Michael Jansen, CEO of Cityzenith, outlines the role that Artificial Intelligence can play in reducing carbon emissions in construction
No greater challenge faces our generation than that of reducing our impact upon the climate of our planet.
There is much work to be done, but the emergence of international climate treaties and, notably the 2016 Paris Agreement, give us reason to be hopeful.
Paris agreed to limit global warming to well below 2°C, and preferably 1.5°C, compared to pre-industrial levels and encourages countries to formulate and submit long-term low greenhouse gas emission development strategies (LT-LEDS), to ensure a cohesive international plan.
But there is a major problem common to all: cities produce more than 70% of global carbon emissions (source: UN) and the world’s top 100 most-polluting cities alone produce a staggering 18% of those emissions.
Digital Twin technology using cutting-edge data and AI can change this dramatically though, facilitating more efficient cities and creating smart new ones.
Digital Twins are 3D virtual replicas of buildings, infrastructure, and physical assets, fully interconnected with the data in and around them, enabling optimised project performance and helping to predict future outcomes.
Our software platform, SmartWorldOS aggregates, integrates, analyses, and visualises all project and property information on a single platform, uniting often disparate software the customer might already use and making them ‘play nicely together’.
As an architect myself, I know this is liberating; it enables architects, construction professionals, planners, and building managers to easily interact with real-time data via the Digital Twin, identifying potential inefficiencies and correcting them whether it be a new build or an existing asset.
We have worked with top companies to help solve highly complex problems like…
- Lowering city ground temperatures by 8°C in Amaravati, India
- Cutting carbon emissions 50-100% in a premier New York City innovation hub
- Aggregating masses of incompatible data into one model for a high-speed UK rail project
We have even spoken to NASA about mapping and managing urban airspace, as US city managers look skywards to reduce ground-level congestion and emissions by using electric powered delivery drones and air taxis.
There are also sound economic reasons for using Digital Twins: the built environment is chronically inefficient, costing hundreds of billions of dollars a year in delays, wasted materials, productivity, and labour.
Savings can be made on productivity, operating and maintenance, and carbon emissions on buildings and infrastructure.
Believe me, the Paris Agreement targets are not just attainable, but easy if we use the right tools.
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