Development of a historic hearing devices exhibit

This paper discusses historic hearing devices and their benefits to users.

Multi-agent collaboration for decision support in shared zones of intelligent buildings

In domain of intelligent buildings, saving energy in buildings and increasing preferences of occupants are two important factors. These factors are the important keys for evaluating the performance of work environment. In recent years, many researchers combine these areas to create the system that can change from original to the modern work environment called intelligent work environment. Due to advance of agent technology, it has received increasing attention in the area of intelligent pervasive environments. In this paper, we review several issues in intelligent buildings, with respect to the implementation of control system for intelligent buildings via multi-agent systems. Furthermore, we present the MASBO (Multi-Agent System for Building cOntrol) that has been implemented for controlling the building facilities to reach the balancing between energy efficiency and occupant’s comfort. In addition to enhance the MASBO system, the collaboration through negotiation among agents is presented.

Access to historic environments for tourists with disabilities: a compromise?

Historic environments, the basis for heritage tourism, are difficult to access for people with disabilities. Many countries have introduced legislation to promote equal rights for people with disabilities. Historic environments, however, enjoy protection under national planning systems which limit the physical access improvements that can be made. The significance of historic environments for tourism in the UK is outlined. Barriers restricting tourists with disabilities accessing historic sites are reviewed from the heritage tourism service provider's viewpoint. Interests of the major stakeholders are considered in terms of the apparent conflict between conservation and access issues as heritage tourism service providers seek to comply with disability discrimination legislation. From a study of access improvements made by major heritage tourism service providers, good practice is identified. However, physical access improvements to enable tourists with disabilities to visit historic environments are a compromise because of the strength of conservation interests. Questions remain as to whether this compromise is acceptable to the tourist with disabilities and whether intellectual access is an acceptable substitute for physical presence.

Improving flood models using LiDAR: progress and problems

Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.

The need of sustainable buildings construction in the Kingdom of Bahrain

This thesis is aimed to initiate implementing sustainable building construction in the kingdom of Bahrain, i.e. Building-Integration PhotoVoltaic (BIPV) or Wind Energy (BIWE). It highlights the main constrains that discourage such modern concept in building and construction. Three groups have been questioned using a questionnaire. These are the policy and decision makers, the leading consultants and the contractors. The main constrains of the dissemination of BIVP and BIWE, according to the policy and decision makers, are: lack of knowledge and awareness of the public in sustainable technology, low cost of electricity, low cost of gas and oil and difficulty in applying local environmental taxes. The consultants had attributed the constrains to ignorance of life cycle cost of PV and Wind turbines systems, lack of education and knowledge in sustainable design, political system, shortage of markets importing sustainable technologies and client worries in profitability and pay-back period. The contractors are found to be very enthusiastic and ready to take over any sustainable building project and prefer to have a construction manger to coordinate between the design and contracting team. Design and Build is found the favorable procurement method in Bahrain for conducting BIPV or BIWE projects.

Potential of making - Over to sustainable buildings in the Kingdom of Bahrain

Two unique large buildings in the Kingdom of Bahrain were selected for make-over to sustainable buildings. These are the Almoayyed Tower (the first sky scraper) and the Bahrain International Circuit, BIC (The best world Formula 1 Circuit). The amount of electricity extracted from using renewable energy resource (solar and wind), integrated to the buildings-has been studied thoroughly. For the first building, the total solar electricity from the PV installed at the roof and the 4 vertical facades was found 3 017 500 kWh annually (3 million kWh), i.e. daily energy of 8219 kWh (enough to Supply electricity for 171 houses, each is rated as 2 kW house-in Europe the standard is 1.2 kW). This means that the annual solar electricity produced will be nearly 3 million kWh. This correspond to annual CO, reduction of 3000 t (assuming each kWh of energy from natural gas lead to emission of 1 kg of CO2). For the second building (BIC) the solar electricity from PV panels installed at the roof top, fixed at tilt angle of 26 degrees facing south, will provide annual solar electricity of is 2.8 x 10(6) kWh. The solar electricity from PV panels installed on the windows (12,000 m(2)) will be 45.3 x 10(6) kWh. This means that the total annual electrical power from PV panels (windows and roofs) will be nearly 12 MW (32 kW per day). The CO2 reduction will be 48,000 t. Under the carbon trading or CDM scheme the revenue (or the reward) would be (sic)480,000 million annually (the reward is (sic)10 per tonnes of CO2). The BIC circuit can have diversified electricity supply, i.e. from solar radiation (PV), from solar heat (CSP) and from wind (wind turbines), assuring its sustainability as well as reducing the CO2 emission.