ICT enabled participatory urban planning and policy development: The UrbanAPI project

Purpose: The aim of this paper is to present the effectiveness of participatory information and communication technology (ICT) tools for urban planning, in particular, supporting bottom-up decision-making in urban management and governance. Design/methodology/approach: This work begins with a presentation on the state of the art literature on the existing participatory approaches and their contribution to urban planning and the policymaking process. Furthermore, a case study, namely, the UrbanAPI project, is selected to identify new visualisation and simulation tools applied at different urban scales. These tools are applied in four different European cities - Vienna, Bologna, Vitoria-Gasteiz and Ruse - with the objective to identify the data needs for application development, commonalities in requirements of such participatory tools and their expected impact in policy and decision-making processes. Findings: The case study presents three planning applications: three-dimensional Virtual Reality at neighbourhood scale, Public Motion Explorer at city-wide scale and Urban Growth Simulation at city-region scale. UrbanAPI applications indicate both active and passive participation secured by applying these tools at different urban scales and hence facilitate evidence-based urban planning decision-making. Structured engagement with the city administrations indicates commonalities in user needs and application requirements creating the potential for the development of generic features in these ICT tools which can be applied to many other cities throughout Europe. Originality/value: This paper presents new ICT-enabled participatory urban planning tools at different urban scales to support collaborative decision-making and urban policy development. Various technologies are used for the development of these IT tools and applied to the real environment of four European cities. © Emerald Group Publishing Limited

Modelo de un entorno virtual inteligente basado en la percepción y el razonamiento de sus elementos con un personaje para la generación de realismo

Los Entornos Virtuales Inteligentes (EVI) están compuestos por la unión de elementos tomados de dos importantes áreas de la computación como son la Realidad Virtual y la Inteligencia Artificial, las cuales tienen múltiples aplicaciones en diferentes campos de investigación. A su vez, un EVI debe estar compuesto por los siguientes niveles: geométrico, cinemático, cognitivo y comportamental. Las limitaciones en un EVI se observan en el realismo que se obtiene a través de las sensaciones que emula el computador y que son percibidas por el usuario a través de sus sentidos. Dicho realismo, recae también, en el comportamiento e interacción con los elementos de un Entorno Virtual (percepción y razonamiento), necesario en aplicaciones de interés científico, de tipo militar, entrenamientos en medicina, en la preservación de patrimonio cultural, en la educación, en los videojuegos, entre otras. En esta tesis se propone un modelo de Entorno Virtual Inteligente, que basado en la percepción y el razonamiento de sus elementos con un personaje, permita generar realismo. Para alcanzar este objetivo, se propone inicialmente un modelo geométrico y cinemático como base necesaria para el modelo de Entorno Virtual Inteligente y con ello, incrementar el desempeño del EVI en los niveles comportamental y cognitivo. En estos niveles, se implementan posteriormente, diferentes técnicas de Inteligencia Artificial aplicadas a la percepción y el razonamiento y después de comparaciones a través de diferentes métricas, se escoge la Red Neuronal Artificial que es en la que se apoya principalmente el modelo. A lo largo del desarrollo de la tesis se realizó un trabajo experimental, que valida que el modelo propuesto funciona flexible y adecuadamente, independiente del área de aplicación.Abstract: Intelligent Virtual Environments (IVE) are composed by the union of elements taken from two important areas of computing, as such the Virtual Reality and the Artificial Intelligence, which have multiple applications in various research fields. At the time, an IVE should be composed of the following levels: geometric, kinematic, cognitive and behavioral. The IVE limitations are observed in the realism obtained through of the senses that a computer emulate and the user perceives these sensations through your senses. That realism, also falls, in the behavior and interaction with the elements of a virtual environment (perception and reasoning), realism necessary in applications of scientific interest such as; military style, training in medicine, cultural heritage, education, videogames, among others. In this thesis, a model of Intelligent Virtual Environment is proposed, which based on the perception and reasoning of its elements with a character, it can achieve realism. To achieve this goal, initially a geometric and kinematic model is proposed as a basis for the model of Intelligent Virtual Environment, and then increase performance of IVE in behavioral and cognitive levels. At these levels, subsequently are implemented, different AI techniques applied to perception and reasoning, and after comparisons across different metrics, is chosen an Artificial Neural Network to supports the model. Throughout the development of the thesis an experimental work is made, which validates that the proposed model works flexible and properly, independent of the application area.Doctorad

