MASC: um modelo computacional para cidades inteligentes assistivas

Abstract

The growing expansion of information and communication technology has been providing opportunities for the development of services for the metropolitan areas. These solutions are aimed at improving the quality of life, minimize environmental impacts, improve health service, minimize spending on natural resources, facilitate trade actions, improve security and bear the increasing number of people at the cities. Initiatives have been proposed by researchers and implemented in cities defined as “Smart Cities”, however none of these fully address the demands made by persons with disabilities (PwDs) and does not make use of the interactions generated by these. One way to promote accessibility for PwD is using mobile computing, communications infrastructure, collaborative resources and actions by PwD to offer intelligent accessibility services. In the Smart Cities infrastructure is already available, requiring only mobile computing and resource management layer, consisting of sensors and cloud computing. In order to improve the quality of life of these people and promote accessibility, it is important support using ICT. One way to promote accessibility to PwDs, is using mobile computing, communications infrastructure and collaborative capabilities in order to offer intelligent accessibility services. This paper presents the Model for Assistive Smart Cities (MASC) for this scenario. Unlike the proposed approaches the MASC uses the interactions of PwD to compose trails which will be offered as a service also is generic because it supports different types of disabilities and is suitable for massive applications. The model includes ontology for people, resources, disability, environments and trails. A prototype was developed to evaluate performance and functionality. This evaluation was conducted with data generated by a simulator contexts in a region located in downtown São Leopoldo - RS. The results indicated that model meets massive applications, getting information to generate trails and supporting the users, PwD, health professionals and public administration.