Building networks to work: an ethnographic study of informal routes into the UK construction industry and pathways for migrant up-skilling

The UK construction industry labour market is characterised by high levels of self-employment, sub-contracting, informality and flexibility. A corollary of this, and a sign of the increasing globalisation of construction, has been an increasing reliance on migrant labour, particularly that from the Eastern European Accession states. Yet, little is known about how their experiences within and outside of work shape their work in the construction sector. In this context better qualitative understandings of the social and communication networks through which migrant workers gain employment, create routes through the sector and develop their role/career are needed. We draw on two examples from a short-term ethnographic study of migrant construction worker employment experiences and practices in the town of Crewe in Cheshire, UK, to demonstrate how informal networks intersect with formal elements of the sector to facilitate both recruitment and up-skilling. Such research knowledge, we argue, offers new evidence of the importance of attending to migrant worker’s own experiences in the development of more transparent recruitment processes.

Investigating the level of awareness of building assessment tools in the construction industry of Botswana

Environmental building assessment tools have been developed to measure how well or poorly a building is performing, or likely to perform, against a declared set of criteria, or environmental considerations, in order to achieve sustainability principles. Knowledge of environmental building assessment tools is therefore important for successful design and construction of environmentally friendly buildings for countries. The purpose of the research is to investigate the knowledge and level of awareness of environmental building assessment tools among industry practitioners in Botswana. One hundred and seven paper-based questionnaires were delivered to industry practitioners, including architects, engineers, quantity surveyors, real estate developers and academics. Users were asked what they know about building assessment, whether they have used any building assessment tool in the past, and what they perceive as possible barriers to the implementation of environmental building assessment tools in Botswana. Sixty five were returned and statistical analysis, using IBM SPSS V19 software, was used for analysis. Almost 85 per cent of respondents indicate that they are extremely or moderately aware of environmental design. Furthermore, the results indicate that 32 per cent of respondents have gone through formal training, which suggests ‘reasonable knowledge’. This however does not correspond with the use of the tools on the ground as 69 per cent of practitioners report never to have used any environmental building assessment tool in any project. The study highlights the need to develop an assessment tool for Botswana to enhance knowledge and further improve the level of awareness of environmental issues relating to building design and construction.

The Brazilian Seismographic Integrated Systems (BRASIS): Infrastructure and data management

In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of São Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation. © 2011 by the Istituto Nazionale di Geofisica e Vulcanologia. All rights reserved.

Integration of embedded data processing algorithms inside PAMELA devices

PAMELA (Phased Array Monitoring for Enhanced Life Assessment) SHMTM System is an integrated embedded ultrasonic guided waves based system consisting of several electronic devices and one system manager controller. The data collected by all PAMELA devices in the system must be transmitted to the controller, who will be responsible for carrying out the advanced signal processing to obtain SHM maps. PAMELA devices consist of hardware based on a Virtex 5 FPGA with a PowerPC 440 running an embedded Linux distribution. Therefore, PAMELA devices, in addition to the capability of performing tests and transmitting the collected data to the controller, have the capability of perform local data processing or pre-processing (reduction, normalization, pattern recognition, feature extraction, etc.). Local data processing decreases the data traffic over the network and allows CPU load of the external computer to be reduced. Even it is possible that PAMELA devices are running autonomously performing scheduled tests, and only communicates with the controller in case of detection of structural damages or when programmed. Each PAMELA device integrates a software management application (SMA) that allows to the developer downloading his own algorithm code and adding the new data processing algorithm to the device. The development of the SMA is done in a virtual machine with an Ubuntu Linux distribution including all necessary software tools to perform the entire cycle of development. Eclipse IDE (Integrated Development Environment) is used to develop the SMA project and to write the code of each data processing algorithm. This paper presents the developed software architecture and describes the necessary steps to add new data processing algorithms to SMA in order to increase the processing capabilities of PAMELA devices.An example of basic damage index estimation using delay and sum algorithm is provided.

Intelligent Decision-Making System Frameworks for a Digital Plan of Work: A Theoretical Investigation for the Construction Industry

The construction industry is characterised by fragmentation and suffers from lack of collaboration, often adopting adversarial working practices to achieve deliverables. For the UK Government and construction industry, BIM is a game changer aiming to rectify this fragmentation and promote collaboration. However it has become clear that there is an essential need to have better controls and definitions of both data deliverables and data classification. Traditional methods and techniques for collating and inputting data have shown to be time consuming and provide little to improve or add value to the overall task of improving deliverables. Hence arose the need in the industry to develop a Digital Plan of Work (DPoW) toolkit that would aid the decision making process, providing the required control over the project workflows and data deliverables, and enabling better collaboration through transparency of need and delivery. The specification for the existing Digital Plan of Work (DPoW) was to be, an industry standard method of describing geometric, requirements and data deliveries at key stages of the project cycle, with the addition of a structured and standardised information classification system. However surveys and interviews conducted within this research indicate that the current DPoW resembles a digitised version of the pre-existing plans of work and does not push towards the data enriched decision-making abilities that advancements in technology now offer. A Digital Framework is not simply the digitisation of current or historic standard methods and procedures, it is a new intelligent driven digital system that uses new tools, processes, procedures and work flows to eradicate waste and increase efficiency. In addition to reporting on conducted surveys above, this research paper will present a theoretical investigation into usage of Intelligent Decision Support Systems within a digital plan of work framework. Furthermore this paper will present findings on the suitability to utilise advancements in intelligent decision-making system frameworks and Artificial Intelligence for a UK BIM Framework. This should form the foundations of decision-making for projects implemented at BIM level 2. The gap identified in this paper is that the current digital toolkit does not incorporate the intelligent characteristics available in other industries through advancements in technology and collation of vast amounts of data that a digital plan of work framework could have access to and begin to develop, learn and adapt for decision-making through the live interaction of project stakeholders.