The original pizza story and what Trapview has to do with it

The official story of pizza Margherita says, that it was invented in 1889 for Queen Margherita's visit of Naples. While different options were tested the one with tomato (red), basil (green), and mozzarella (white) was selected as it best represented Italian flag. The legend was born and the taste of true pizza Margherita (like the one in picture below) is something that is hard to forget.

In order to achieve the perfection a careful ingredients selection is crucial. One of the most important ingredients is tomato. True pizza Margherita (and also pizza Napoletana) use San Marzano tomatoes. Wikipedia says, that San Marzano tomatoes originate from the small town of San Marzano sul Sarno, near Naples, Italy, and were first grown in volcanic soil in the shadow of Mount Vesuvius. One story goes that the first seed of this tomato came to Italian province of Campania in 1770, as a gift from the Viceroyalty of Peru to the Kingdom of Naples, and that it was planted in the area of San Marzano. It is considered the most important tomato variety of 20th century.  

Unfortunately San Marzano - as well as other varieties of tomatoes - is one of the favorite host plants for Cotton bollworm (Helicoverpa armigera). This pest is not really picky and its caterpillars can feed on different host plants which makes it one of the most economically important pest worldwide with estimated damage of around $5 billion annually. To make things even more complicated, it is a great traveler and can travel several hundreds of kilometers using high altitude winds. Monitoring and acting against this pest is thus quite a challenge.

Here is where a network of automated pest monitoring traps comes into play. Knowing what is happening with pest population in real time is crucial. Knowing what will happen in next few days completely changes decision making progress. This is not about collecting only weather data and using that data in more or less adopted biological models. It is about automatically collecting pest data with relevant weather data and using artificial intelligence to forecast pest development way more accurate and location specific than what has been possible so far. In order to achieve that, high quality and high resolution data is needed. 

That's why at Trapview we are setting up networks of fully automated traps that include high efficiency catching (funnel trap) combined with self-cleaning mechanism to minimize maintenance needs. That's why the lures are standardized to have reliable and comparable catches. And that's why every device collects also relevant weather data. 

Of course all above is combined with proved Trapview platform, where the "magic" of intelligent processing of all this data is done. While "Magic" of artificial intelligence is often just a combination of buzzword and wishful thinking, in Trapview can be very concrete - like identifying targeted pest from the pictures with better accuracy than human.

There is so much knowledge hidden in the data. Utilizing machine learning helps us unlock this knowledge and deliver a simple, yet so powerful outcome - accurately telling you what will happen in the next few days. 

Matej Štefančič