Past, present and future mathematical models for buildings (ii)

This article is the second part of a review of the historical evolution of mathematical models applied in the development of building technology. The first part described the current state of the art and contrasted various models with regard to the applications to conventional buildings and intelligent buildings. It concluded that mathematical techniques adopted in neural networks, expert systems, fuzzy logic and genetic models, that can be used to address model uncertainty, are well suited for modelling intelligent buildings. Despite the progress, the possible future development of intelligent buildings based on the current trends implies some potential limitations of these models. This paper attempts to uncover the fundamental limitations inherent in these models and provides some insights into future modelling directions, with special focus on the techniques of semiotics and chaos. Finally, by demonstrating an example of an intelligent building system with the mathematical models that have been developed for such a system, this review addresses the influences of mathematical models as a potential aid in developing intelligent buildings and perhaps even more advanced buildings for the future.

The use of wireless data communication and body sensing devices to evaluate occupants' comfort in buildings

Physiological parameters measured by an embedded body sensor system were demonstrated to respond to changes of the air temperature in an office environment. The thermal parameters were monitored with the use of a wireless sensor system that made possible to turn any existing room into a field laboratory. Two human subjects were monitored over daily activities and at various steady-state thermal conditions when the air temperature of the room was altered from 22-23°C to 25-28°C. The subjects indicated their thermal feeling on questionnaires. The measured skin temperature was distributed close to the calculated mean skin temperature corresponding to the given activity level. The variation of Galvanic Skin Response (GSR) reflected the evaporative heat loss through the body surfaces and indicated whether sweating occurred on the subjects. Further investigations are needed to fully evaluate the influence of thermal and other factors on the output given by the investigated body sensor system.

Assessing the natural ventilation cooling potential of office buildings in different climate zones in China

This paper presents an investigation of the natural ventilation cooling potential (NVCP) of office buildings in the five generally recognised climate zones in China using the Thermal Resistance Ventilation (TRV) model, which is a simplified, coupled, thermal and airflow model. The acceptable operative temperature for naturally conditioned space supplied by the ASHARE Standard 55-2004 has been used for the comfort temperature setting. Dynamic simulations for a typical office room in the five representative cities, which are Harbin, Beijing, Shanghai, Kunming and Guangzhou, have been carried out. The study demonstrates that the NVCP depends on the multiple impacts of climate, the building's thermal characteristics, internal gains, ventilation profiles and regimes. The work shows how the simplified method can be used to generate detailed, indoor, operative temperature data based on the various building conditions and control profiles which are used to investigate the NVCP at the strategic design stage. The simulation results presented in this paper can be used as a reference guideline for natural ventilation design in China.

Energy saving in intelligent buildings - via energy harvesting in wireless sensor networks

Wireless sensor networks (WSNs) have been widely used in pervasive systems such as intelligent buildings. As a vital factor of product cost, energy consuming in WSN has been focused upon, but only via energy harvesting can the problem be overcome radically. This article presents a new approach to harvesting electromagnetic energy for WSN from useless radio frequency (RF) signals transmitted in WSN, with a quantitative analysis showing its feasibility.