Smoke and fire detection is critical for human safety as well as inventory protection. Traditionally, indoor detection has been accomplished with smoke detectors, which are mounted on ceilings and can provide an audio or other alerts. But outdoor spaces and even large indoor spaces, especially open ones like warehouses or parking lots, can be difficult to monitor using traditional sensors. Fortunately, computer vision technology can be deployed to solve this challenge. Since out-of-the-box AI doesn't usually include fire/smoke detection, a custom AI module is required.
To detect outdoor smoke and fire for one of the largest US tomato distributors, Dragonfruit created an advanced AI model within 6 weeks from start to finish. The model uses existing cameras to detect the presence of either smoke or fire, both indoors as well as outdoors. It's also integrated with Dragonfruit's other platform features so customers can receive real-time alerts, perform video searches and summaries, and tabulate metrics on occurrences.
Best of all, the AI automatically improves over time, with an end-to-end process we call KaiZen that constantly updates the ML model.