WHAT IS VULTURE?
Welcome to Vision Analytics, we are the AI and Computer Vision division of Seitech. We specialize in early fire detection using a computer vision algorithm. This algorithm allows us to detect fire or smoke at its initial stage, providing valuable time to respond.
Our system allows for an immediate and accurate review of the alarm. Through the platform, the user can visualize the specific area and, in case of confirmed risk, take appropriate action.
The early fire detection solution we offer has multiple benefits:
Speed and Efficiency
Meet our process
Using artificial intelligence and machine learning, our algorithm analyzes real-time data to identify fire patterns and make accurate predictions, adapting to various conditions and environments.
Upon detecting a possible fire, the alert system quickly notifies relevant parties through multiple channels, such as SMS, email, and push notifications.
Our intuitive dashboard allows users to monitor and manage the situation in real-time, interact with the alert system, and deploy emergency resources if necessary.
Our system monitors and protects facilities 24/7, ensuring that quick measures are taken at any sign of fire.
Thanks to our artificial intelligence algorithm, we are able to identify fire patterns in their initial stage.
The system can be customized according to the specific needs of each situation and is capable of adapting to different conditions and types of fires.
Frequently Asked Questions
Of course. The solution is designed to utilize any camera as long as it has an IP address or RTSP protocol.
Of course, it will depend on visibility at any given time, but it can usually range between 1,000 and 3,000 hectares.
The solution is scalable in terms of the number of cameras (we are prepared logistically and computationally) and in terms of capacity, expanding detection capabilities with other algorithms.
The processing and configuration of alerts can be set up within a matter of days (depending on the cameras). The set up of the platform, with style guide and parameterization, in approximately one month. The fully operational tool (with included training) will be ready in less than 3 months.
Our solution can be integrated with different data sources (AEMET, Xeocode…), as well as tools and systems owned by the administration. The only requirement is to have the appropriate documentation of the APIs.
Yes, of course there can be false alarms. We always prefer a false alarm to a «non-detection», but ad hoc training of the algorithm minimizes them. Additionally, the confidence parameters of the neural network allow the sensitivity to be adapted to weather conditions and fire risk.