Mobile information systems agendas are increasingly becoming an essential part of human life and they play an important role in several daily activities. These have been developed for different contexts such as public facilities in smart cities, health care, traffic congestions, e-commerce, financial security, user-generated content, and crowdsourcing. In GIScience, problems related to routing systems have been deeply explored by using several techniques, but they are not focused on security or crime rates. In this paper, an approach to provide estimations defined by crime rates for generating safe routes in mobile devices is proposed. It consists of integrating crowd-sensed and official crime data with a mobile application. Thus, data are semantically processed by an ontology and classified by the Bayes algorithm. A geospatial repository was used to store tweets related to crime events of Mexico City and official reports that were geocoded for obtaining safe routes. A forecast related to crime events that can occur in a certain place with the collected information was performed. The novelty is a hybrid approach based on semantic processing to retrieve relevant data from unstructured data sources and a classifier algorithm to collect relevant crime data from official government reports with a mobile application.

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Ontologies are widely used as a tool for representing knowledge in Artificial Intelligence more specifically in qualitatively knowledge representation and reasoning, for example, to represent concepts and their relationships. On the other hand, virtual reality has several applications in different fields: such as in medical systems, computer-aided design and education as a virtual learning environment. In both cases, qualitative representations are necessary to perform any qualitative reasoning task. In this paper, we see VRML and Java 3D. Which are formal languages are used to describe objects in 3D. We analyze the similarities between them to define an application ontology with the aim to represent virtual reality environments, independently of the programming language. Then a spatial ontology is defined to describe topological, directional and metric relation which can be used to describe the basic operations in a 3D scene to build a complex environment. Finally, these two ontologies are seen that can be constructed independently but integrated together whether needed.

This Works propose the benefits of developing an expert system, specialized to evaluate visual diseases. The pathologies of interest in this work are: Diabetic retinopathy, macular degeneration, retinitis pigmentosa and glaucoma. These visual impairments are common in Mexico. The purpose of develop a medical expert system is to evaluate visual diseases with the aim of help people who have no resources or live in a distant town from the major cities in Mexico. We found that the majority of people affected are: in a productive age, have chronic conditions and misinformed about those problems. The number of ophthalmologist is reduced and the often they live in cities. Additionally, we show the type of reasoning methods are used to develop medical expert systems. And we conclude that it is necessary a knowledge representation to store the knowledge of the experts.