2023/12/22 Sustainable Development Goals (SDGs) Presentation Contest

Artificial intelligence (AI) has recently emerged as an innovative tool for forest protection. Deforestation due to climate change and human activities poses a significant threat to the environment, making effective management and protection one of the key challenges of the Sustainable Development Goals (SDGs).

• Monitoring with Satellite Imagery and Drones: AI analyzes satellite images and drone data to monitor forest area changes in real-time. By utilizing deep learning, it can quickly detect anomalies such as wildfires, illegal logging, and poaching, enabling early intervention. This helps forest managers efficiently assess forest conditions and take protective measures.
• Preventing Deforestation with Predictive Models: Machine learning algorithms analyze past forest data along with current weather and topographical information to predict potential future deforestation. For instance, AI can help forecast deforestation risks due to climate change or human activities and assist in developing strategies to mitigate these risks.
• Ecosystem Conservation and Biodiversity Preservation: AI technology is also applied to understand the distribution and habitat changes of species within forests. This enables the protection of habitats for endangered species and the efficient establishment of conservation zones to maintain biodiversity.
• Smart Agroforestry for Forest Conservation: AI-driven smart agroforestry techniques contribute to minimizing forest destruction while improving the efficiency of agricultural and forestry activities. By implementing systems that monitor crop conditions and predict pests and diseases using AI, the environmental impact of agricultural practices on forests can be minimized.

The presentation focused on these examples of AI applications for forest protection and sustainable development, highlighting the importance and potential of AI in future environmental conservation. AI plays a critical role in enhancing environmental monitoring and forecasting, as well as enabling rapid response and prevention strategies against deforestation.