Researchers are exploring the use of compact vision-language models and other machine learning frameworks for efficient context-aware classification, with applications including fire detection. Some studies focus on early fire detection in specific settings, such as subway tunnels, while others investigate real-time fire and smoke detection using vision transformers. The approaches being developed incorporate various techniques, including spatiotemporal learning and hybrid models combining large language models with machine learning.