Data-driven solutions
Data-driven solutions refer to the use of data analytics, machine learning, and other computational techniques to analyze and make sense of data collected from various sources to address challenges in infrastructure and city planning. This approach involves collecting and analyzing large volumes of data, including real-time data, to provide insights into how cities and infrastructure are functioning and to identify areas for improvement. Data-driven solutions also enable real-time monitoring and decision-making, which can improve the efficiency and effectiveness of infrastructure and city services. For instance, smart sensors can be used to detect traffic congestion and adjust traffic signals in real-time to alleviate congestion.
By using data-driven solutions, researchers and policymakers can make more informed decisions that are based on empirical evidence. For example, by analyzing data on traffic patterns and air quality, researchers can develop better transportation systems that reduce congestion and pollution. Similarly, by analyzing data on weather patterns and flooding, researchers can design infrastructure that is more resilient to extreme weather events. Data can be used to analyze traffic patterns, pedestrian flows, and public transport usage to identify areas that need improvement in terms of accessibility and mobility. Real-time data can also be used to monitor and optimize energy consumption in buildings, water usage, and waste management. This approach is already revolutionizing the way infrastructure and cities are planned, designed, and managed by enabling evidence-based decision-making and improved services for citizens.
UKCRIC's research agenda focuses on developing data-driven solutions for infrastructure and cities that are sustainable, resilient, and inclusive. By leveraging data and digital technologies, UKCRIC researchers are able to develop more innovative and effective approaches to addressing the challenges facing our cities and infrastructure systems, and develop a more comprehensive understanding of the complex and interrelated systems that underpin the built environment.