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This paper presents the development of stochastic models of occupants' main bedroom window operation based on measurements collected in ten UK dwellings over a period of a year. The study uses multivariate logistic regression to understand the probability of opening and closing windows based on indoor and outdoor environment factors (physical environmental drivers) and according to the time of the day and season (contextual drivers). To the authors' knowledge, these are the first models of window opening and closing behaviour developed for UK residential buildings. The work reported in this paper suggests that occupants' main bedroom window operation is influenced by a range of physical environmental (i.e. indoor and outdoor air temperature and relative humidity, wind speed, solar radiation and rainfall) and contextual variables (i.e. time of day and season). In addition, the effects of the physical environmental variables were observed to vary in relation to the contextual factors. The models provided in this work can be used to calculate the probability that the main bedroom window will be opened or closed in the next 10 minutes. These models could be used in building performance simulation applications to improve the inputs for occupants' window opening and closing behaviour and thus the predictions of energy use and indoor environmental conditions of residential buildings.

The purpose of this paper is presenting a new advanced hardware/software system, boasting two main features: first it performs real time tracking of workers' routes in construction sites; then it implements an algorithm for preventing workers to be involved in hazardous situations. This research step is part of a wider ongoing research concerning the development of a new generation of advanced construction management systems, allowing for real-time monitoring and coordination of tasks, automatic health and safety management, on-site delivering of technical information, capture of as-built documentation. Exploiting the high accuracy provided by the UWB system responsible for position tracking and successfully tested in previous research, our software interface is able to graphically reproduce (and store) the travel patterns of workers. Moreover, it constantly checks if they are accessing hazardous areas, using an algorithm based on a predictive approach: it is conceived to predict in advance whether any worker is approaching a forbidden area, in fact performing virtual fencing. This approach could be easily extended to other applications, too. Some preliminary tests simulated in the DACS laboratory are described and the obtained results discussed.

Abstract. This paper reports a feasibility study which addressed the development of a new, advanced system mainly devoted to automatic real-time health and safety management on construction sites. The preliminary analyses and experiments described in this paper concern two of the most important functionalities which must be included in the system's final release. The first functionality consists in real-time position-tracking of workers involved on construction sites and the second -in a software tool for the prevention of non-authorized access to dangerous zones. This research step is part of a vaster, ongoing research project, addressing the development of a new generation of advanced construction management systems which allow real-time monitoring and coordination of tasks, automatic health and safety management, on-site delivery of technical information and the capture of "as-built" documentation. This paper focuses mainly on the development of a reliable methodology for real-time monitoring of the position of both workers and equipment in outdoor construction sites by applying Ultra Wide Band (UWB) based technologies. This positioning system was then interfaced with a software tool which performs virtual fencing of pre-selected, dangerous areas. Guidelines for the design of the receivers' topology will be addressed and the results of measurements recorded on a typical medium-sized block of flats, during different phases of the construction progress will be summed up. Finally, the preliminary experimental results obtained by the virtual fencing application tool will be presented and used to plan future research objectives.

Underground transportation systems are big energy consumers and have significant impacts on energy consumption at a regional scale. The literature has revealed that the energy consumption for non-traction purposes may be of the same magnitude as the energy used to move rolling stock, and in some cases even greater. However, most of the research conducted so far has focused on the energy demand of rolling stock. This paper investigates the electricity consumption of an underground metro station using data from on-site surveys and measurements. With an average consumption of 217.64 kWh/m(2)/year, the breakdown revealed that the lighting system dominated the underground station's energy consumption (37%). Illuminated advertising signs were found to be responsible for 14% of the total energy consumption, and ventilation accounted for another 14%. The rest of the energy consumption was attributed to systems such as mobile phone signal antenna (12%), the vertical transportation system (8%) and small power devices (5%). Accurate information on energy consumption for non-traction usage is useful for future implementation of energy conservation measures in underground stations, which could result in a reduction of operating costs in the long run.Peer ReviewedPostprint (author's final draft