The indoor localization system using vision for multiple mobile robots

This paper presents the development of an indoor localization system using camera vision. The localization system has a capability to determine 2D coordinate (x, y) for a team of mobile robots, Miabot. The experimental results show that the system outperforms our existing sonar localizer both in accuracy and a precision.

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.

Work performance, productivity and indoor air

Temperature, relative humidity, and air quality all affect the sensory system via thermo receptors in the skin and the olfactory system. Air quality is mainly defined by the contaminants in the air. However, the most persistent memory of any space is often its odor. Strong, emotional, and past experiences are awakened by the olfactory sense. Odors can also influence cognitive processes that affect creative task performance, as well as personal memories and moods. Besides nitrogen and oxygen, the air contains particles and many chemicals that affect the efficiency of the oxygenation process in the blood, and ultimately the air breathed affects thinking and concentration. It is important to show clients the value of spending more capital on high-quality buildings that promote good ventilation. The process of achieving indoor-air quality is a continual one throughout the design, construction, commissioning, and facilities management processes. This paper reviews the evidence.

Effect of internal partitioning on indoor air quality of rooms with mixing ventilation - basic study

The internal partitioning, which is frequently introduced in open-space planning due to its flexibility, was tested to study its effects on the room air quality as well as ventilation performance. For the study, physical tests using a small model room and numerical modeling using CFD computation were utilized to evaluate different test conditions employing mixing ventilation from the ceiling. The partition parameters, such as its location, height, and the gap underneath, as well as contaminant source location were tested under isothermal conditions. This paper summarizes the results from the study.

Developing a method to characterize indoor environmental parameters in naturally ventilated classrooms

Until recently, there has been little investigation concerning the poor indoor air quality (IAQ) in classrooms. Despite the evidence that the educational building systems in many of the UK institutions have significant defects that may degrade IAQ, systematic assessments of IAQ measurements has been rarely undertaken. When undertaking IAQ measurement, there is a difficult task of representing and characterizing the environment parameters. Although technologies exist to measure these parameters, direct measurements especially in a naturally ventilated spaces are often difficult. This paper presents a methodology for developing a method to characterize indoor environment flow parameters as well as the Carbon Dioxide (CO2) concentrations. Thus, CO2 concentration level can be influenced by the differences in the selection of sampling points and heights. However, because this research focuses on natural ventilation in classrooms, air exchange is provided mainly by air infiltration. It is hoped that the methodology developed and evaluated in this research can effectively simplify the process of estimating the parameters for a systematic assessment of IAQ measurements in a naturally ventilated classrooms.

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.