Semantic Reflection for Intelligent Virtual Environments

Latoschik ME, Fröhlich C. Semantic Reflection for Intelligent Virtual Environments. In: Proceedings of the IEEE VR 2007. 2007: 305-306.We introduce semantic reflection as an architectural concept for Intelligent Virtual Environments (IVEs). SCIVE, a dedicated IVE simulation core, combines modularity with close coupled integrative aspects to provide semantic reflection on multiple layers from low-level simulation core logic, specific simulation modules' appli- cation definitions, to high-level semantic environment descriptions. SCIVE's Knowledge Representation Layer provides the central organizing structure which ties together data representations of simulation modules, e.g., for graphics, physics, audio, haptics, or AI etc., while it additionally allows bidirectional knowledge driven ac- cess between the modules

Towards Intelligent VR: Multi-Layered Semantic Reflection for Intelligent Virtual Environments

Latoschik ME, Fröhlich C. Towards Intelligent VR: Multi-Layered Semantic Reflection for Intelligent Virtual Environments. In: Proceedings of the Graphics and Applications GRAPP 2007. 2007: 249-259.This paper introduces semantic reflection, a novel concept for a modular design of intelligent applications. SCIVE, a simulation core for intelligent Virtual Environments (IVEs), provides semantic reflection on multiple layers: SCIVE’s architecture grants semantic driven uniform access to low-level simulation core logic, to specific simulation modules’ application definitions, as well as to high-level semantic environment descriptions. It additionally provides a frame to conveniently interconnect various simulation modules, e.g., for graphics, physics, audio, haptics, or AI etc. SCIVE’s Knowledge Representation Layer’s base formalism provides the central organizing structure for the diverse modules’ data representations. It allows bidirectional knowledge driven access between the modules since their specific data structures and functions are transitively reflected by the semantic layer. Hence SCIVE preserves, integrates and provides unified access to the development paradigms of the interconnected modules, e.g., scene graph metaphors or field route concepts etc. well known from todays Virtual Reality systems. SCIVE’s semantic reflection implementation details are illustrated following a complex example application. We illustrate how semantic reflection and modularity support extensibility and maintainability of VR applications, potential for automatic system configuration and optimization, as well as the base for comprehensive knowledge driven access for IVEs

TOWARDS INTELLIGENT VR Multi-Layered Semantic Reflection for Intelligent Virtual Environments

Abstract: This paper introduces semantic reflection, a novel concept for a modular design of intelligent applications. SCIVE, a simulation core for intelligent Virtual Environments (IVEs), provides semantic reflection on multiple layers: SCIVE’s architecture grants semantic driven uniform access to low-level simulation core logic, to specific simulation modules ’ application definitions, as well as to high-level semantic environment descriptions. It additionally provides a frame to conveniently interconnect various simulation modules, e.g., for graphics, physics, audio, haptics, or AI etc. SCIVE’s Knowledge Representation Layer’s base formalism provides the central organizing structure for the diverse modules ’ data representations. It allows bidirectional knowledge driven access between the modules since their specific data structures and functions are transitively reflected by the semantic layer. Hence SCIVE preserves, integrates and provides unified access to the development paradigms of the interconnected modules, e.g., scene graph metaphors or field route concepts etc. well known from todays Virtual Reality systems. SCIVE’s semantic reflection implementation details are illustrated following a complex example application. We illustrate how semantic reflection and modularity support extensibility and maintainability of VR applications, potential for automatic system configuration and optimization, as well as the base for comprehensive knowledge driven access for IVEs.