Buildings’ sustainability is one of the crucial parts for achieving urban sustainability. Applied to buildings, life-cycle assessment encompasses the analysis and assessment of the environmental effects of building materials, components and assemblies throughout the entire life of the building construction, use and demolition. Estimate of carbon emissions is essential and crucial for an accurate and reasonable life-cycle assessment. Addressing the need for more research into integrating analysis of real-time and automatic recording of key indicators for a more accurate calculation and comparison, this paper aims to design a real-time recording model of these crucial indicators concerning the calculation and estimation of energy use and carbon emissions of buildings based on a Radio Frequency Identification (RFID)-based system. The architecture of the RFID-based carbon emission recording/tracking system, which contains four functional layers including data record layer, data collection/update layer, data aggregation layer and data sharing/backup layer, is presented. Each of these layers is formed by RFID or network devices and sub-systems that operate at a specific level. In the end, a proof-of-concept system is developed to illustrate the implementation of the proposed architecture and demonstrate the feasibility of the design. This study would provide the technical solution for real-time recording system of building carbon emissions and thus is of great significance and importance to improve urban sustainability.

We report a new digital shearing method for extracting the three-dimensional displacement vector data from double-exposure holograms. With this method we can manipulate both the phase and the amplitude of the recorded signal, which, like optical correlation analysis, is inherently immune to imaging aberration. However, digital shearing is not a direct digital implementation of optical correlation, and a considerable saving in computation time results. We demonstrate the power of the method by matlab simulation and discuss its performance with reference to optical analysis.

Driver error and reaction is one of the major causes of road accidents. In-vehicle driver behaviour warning system can help to prevent a significant number of road accidents. However, current technologies struggle to provide satisfactory performance for the underlying data transmission/sharing layer between vehicles and infrastructure to support the system. In this paper, we present our way for approaching the design of such a system. First, we identify the primary contributing factors to road accidents and analyse the data transmission/sharing requirement for tackling them based on the study of historical accident records. We then investigate the feasibility of adopting various RFID technologies as the underlying technology to address those requirements in order to support active accident prevention. Our work demonstrated the effectiveness of RFID technologies in retrieving information from roadside and other vehicles for providing reliable and affordable solutions in future driver warning systems or autonomous vehicle control systems.