Environmental Tech use AI for Sustainability Applications

Sustainable Futures, an initiative within the Nvidia Inception program for cutting-edge start-up's, is supporting 750+ companies globally focused on agriculture, carbon capture, clean energy, climate and weather, environmental analysis, green computing, sustainable infrastructure and waste management.

We have listed several of these and included some additional companies which are working on various AI applications to model our planetary resources, consumption and highlight where efficiencies and positive feedback loops can be created.

Energy Management:

DeepMind (a subsidiary of Alphabet) uses AI to optimise energy usage in data centres, reducing energy consumption and promoting sustainability.

Grid4C employs AI algorithms to optimize energy distribution, enabling better integration of renewable energy sources into the grid.

Smart Grids:

Autogrid utilizes AI to manage and optimize electricity grids, facilitating the integration of renewable energy and demand-side management.

ABB develops AI-powered solutions for smart grids, improving efficiency and resilience while reducing environmental impact.

Water management:

Our planet will experience a 40% global water deficit by 2030 under projected climate scenarios. AI can contribute to more effective water treatment processes and better water infrastructure management by detecting potential defects ahead of time.

With AI, new insights can be created, enabling better water reuse and its flow rates. AI can also play a crucial role in measuring water supply and sanitation, ensuring water quality and proper treatment standards. For water utility companies, AI can create an overall monitoring system leading to optimised water supply for planning and predicting future investment requirements.

Renewable Energy Optimization:

Vestas Wind Systems employs AI for predictive maintenance of wind turbines, maximizing energy production while minimizing downtime and maintenance costs.

Sunverge Energy uses AI to optimize energy storage systems, enhancing the efficiency and reliability of renewable energy integration.

Waste management:

Recycling is crucial for a circular economy, however there are varying levels that take place. Approximately 75% of waste produced by consumers is recyclable, but only 30% gets recycled (with much of it actually sent to developing nations, only to be then burnt).

ZenRobotics based in Finland was the first company to apply AI and robotics in a demanding waste processing environment. The company combines AI and robotics to recover recyclables from waste. Their technology solution allows greater flexibility in waste sorting, enabling operators to react quickly to changes in a waste stream and increasing the rate of recovery and purity of secondary materials.

A startup named SamurAI has innovated a similar solution also, whilst a similar waste disposal solution has been developed by a Polish tech startup called Bin-e. The team there have created a robotic system designed to recognise and sort waste according to its type.

Waste Robotics develops AI-powered robotic systems for waste sorting, enhancing recycling efficiency and diverting more waste from landfills.

Banyan Nation employs AI in waste tracking and management, enabling better resource recovery and recycling in the circular economy.

Agriculture:

By combining with the Internet of Things (IoT), AI is set to revolutionise agriculture. While agriculture may not be the first field that comes to mind when considering AI applications, AgriTech is rapidly gaining importance. Similar to many other discussed industries, agriculture faces significant challenges, including a limited and stressed workforce and the severe impacts of climate change.

Pastoral AI, has created the world's first low-cost regenerative grazing platform to increase efficiencies and improve biodiversity. The company has identified the possibility to reduce pasture degradation and CO2 emissions by 30 per cent on given farming locations across the world.

John Deere has been using machine-learning for its farming equipment for precision agriculture, optimizing resource usage and minimizing environmental impact.

Indigo Agriculture utilizes AI to improve crop yields and reduce reliance on chemical inputs, promoting sustainable agriculture practices.

Circular Economy:

In our previous circular economics blog here, we looked into how technology and AI can be leveraged to aid circular economics. Some of the later developments have been from companies such as;

IBM applies AI in supply chain management to optimize resource utilization and minimize waste generation, contributing to circular economic models.

SAP develops AI-driven solutions for waste management and recycling, enabling better resource recovery and material reuse.

AI as an enabler and accelerator

AI can be an enabler and accelerator of the transition to a circular economy, where AI technologies can be applied to three key aspects of a circular economy: design circular products, components and materials, operate circular business models and optimise infrastructure, to ensure circular flows of products and materials.

Creating greater awareness and understanding of how AI can support a circular economy is essential to encourage applications in design, business models, and infrastructure.

At BSI, we supply AI technology solutions and offer options for hosting systems in sustainable 100% renewable powered data centres.