EXPLORING FACTORS THAT INFLUENCES THE ADOPTION OF ICT-BASED BUILDING AND CONSTRUCTION INFORMATIC PLATFORMS

Construction industry has witnessed introduction of automation processes in executing construction operations. Introduction of green building concept, building automation, intelligent buildings and all informatics platform. In this study stratified sampling method was used in data collection. The knowledge gap was bridged with the aid of data collated through questionnaires distributed to 950 respondents Population sample 100 residential accommodation was used while sample size of 95 was picked from the population. The study respondents for this research includes facility managers and professionals that have been informed in the use of informatics platform in solving built environment related problems. Existing informatics platforms were explored, level of awareness of the available informatics platform was also explored and later the factors that influences effective adoption of informatics platform in solving problems in building and construction works was presented in this study

The Building Informatics Approach to Modelling Construction Quality Assurance Parameters to Prevent Structural Collapse of Building

Building collapses have become a global phenomenon and continue to occur unabated, with properties and lives being lost on a daily basis all over the world.  This study addresses important issues that have been identified to be the major causes of the problem of building collapses. The study aims to develop parameters that could be used to assure quality processes in building construction using building informatics, with the intention to prevent building structure collapse on construction sites.  In order to achieve this, a random survey technique was used based on the purposive method, in the form of a structured questionnaire distributed to 100 respondents. 100 structured questionnaires, designed using a Likert scale from 1 to 5, were employed in the data collection. The random sampling technique was used for the sample selection. The data collected were analysed using a relative agreement index and subjected to factor rotation, from which factors with high eigenvalues were extracted and used to create a model aimed at supplying information on building collapse prevention. The study reveals that the construction industry is filled with many unqualified personnel, poor supervision; non-compliance with designs (i.e. a structural issue) as a result of the addition of under designed or over designed components which can cause excessive loading; lack of regard for environmental issues; inappropriate planning of construction activities; poor maintenance; and, most importantly, the use of inferior materials in other to save costs, All these issues affect the construction industry and contribute to building failure