The University of the Cordilleras (UC) continues to demonstrate its leadership in “AI for Good” through the College of Information Technology and Computer Science (CITCS) Student Webinar Series. On April 16, 2026, Computer Science student Micheal Rayden Dicang presented a compelling research session titled “Machine Learning for Forest Fire Risk Prediction using Environmental and Fire-Weather”. The webinar focused on a critical question for the region: Can machine learning help predict forest fire risk in Baguio City?
Bridging Data Science and Environmental Safety
The session provided a technical yet accessible look at how advanced algorithms can protect Baguio’s unique ecosystem. Participants explored the full lifecycle of environmental AI research, including:
- Dataset Preparation: The methodology behind collecting and processing fire-weather indicators.
- Model Effectiveness: An evaluation of which machine learning models yield the most accurate results for forest fire risk assessment.
- Feature Importance: Insights into which environmental factors—such as temperature, humidity, and wind—have the most significant impact on fire risk predictions.
Hosted via Google Meet, the event was open to students and researchers, offering E-Certificates to attendees committed to using data science for real-world challenges.
Impact and Real-World Application
The impact of this research extends far beyond the classroom. By identifying high-risk conditions before an ignition occurs, this machine learning approach provides:
- Enhanced Disaster Preparedness: Allowing local authorities to allocate resources more effectively during high-risk weather windows.
- Urban-Forest Resilience: Protecting the Summer Capital’s vital green spaces and the communities that live near them.
- Scientific Literacy: Empowering the local community with “Smarter Data” to drive “Safer Communities”.
SDG Alignment
- SDG 13: Climate Action: By developing predictive tools to mitigate the frequency and severity of forest fires, which are exacerbated by climate change.
- SDG 11: Sustainable Cities and Communities: By integrating smart technology into urban planning to protect Baguio City from environmental disasters.
- SDG 9: Industry, Innovation, and Infrastructure: By showcasing how student-led innovation in AI and Machine Learning can solve localized infrastructure and safety challenges.
