Hybrid application to BIM has been designed to reduce the risk of injuries and loss of life from personnel working in confined spaces
Building Information Modelling (BIM) is an intelligent 3D based model process that provides architecture, engineering and construction professionals the tools and understanding to plan, design, construct and manage building and infrastructure in a more efficient manner. In order to address environmental hazards associated with working in buildings, the BIM technology is rapidly evolving to coalesce with other emerging technologies such as wireless sensor motes (WSM).
The School of Engineering and Built Environment of The Birmingham City University and other universities of Lahore and Hong Kong carried out research to further develop a hybrid application programming interface (API) plug-in to BIM. The research relied on the participation of our current BIM Coordinator, Erika Parn. To read the publication click here.
The application called “CosMoS” was originally designed as a system to monitor oxygen and temperature changes for remote sensing of spaces. In its second generation, “CoSMoS” was expanded. The researchers used archived records that proactively learn from data generated from WSN sensors (also known as nodes) that provide real-time monitoring of physical or environmental conditions during the building’s operations and maintenance (O&M) phase of asset management (AM).
The purpose of the system is to enable remote monitoring of confined spaces prior to conducting maintenance. The prototype is hoped to address health and safety issues related to working in confined spaces which frequently results in injury and/or loss of life. CoSMoS prototype has automated new safety applications for Facilities Management (FM) during the asset life-cycle and maintenance phase of a building’s O&M phase of AM. The application allows integrating, for instance, an additional layer of protection to attenuate human acts, errors or omissions that may occur when implementing risk control mitigation strategies.
Further development of CoSMoS presents a significant opportunity. Machine learning algorithms can be applied to develop self-learning and self-improving algorithms to automate predictions for members of the Facility Management team. Lessons learnt from existing buildings can be considered to influence future design developments. CoSMoS could also contemplate the use of technological innovations such as miniaturisation and mass-manufacture of electronic componentry and create hybrid solutions that not only encapsulate a single building but also smart cities and entire economies.