Yi-Tin Shi

Smart cities represent a new perspective on modern urban development. They involve an information infrastructure environment with application intelligence to improve operational efficiency and welfare effectively. However, understanding how to overcome the barriers of data fragmentation and heterogeneity to exploit the strengths of existing resources and create integration effects remains a key challenge in smart city development. This research focuses on the effective management of heterogeneous sensor systems across different domains to improve quick disaster responses. Metadata serve as the core of this proposed framework, which is designed to not only describe the common and unique characteristics of various IoT-based devices and services, but also to provide necessary information to support the searching, requesting, and updating of required sensors and observation, as well as responding to the upcoming disaster. A workflow consisting of four list types was proposed and used to guide the response procedure. This research specifically aims to enable heterogeneous sensor systems available to all public or private stakeholders to be integrated in a collaborative fashion. While a flooding response was chosen for demonstration in this research, the proposed standard-based framework can be further promoted for other types of smart city applications, not limited to disaster response. The study’s results and implications underscore the importance of effective management of heterogeneous sensor systems and the role of metadata in enabling disaster responses in smart cities.

The installation of closed-circuit television monitors (CCTV) has rapidly increased in number ever since the 11 September attacks. With the advantages of direct visual inspection, CCTV systems are widely used on various occasions that require instantaneous and long-term monitoring. Especially for emergency response tasks, the prompt availability of CCTV offers EOC (Emergency Operation Center) commanders much better action reference about the reported incidents. However, the heterogeneity among the CCTV systems impedes the effective and efficient use and sharing of CCTV services hosted by different stakeholders, making individual CCTV systems often operate on their own and restrict the possibility of taking the best advantages of the huge number of existing CCTV systems. This research proposes a metadata-driven approach to facilitate a cross-domain sharing mechanism for heterogeneous CCTV systems. The CCTV metadata includes a set of enriched description information based on the analysis from the aspects of Who, When, Where, What, Why and How (5W1H) for CCTV. Sharing mechanisms based on standardised CCTV metadata can then suffice the need for querying and selecting CCTV across heterogeneous systems according to the task at hand. One distinguished design is the modelling of the field of view (FOV) of CCTV from the 3D perspective. By integrating with the 3D feature-based city model data, the 3D FOV information not only provides better visualisation about the spatial coverage of the CCTV systems but also enables the 3D visibility analysis of CCTV based on individual features, such that the selection decision can be further improved with the indexing of CCTV and features. As the number and variety of CCTV systems continuously grows, the proposed mechanism has a great potential to serve as a solid collaborated foundation for integrating heterogeneous CCTV systems for applications that demand comprehensive and instantaneous understanding about the dynamically changing world, e.g., smart cities, disaster management, criminal investigation, etc.