This paper describes a methodology to assess the energy performance of residential buildings starting from the semantic 3D city model of Vienna. Space heating, domestic hot water and electricity demand are taken into account. The paper deals with aspects related to urban data modelling, with particular attention to the energy-related topics, and with issues related to interactive data exploration/visualisation and management from a plugin-free web-browser, e.g. based on Cesium, a WebGL virtual globe and map engine. While providing references to existing previous works, only some general and introductory information is given about the data collection, harmonisation and integration process necessary to create the CityGML-based 3D city model, which serves as the central information hub for the different applications developed and described more in detail in this paper. The work aims, among the rest, at developing urban decision making and operational optimisation software tools to minimise non-renewable energy use in cities. The results obtained so far, as well as some comments about their quality and limitations, are presented, together with the discussion regarding the next steps and some planned improvements.

This paper describes a methodology to assess the energy performance of residential buildings starting from the semantic 3D city model of Vienna. Space heating, domestic hot water and electricity demand are taken into account. The paper deals with aspects related to urban data modelling, with particular attention to the energy-related topics, and with issues related to interactive data exploration/visualisation and management from a plugin-free web-browser, e.g. based on Cesium, a WebGL virtual globe and map engine. While providing references to existing previous works, only some general and introductory information is given about the data collection, harmonisation and integration process necessary to create the CityGML-based 3D city model, which serves as the central information hub for the different applications developed and described more in detail in this paper. The work aims, among the rest, at developing urban decision making and operational optimisation software tools to minimise non-renewable energy use in cities. The results obtained so far, as well as some comments about their quality and limitations, are presented, together with the discussion regarding the next steps and some planned improvements.

Yes / Agent-based modeling techniques are ideal for modeling massive complex systems such as insect colonies or biological cellular systems and even cities. However these models themselves are extremely complex to code, test, simulate and analyze. This paper discusses the challenges in using agent-based models to model complete cities as a complex system. In this paper we argue that Cities are actually a collection of various complex models which are themselves massive multiple systems, each of millions of agents, working together to form one system consisting of an order of a billion agents of different types - such as people, communities and technologies interacting together. Because of the agent numbers and complexity challenges, the present day hardware architectures are unable to cope with the simulations and processing of these models. To accommodate these issues, this paper proposes a Tera (to denote the order of millions)-modeling framework, which utilizes current technologies of Cloud computing and Big data processing, for modeling a city, by allowing infinite resources and complex interactions. This paper also lays the case for bringing together research communities for interdisciplinary research to build a complete reliable model of a city.