Visual Navigation: Constructing and Utilizing Simple Maps of an Indoor Environment

The goal of this work is to navigate through an office environmentsusing only visual information gathered from four cameras placed onboard a mobile robot. The method is insensitive to physical changes within the room it is inspecting, such as moving objects. Forward and rotational motion vision are used to find doors and rooms, and these can be used to build topological maps. The map is built without the use of odometry or trajectory integration. The long term goal of the project described here is for the robot to build simple maps of its environment and to localize itself within this framework.

Body-centric ultra-wideband multi-channel characterisation and spatial diversity in the indoor environment

This study presents the findings of an empirical channel characterisation for an ultra-wideband off-body optic fibre-fed multiple-antenna array within an office and corridor environment. The results show that for received power experiments, the office and corridor were best modelled by lognormal and Rician distributions, respectively [for both line of sight (LOS) and non-LOS (NLOS) scenarios]. In the office, LOS measurements for t and tRMS were both described by the Normal distribution for all channels, whereas NLOS measurements for t and t were Nakagami and Weibull distributed, respectively. For the corridor measurements, LOS for t and t were either Nakagami or normally distributed for all channels, with NLOS measurements for t and t being Nakagami and normally distributed, respectively. This work also shows that achievable diversity gain was influenced by both mutual coupling and cross-correlation co-efficients. Although the best diversity gains were 1.8 dB for three-channel selective diversity combining, the authors present recommendations for improving these results. © The Institution of Engineering and Technology 2013.

A statistical characterization of shadowed device-to-device communications in an indoor environment

This paper presents the results of a measurement campaign aimed at characterizing and modeling the indoor radio channel between two hypothetical cellular handsets. The device-to-device channel measurements were made at 868 MHz and investigated a number of different everyday scenarios such as the devices being held at the user's heads, placed in a pocket and one of the devices placed on a desktop. The recently proposed shadowed k-μ fading model was used to characterize these channels and was shown to provide a good description of the measured data. It was also evident from the experiments, that the device-to-device communications channel is susceptible to shadowing caused by the human body.

Propagation modelling and measurements in a populated indoor environment at 5.2 GHz

Human occupants within indoor environments are not always stationary and their movement will lead to temporal channel variations that strongly affect the quality of indoor wireless communication systems. This paper describes a statistical channel characterization, based on experimental measurements, of human body effects on line-of-sight indoor narrowband propagation at 5.2 GHz. The analysis shows that, as the number of pedestrians within the measurement location increases, the Ricean K-factor that best fits the empirical data tends to decrease proportionally, ranging from K=7 with 1 pedestrian to K=0 with 4 pedestrians. Level crossing rate results were Rice distributed, while average fade duration results were significantly higher than theoretically computed Rice and Rayleigh, due to the fades caused by pedestrians. A novel CDF that accurately characterizes the 5.2 GHz channel in the considered indoor environment is proposed. For the first time, the received envelope CDF is explicitly described in terms of a quantitative measurement of pedestrian traffic within the indoor environment.

Designing the indoor environment for people

Intelligent buildings should provide a multi-sensory experience so that visual, aural, tactile, olfactory and gustatory senses are stimulated appropriately. A lack of environmental stimuli produces a boring and unsatisfying environment. It is now known that the environment affects people at deeper levels than, say, health and safety, and consequently it can modify moods and work performance. A holistic approach is proposed which recognizes that the physical environment together with social, organizational and personal factors can enhance the productivity of occupants. This approach provides a footprint for the design of healthier and more sustainable workplaces.

Understanding the indoor environment through mining sensory data - A case study

A wireless sensor network (WSN) is a group of sensors linked by wireless medium to perform distributed sensing tasks. WSNs have attracted a wide interest from academia and industry alike due to their diversity of applications, including home automation, smart environment, and emergency services, in various buildings. The primary goal of a WSN is to collect data sensed by sensors. These data are characteristic of being heavily noisy, exhibiting temporal and spatial correlation. In order to extract useful information from such data, as this paper will demonstrate, people need to utilise various techniques to analyse the data. Data mining is a process in which a wide spectrum of data analysis methods is used. It is applied in the paper to analyse data collected from WSNs monitoring an indoor environment in a building. A case study is given to demonstrate how data mining can be used to optimise the use of the office space in a building.

A model of intelligent building energy management for the indoor environment

People's interaction with the indoor environment plays a significant role in energy consumption in buildings. Mismatching and delaying occupants' feedback on the indoor environment to the building energy management system is the major barrier to the efficient energy management of buildings. There is an increasing trend towards the application of digital technology to support control systems in order to achieve energy efficiency in buildings. This article introduces a holistic, integrated, building energy management model called `smart sensor, optimum decision and intelligent control' (SMODIC). The model takes into account occupants' responses to the indoor environments in the control system. The model of optimal decision-making based on multiple criteria of indoor environments has been integrated into the whole system. The SMODIC model combines information technology and people centric concepts to achieve energy savings in buildings.

Physiological expression of human thermal comfort to indoor operative temperature in the non-HVAC environment

A physiological experiment was carried out in a naturally ventilated, non-HVAC indoor environment of a spacious experimental room. More than 300 healthy university students volunteered for this study. The purpose of the study was to investigate the human physiological indicators which could be used to characterise the indoor operative temperature changes in a building and their impact on human thermal comfort based on the different climatic characteristics people would experience in Chongqing, China. The study found that sensory nerve conduction velocity (SCV) could objectively provide a good indicator for assessment of the human response to changes in indoor operative temperatures in a naturally ventilated situation. The results showed that with the changes in the indoor operative temperatures, the changing trend in the nerve conduction velocity was basically the same as that of the skin temperature at the sensory nerve measuring segment (Tskin(scv)). There was good coherent consistency among the factors: indoor operative temperature, SCV and Tskin(scv) in a certain indoor operative temperature range. Through self-adaptation and self-feedback regulation, the human physiological indicators would produce certain adaptive changes to deal with the changes in indoor operative temperature. The findings of this study should provide the baseline data to inform guidelines for the development of thermal environment-related standards that could contribute to efficient use of energy in buildings in China.

Assessing how retrofit of traditional buildings impacts indoor environment and occupant’s thermal comfort

Buildings consume a large amount of energy, in both their use and production. Retrofitting aims to achieve a reduction in this energy consumption. However, there are concerns that retrofitting can cause negative impacts on the internal environment including poor thermal comfort and health issues. This research investigates the impact of retrofitting the façade of existing traditional buildings and the resulting impact on the indoor environment and occupant thermal comfort. A Case building located at the University of Reading has been monitored experimentally and modelled using IES software with monitored values as input conditions for the model. The proposed façade related retrofit options have been simulated and provide information on their effect on the indoor environment. The findings show a positive impact on the internal environment. The data shows a 16.2% improvement in thermal comfort after retrofit is simulated. This also achieved a 21.6% reduction in energy consumption from the existing building.