4 Ways AI Helps Business Protect the Environment

With its ability to understand, reason and learn, cognitive technology and artificial intelligence are proving great allies in protecting our planet.

By Julie Yamamoto

Source: Pixabay

Here's how: 

1. Better conservation of natural resources.  By combining satellite imagery, sensors and machine learning, companies and governments are reducing water usage in their operations as well as pinpointing the variables that lead to better soil health. One winery created a cognitive irrigation system that can deliver water in a way that’s situational, hyper-local, automated and self-tuning, helping it cut water use by 25 percent over three years.

2. Earlier pollution detection.  Advanced machine learning and self-organizing mesh networks are helping organizations pinpoint the sources of pollution faster and more accurately, whether air pollution or methane leaks. This enables more targeted mitigation actions that are better for business and the environment, such as improved natural gas operations with reduced emissions.

3. Accelerating sustainable options.  Cognitive technology is accelerating more sustainable energy and product choices for consumers. One of the biggest barriers to widespread use of renewable energy has been forecast accuracy.

Not only is it tough to predict how much renewable energy will be available at a given time on a given day but solar and wind farms are adding to the supply (while decreasing their own demand), making forecasting more difficult. By combining advanced weather forecasting models with cognitive self-learning capabilities, a Vermont-based power company is developing a more precise, automated renewable energy forecast for solar and wind power.

Cognitive technology can also assist with environmental regulation compliance — an important first step toward greater transparency and greener product choices for consumers.

Cognitive technology also can assist with environmental regulation compliance — an important first step toward greater transparency and greener product choices for consumers. Cognitive platforms equipped with natural language capabilities can read large blocks of regulatory text and extract essential obligations, such as a local requirement for a specific label on a product.

4. Learning from nature’s ecosystems.  Policy makers and companies that manage natural resources face an increasingly tough challenge to develop those resources sustainably as they change over time. It’s not always clear how a single stressor, such as salt runoff from roads, affects a natural ecosystem, let alone multiple stressors. Environmental assessments are often manually collected over time, making it more difficult to pinpoint and monitor cause and effect.

One research project in upstate New York is working to advance knowledge in this area. Scientists are analyzing data from environmental sensors around Lake George to build and refine computer models of the lake’s ecosystem. As more data is collected, machine learning will provide a better understanding of what the norms and anomalies are, enabling decision makers to run what-if scenarios and tradeoff analyses for better insights.

Read full article: Green Biz

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• Resource Management
• Technology
• Impact Assessment
• Data Management
• Environment
• Sustainable Water Resource Management
• Water Software
• Environmental Impact
• Data & Analysis