Harnessing AI for Climate Change Mitigation: Predictive Analytics and Modeling

AI enthusiasts in all sectors are finding creative ways to implement artificial intelligence’s predictive analytics and modelling capabilities to mitigate climate change. What are some examples across industries where effective installation yields results?

Smart Grid Management in the Energy Sector

“Urban planners, electricians and engineers are collaborating to grow the grid’s capacity and resilience to support modern demands and green generators.” 

AI is pivotal for this, because the workforce only knows how to design the grid’s needs with big data.

Combined with sensors, AI models discover demand patterns and predict how to optimize resources for the future. Models achieve this by simulating the impact of renewable energy while considering their potential expansion.

However, innovation in the AI space is critical for balance. AI and their data centers will total 8% of electricity by 2030 in the U.S. Big Tech companies like Microsoft and Google are innovating to pare down energy use or match consumption with zero-carbon energy purchases. For the marriage of AI and the grid to work in the long term, contributors must reduce AI energy requirements while amplifying the grid’s potential.

Precision Farming and Food Safety in Agriculture

Agriculture is one of the sectors most affected by climate change when the world is already experiencing food scarcity. Farmers learn the growth cycles of the crops against market demands, drafting models of what the upcoming seasons could look like for staff. AI could help farmers digitize, automate and monitor crops to enhance yield and deliver the most food to communities as they can. 

“AI drones could drop seeds on plots to plant climate-resilient crops or reforest an area to defend against rising waters.” 

The Environmental Protection Agency could improve its water pollution detection abilities by 600%, leveraging machine learning algorithms to help agriculture stay healthy. AI air monitors in hydroponic settings could determine how indoor air quality will impact output. These are other ways a predictive AI could help farmers by informing connected smart devices:

• Weather and natural disaster forecasting
• Soil monitoring
• Livestock health oversight
• Disease and invasive species identification
• Water distribution and consumption
• Pest control dispersal

Fleet Optimization in Transportation

Logistics managers, supply chains and transportation organizations will electrify to reduce one of their most prominent carbon emissions categories. An AI could connect to a carbon ledger platform, tracking emissions as fleets optimize. 

Another fleet optimization hack drivers can use in real time is route optimization. AI integrated into vehicles could assist drivers by immediately responding to traffic data, saving energy by taking a route requiring fewer miles or wear and tear on the vehicle. While one reroute may not seem like monumental emissions reductions in the short term, it saves on vehicle maintenance and wasted battery power from sitting in stop-and-go traffic.

Predictive analytics works best when handling maintenance. AI models become familiar with individual vehicles to extend the fleet’s life span with smarter maintenance scheduling.

AI’s Role in Climate Change Mitigation

AI is one of the most versatile technologies in history. It has the processing and decision-making power to provide humanity with climate insights. It can collect data to educate workforces on how to act or connect to other devices to automate their processes. AI could be the reason all sectors understand their impact with more nuance, taking action that makes the most difference in emissions reductions and wasting fewer natural resources.

Also Read Leveraging Artificial Intelligence (AI) To Reduce Plastic Waste