Artificial intelligence

Trapview: Can an AI-powered insect trap solve a $220 billion pest problem?

CNN Business

Pests destroy up to 40% of global crops each year, causing $220 billion in economic losses, according to the Food and Agriculture Organization of the United Nations (FAO). Trapview harnesses the power of AI to help solve the problem.

The Slovenian company has developed a device that traps and identifies pests, and acts as an early warning system by predicting how they will spread.

“We have built the largest database of insect images in the world, which allows us to make the most optimal use of modern AI-based computer vision,” says Matej Štefančič, CEO of Trapview and the parent company EFOS.

As climate change drives the spread of species and disrupts the migration patterns of highly destructive pests, such as locustsŠtefančič hopes to help farmers save their crops through faster and smarter interventions.

Trapview’s devices use pheromones to attract pests, which are photographed by a camera inside. The AI ​​crosses the images with the Trapview database and is able to identify more than 60 species, such as the codling moth, which afflicts apples, and the cotton bollworm, which can damage the lettuce and tomatoes. Once identified, the system integrates location and weather data, maps the insect’s likely impact and sends the results to farmers via an app.

Depending on the terrain and the value of the crop, a single trap can cover an area from a few hectares to more than 100, according to Štefančič. The devices come in different shapes and sizes, with the system being adapted to crops and landscapes. Štefančič says that a single insect can sometimes be alarming. In other cases, hundreds of insects can be caught without cause for concern.

Trapview’s app is also able to calculate where and when to best use pesticides. Štefančič says Trapview can significantly reduce the use of chemical sprays and the need for farmers to visit their fields. By reducing the emissions generated by farmers who go to their fields and those associated with the production and transport of pesticides, the technology can also help the climate, he argues.

Trapview is one of many automated pest detection systems.

“Any agriculture and AI technology that can help meet the challenges of the global food crisis is a good thing,” says Steve Edgington, biopesticides team leader at the Center for Agriculture and Bioscience International, an intergovernmental nonprofit organization.

About 2 million tons of pesticides are used each year, says Edgington.

“Reducing the amount of pesticides used on farmland is very important if we are to produce food sustainably and in the face of the challenges of pests and diseases and climate change,” he adds.

Trapview currently employs 50 people and received a $10 million investment in September. It’s not the only one using AI to fight pests. Pessl Instruments has developed iScouta solar-powered insect trap and camera identification system, while FarmSense flight sensor listens for pests and uses AI to identify them via the sound of their flapping wings.

According to Buyung Hadi, agricultural officer at the FAO, solutions like Trapview’s represent a change from conventional pest control, which is generally based on reactive rather than proactive approaches.

“Predictive technologies can facilitate the transition to more sustainable crop protection if combined with safe and sustainable solutions, such as biological control,” says Hadi, while warning that the quality of data from these technologies is essential. .

“You have to be very careful in formulating messages and recommendations from predictive technologies so that they don’t create panic among farmers, which could trigger the very indiscriminate use of pesticides that we would like to avoid in the first place” , he adds. .

Trapview says it has sold more than 7,500 devices in more than 50 countries since its launch in 2012. It has focused on Italy, France, Spain, the United States and Brazil, targeting such varied cultures as grapes, tomatoes, olives, fruit trees, crucifers. , cotton and sugar cane.

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