Abstract
Bee2Fire is a commercial system for forest fire detection, inheriting from the Forest Fire Finder System. Designed in Portugal, it aims to address one of Southern Europe's main concern, forest fires. It is a well known fact that the sooner a wildfire is detected, the quicker it can be put out, which highlights the importance of early detection. By scanning the landscape using regular cameras and Deep Artificial Neural Networks, Bee2Fire searches for smoke columns above the horizon with a image classification approach. After these networks were trained, the system was deployed in the field, obtaining a sensitivity score between 74% and 93%, a specificity of more than 99% and a precision of around 82%.
| Original language | English |
|---|---|
| Title of host publication | ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence |
| Editors | Ana Rocha, Luc Steels, Jaap van den Herik |
| Publisher | SciTePress - Science and Technology Publications |
| Pages | 603-609 |
| Number of pages | 7 |
| Volume | 2 |
| ISBN (Electronic) | 9789897583957 |
| DOIs | |
| Publication status | Published - 2020 |
| Event | 12th International Conference on Agents and Artificial Intelligence, ICAART 2020 - Valletta, Malta Duration: 22 Feb 2020 → 24 Feb 2020 |
Conference
| Conference | 12th International Conference on Agents and Artificial Intelligence, ICAART 2020 |
|---|---|
| Country/Territory | Malta |
| City | Valletta |
| Period | 22/02/20 → 24/02/20 |
Keywords
- Deep Learning
- FastAI
- Forest Fire Detection
- IBM Watson
- PyTorch