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:
| Application | Description | Example |
| Deforestation monitoring | Deforestation and land use changes cause more than 10% of global greenhouse gas emissions. Using AI to monitor forest sounds and detect illegal logging | Non-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 industry | Using AI to optimize industrial processes and reduce carbon emissions | Fero Labs’ AI-driven optimization software, which reduces the amount of mined ingredients used in steel production |
| Energy efficiency in buildings | Using AI to optimize heating, ventilation, and air conditioning systems in buildings | Arup’s Neuron app, which uses IoT sensors to gather data on building energy usage and optimize HVAC systems |
| Wildlife conservation | Using AI to monitor and protect endangered species | Rouxcel Technology’s AI-enabled bracelets for rhinos, monitor their movements and alert authorities to potential threats |
| Smart agriculture | Using AI to optimize farming processes and reduce waste | John Deere’s AI-powered system, which optimizes planting, irrigation, and fertilization for crops |
| Climate modelling | Using AI to make predictions about climate patterns and inform climate policy | The UK’s Met Office, which uses AI to model climate patterns and inform government policy on climate change |
| Renewable energy management | Using AI to manage and optimize renewable energy sources | IBM’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:
| Challenge | Example |
| Data quality and quantity | AI models require high-quality data to perform accurately, and the availability of large and diverse datasets can be limited |
| Bias in data and algorithms | For 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 deployment | E.g., deploying sensors to collect environmental data in remote locations or deploying drones to monitor wildlife may require significant investment. |
| Ethical considerations | E.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)
