Tayf is a plant camera with the world’s fastest mobile processor on board and with features never seen before, it can recognise diseases of the plants with deep learning in real time from their unique light reflectance and generate prescription for irrigation, pesticide, herbicide or fertilizer.
Origin of Technology: Turkey
Like all other multispectral cameras, Tayf gathers data, but main difference is, it can generate the necessary prescription about the plant and send the coordinate information to compatible machinery to do all processing automatically, it can create the real life FarmVille all by itself
It can cut the time of processing NDVI and generate results without need of an engineer.
Stage: Proof of Concept
Time to Market: 1-3 year
IP Number: TR2016/17566
IP Status: Pending
We -literally- don’t have any competitior on this planet about the topic being. We are quantum leap ahead of closest invention we’ve seen, which we made it before they did and it was a live-stream NDVI camera. Currently UAV NDVI market size is about $2.8B, by 2020 it will reach $4.8B, the camera industry or autonomous control systems will have value estimation about $90B by 2025 and all of the unmanned vehicles will use deep learning cameras to navigate themselves.
We already have 2 key partners, one of them focussed on UAV and another UGV, we’re planning to use their platform to launch our product. In a near future we’ll be launching our own handheld devices but technology is not there yet. With investment, we’re going to acquire high-end sensors and create a design team to create MVP. For the martket research and business relations, we got in contact with the largest potato farmer in Turkey and met with rice producers. Since we all have agricutlural production background we know how hard to keep track of diseases on the field. Our goal is the make this product globally available and even send it to mars for martian food production facilities.
Create the MVP and field test till get the right results between 30 to 100 meter flight range using fixed wing and other unmanned aerial vehicles.
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