An analysis of the use of photogrammetric sorting to audit construction and demolition waste production on site

This study analyses the area of construction and demolition waste (C & D W) auditing. The production of C&DW has grown year after year since the Environmental Protection Agency (EPA) first published a report in 1996 which provided data for C&D W quantities for 1995 (EPA, 1996a). The most recent report produced by the EPA is based on data for 2005 (EPA, 2006). This report estimated that the quantity of C&DW produced for that period to be 14 931 486 tonnes. However, this is a ‘data update’ report containing an update on certain waste statistics so any total provided would not be a true reflection of the waste produced for that period. This illustrates that a more construction site-specific form of data is required. The Department of Building and Civil Engineering in the Galway-Mayo Institute of Technology have carried out two recent research projects (Grimes, 2005; Kelly, 2006) in this area, which have produced waste production indicators based on site-specific data. This involved the design and testing of an original auditing tool based on visual characterisation and the application of conversion factors. One of the main recommendations of these studies was to compare this visual characterisation approach with a photogrammetric sorting methodology. This study investigates the application of photogrammetric sorting on a residential construction site in the Galway region. A visual characterisation study is also carried out on the same project to compare the two methodologies and assess the practical application in a construction site environment. Data collected from the waste management contractor on site was also used to provide further evaluation. From this, a set of waste production indicators for new residential construction was produced: □ 50.8 kg/m2 for new residential construction using data provided by the visual characterisation method and the Landfill Levy conversion factors. □ 43 kg/m2 for new residential construction using data provided by the photogrammetric sorting method and the Landfill Levy conversion factors. □ 23.8 kg/m2 for new residential construction using data provided by Waste Management Contractor (WMC). The acquisition of the data from the waste management contractor was a key element for testing of the information produced by the visual characterisation and photogrammetric sorting methods. The actual weight provided by the waste management contractor shows a significant difference between the quantities provided.

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.