AI and Sustainability: Digital Solutions for the Planet

Artificial intelligence (AI) and sustainability are becoming increasingly interconnected. AI is one of the most powerful tools we have at our disposal to effectively tackle complex climate challenges, from decarbonizing the built environment and transport to sustaining ecosystems. It offers us the ability to approach these complex challenges in new ways, from analyzing massive datasets to facilitating solutions that humans alone could never achieve.

From making buildings smarter and predicting weather patterns to uncovering new insights that are critical to our ecosystems, AI and sustainability are expanding our toolbox for resilience and efficiency. And, as this technology continues to evolve rapidly, we have a responsibility to use it thoughtfully and efficiently to enable real-world impact and facilitate energy management, while keeping ethics and safety top of mind.

AI and sustainability for energy management

At BrainBox AI, a Trane Technologies’ company, we develop solutions using advanced AI to make the built environment, a major contributor to emissions, more energy efficient and sustainable. The goal is to reduce the energy that the built environment consumes every day, along with the emissions it generates. 

Before AI, fully calibrating every building for optimal efficiency would require humans to essentially sit in front of equipment and adjust it constantly — an unrealistic, if not impossible, use of talent and time. Now, with predictive AI, we can optimize the operation of that equipment in real-time. 

We start by modeling different possible combinations of what could happen, then use those predictions to ask ‘how should I operate this equipment now to craft a better future?’ By combining telemetry from inside the building with what’s happening outside, such as data about the weather, we can make smarter operating decisions. That enables us to move from reactive to predictive control: saving energy, reducing emissions and prolonging the life of equipment while cutting maintenance costs. 

This shift towards AI and sustainability also helps address a significant shortage of labor. Consider Aria, an AI-powered virtual mechanical engineer. It can analyze issues rapidly and recommend the right next step, such as changing a belt on a rooftop HVAC unit. This can create outcomes like reduced truck rolls, less time spent on troubleshooting and more time for our technicians to focus on complex issues, augmenting the capacity of our human experts.

And, the built environment is just one arena where AI and sustainability converge. AI is also being applied to the natural world, from forests and oceans to the tiniest ecosystems that keep the planet in balance. Professor David Rolnick, co-founder of the nonprofit Climate Change AI, points to several areas where AI can help tackle climate challenges. From distilling large amounts of unstructured data into useful information to forecasting based on the past and optimizing complicated systems, sustainable AI can accelerate decarbonization. New use cases include using satellite images to identify deforestation in real time, improving predictions that help integrate solar and wind power or figuring out how to change industrial operations to use the least energy and raw materials.

AI can also support ecosystem health and biodiversity. Land use and healthy ecosystems are major contributors to climate resilience, from pollination in agriculture to the health of forests and fisheries. AI-enabled systems are already being deployed around the world to track biodiversity, generating insights into how native species populations are changing, when invasive species appear and when species are declining.