and evolving concept based on innovative information and communication technologies. Thinks and Internet of Thinks (IoT) must be core technologies in smart cities. Thinks’ services and maintenance must be managed through digital planes. Location based service (LBS) are service targeted to a wide range of users. The increasing number of LBS will have a bad impact on transitions. One of the objectives of building smart cities is to reduce the traffic congestion and transportation demand. This paper utilizes Geographic Information System (GIS) and spatial analysis techniques for decision support of LBS. the objective is the advance determination of the best service location for covering services requirement based on three factors: location, time and type of service.
Education is the greatest service required for humanity. This paper focuses on considering service factors and client requirements by applying a developed GIS platform to inform service provider by the assets required to cover customer needs and meets smart cities goals. While 1st stage of primary schools accepts students in age of 6 years, the suggested platform determines schools’ plane for 5 years in advance, according to: student location, date of birth, and education type requirement.
The suggested platform was applied on Mansoura city, Egypt. That platform was designed by: using geoprocessing tools, and Python programming language of GIS (arcPy) for implementing functions and procedures (“split by attribute”, “periodic service plane”). Geocoding processing is used for converting students’ addresses to spatial location, which is necessary for geo-relational analysis.