Olayemi Usman
Olayemi Usman is a passionate and dedicated quantity surveyor with a strong focus on sustainable building practices and digital construction techniques. Currently pursuing a Master of Science degree in BIM-Enabled Sustainable Building at the University of Northampton in England, Olayemi's research centres on reducing energy consumption and carbon emissions in construction projects, aligning with the United Nations goal of achieving Net Zero. As the co-founder of a tech solution company in Africa, Olayemi has led efforts to train over 1500 professionals and students in the AECO sector in the implementation of Building Information Modeling (BIM). With a deep understanding of the importance of digital tools and data analysis in optimizing building performance, Olayemi is a certified Itwin Developer by Bentley Systems, showcasing his expertise in utilizing digital tools to drive innovative solutions in the construction industry. Olayemi's passion for sustainable building practices and digital construction has led him to become a respected thought leader in the industry. His insights and experiences are frequently shared at conferences and events, where he is known for his ability to inspire and motivate others in the industry. Through his work and research, Olayemi seeks to create a more sustainable future for all by reducing the carbon footprint of construction projects and promoting the adoption of digital construction techniques. As a data analyst, Olayemi understands the critical role of real-time data management in enhancing building performance and reducing carbon emissions. His unique blend of technical expertise, passion for sustainable building practices, and commitment to digital construction techniques positions him as a valuable asset to the construction industry. Olayemi's work serves as an inspiration to many professionals and students seeking to create a more sustainable future through digital innovation and sustainable building practices.
What to expect during the event
Digital twin technology has been gaining traction in the building industry as a tool for improving building performance, reducing energy consumption, and enhancing occupant comfort. However, the successful implementation of digital twin technology for building operations requires effective real-time data management techniques. In this presentation, I will explore the real-time data management techniques used in digital twin technology for building operations, including data acquisition and processing, data analysis, and visualisation techniques. I will discuss the challenges and opportunities associated with real-time data management in digital twin technology, including the integration of digital twin technology with building management systems, the use of sensor networks and Internet of Things (IoT) devices, and the application of machine learning and artificial intelligence techniques. This presentation will cover the application of machine learning and artificial intelligence techniques in digital twin technology for real-time data management, including advanced analytics and predictive modeling. Attendees will gain an understanding of the role of these techniques in building operations and how they can be used to achieve significant improvements in building performance. Key Learning Outcomes will involve the following; 1. Understanding real-time data management techniques 2. Knowledge of the challenges and opportunities associated with real-time data management 3. Familiarity with the integration of digital twin technology with building management systems 4. Knowledge of the application of machine learning and artificial intelligence techniques 5. Awareness of the potential benefits of real-time data management in digital twin technology
Real-time Data Management for Digital Twin in Building Operation
