3D Augmented Urban Space Modeling for Smart City

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3D reconstruction of indoor and outdoor buildings is an increasingly important research problem, with large scale efforts underway to recover outdoor models of cities at a global scale (e.g. Google Earth). Unfortunately these models are limited in applications and their true potential not realized. There is also a severe lack of knowledge and understanding in indoor and utility (i.e. power line network) modeling which significantly hinder movements for pushing forward with these semantically rich 3D spatial models for engineering and commercial purposes. One such applications involve the augmentation of the 3D models to urban Information and Communication Technologies (ICT) for providing real time decision support and spatial awareness. These augmented 3D models serve as important model-centric interfaces that could result in unprecedented opportunities for efficiently monitoring and managing infrastructures for supporting urban sustainability and elevating the competitiveness of cities which account for nearly 90% of global population growth, 80% of wealth creation, and 60% of total energy consumption [1].In this current Discovery proposal we propose a comprehensive approach to developing a novel 3D framework with potential applications toward urban sustainability and smart city. By extending and advancing our on-going research for modeling of 3D urban spaces, including building and infrastructure modeling, we will develop innovative techniques for integrating the 3D urban space models and delivering real-time information through augmentation. The objective include 1) creating an innovative crowd-sourced modeling approach that is suitable for large scale generation of indoor models. 2) Enhancing the existing suspension type power line network mapping system to model a wide range of line types through expanding our inventory database. 3) we will develop 3D model-based mobile augmented reality (MAR) applications for indoor and outdoor building environments by introducing an original 3D building model-to-image alignment technique and a new hierarchical Geometric Hash table based on quadtree structure for performing accurate localization. Our grand goal for this research program is to develop and implement a framework for large scale augmented urban space model that includes above and underground facilities, natural objects, and man-made indoor/outdoor structures. The integration of high quality 3D indoor and outdoor urban space models augmented with data from systems such as Building Information Model (BIM) will be significant for moving towards a spatial and context-aware society. Ultimately we aim to remove the gap between virtual and physical spaces where they can be considered as part of a continuum in the same dimension for supporting urban sustainability and smart city.Spatial and context-awareness is the trend for future 3D modeling and augmentation researches as advancements in mobile computing technologies continue to blur the line between virtual and physical spaces. Applications such as MAR recognize and react to the real world content and combine users’ view of reality with location specific information. Such information could be in the form of simple text, image, multi-media, or 3D graphics. Whether it is for facility management, urban planning, navigation, tourism and exploration, such augmented information will provide users with information (in real time) for better decision making on-the-go.