In the past, fire detection and fire suppression were separate endeavors. One system detected fire and another contained it. Unlike traditional detection systems, who simply say there is a fire, Deep Sight tells you where in 3D space the fire is using recent advances in computer vision technology. Since our system knows where fire is in 3D space, it can put out a fire in a targeted manner, unlike sprinklers. This “targeted suppression” is our key value proposition as it decreases damages from fire and water. However, “targeted suppression” is a new concept to the industry and gaining industry acceptance will be critical. The first step to industry acceptance is a proof of concept prototype which can demonstrate the potential effectiveness of Deep Sight to museums, insurance agencies, and code writing bodies. Concurrent with this step is obtaining IP that will allow to confidently engage with the industry and our potential customers.
In museums, the story of the human race is told. Deep Sight will protect our story by detecting and suppressing fires faster, keeping safe those items that hold a part of us within them. From an economic standpoint, museums will minimize their risk of loss and will potentially see lower insurance by using our system. In the future we see Deep Sight expanding beyond just museums, protecting the human story wherever it may take place.
What I Will Do With $5,000
We will use the $5000 for two main purposes. First we will use $2100 to buy 3 different types of cameras, which will allow us to prove our concept, collect a data set of fires (needed for machine learning), and determine which camera type will be best for the final design. Second, we will put the remainder of our money towards acquisition of our IP, which will allow us to more openly discuss our idea with potential customers and members of the industry.