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How AI can help the environment

GS Paper 3

 

Syllabus: Environment/ Science and Technology

 

Source: IE

 

Context: Previously, we talked about the use of AI for Medicine. Here we will see AI applications for the environment.

 

Some examples of how AI can help the environment:

ApplicationDescriptionExample
Deforestation monitoringDeforestation and land use changes cause more than 10% of global greenhouse gas emissions. Using AI to monitor forest sounds and detect illegal loggingNon-profit organization the Rainforest Connection’s “Guardian” devices, which attach acoustic monitoring sensors to trees to detect sounds associated with illegal logging
Carbon footprint reduction in the industryUsing AI to optimize industrial processes and reduce carbon emissionsFero Labs’ AI-driven optimization software, which reduces the amount of mined ingredients used in steel production
Energy efficiency in buildingsUsing AI to optimize heating, ventilation, and air conditioning systems in buildingsArup’s Neuron app, which uses IoT sensors to gather data on building energy usage and optimize HVAC systems
Wildlife conservationUsing AI to monitor and protect endangered speciesRouxcel Technology’s AI-enabled bracelets for rhinos, monitor their movements and alert authorities to potential threats
Smart agricultureUsing AI to optimize farming processes and reduce wasteJohn Deere’s AI-powered system, which optimizes planting, irrigation, and fertilization for crops
Climate modellingUsing AI to make predictions about climate patterns and inform climate policyThe UK’s Met Office, which uses AI to model climate patterns and inform government policy on climate change
Renewable energy managementUsing AI to manage and optimize renewable energy sourcesIBM’s Watson Energy, which uses AI to optimize the performance of wind and solar energy systems

 

Challenges in the use of AI for the Environment:

ChallengeExample
Data quality and quantityAI models require high-quality data to perform accurately, and the availability of large and diverse datasets can be limited
Bias in data and algorithmsFor example, an AI system that recommends conservation areas to protect might not account for cultural significance or indigenous knowledge.
Interpretability E.g., it may be challenging to understand how a deep learning model classifies satellite images to detect deforestation.
Scalability and deploymentE.g., deploying sensors to collect environmental data in remote locations or deploying drones to monitor wildlife may require significant investment.
Ethical considerationsE.g., the use of facial recognition technology to monitor endangered species could violate the privacy of individuals visiting conservation areas.

Conclusion:

AI is a powerful tool that, when used appropriately, can help address some of the most pressing environmental challenges facing our planet. By leveraging the strengths of AI and addressing the challenges it presents, we can develop sustainable and innovative solutions for a better future.

 

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Discuss the applications of AI for use in Environment conservation. (250 Words)