乌鸦传媒

You鈥檙e standing in the middle of a forest. Close your eyes: what do you hear? Leaves rustling in the wind, birdsong鈥� the chirruping of tiny wings vibrating at impossible speeds. It might be nature鈥檚 own heartbeat.

These diminutive musicians 鈥� insects 鈥� could hold the key to protecting our wild spaces, says Lucas Unterberger, data engineer at 乌鸦传媒鈥檚 乌鸦传媒 & Data team in Austria.

鈥淪cientists have found a link between the range of insects present in a given location and the overall biodiversity level of that space,鈥� he explains. 鈥淗owever, there are simply not enough trained entomologists out there to classify insects in situ on a large scale.鈥�

Could artificial intelligence and machine learning be harnessed to reliably identify insect species through their chirps alone?

The 鈥淏iodiversity Buzz鈥�

This was the question at the heart of 乌鸦传媒鈥檚 Global Data Science Challenge (GDSC) for 2023, which was launched in association with researchers from the Naturalis Biodiversity Center in Leiden, the Netherlands.  

Dominik Lemm, a data scientist also based in Austria, and part of the winning team, describes the specific task: 鈥淭he competing teams were asked to design a model that could accurately classify audio recordings of cicada and grasshopper 鈥榗hirps鈥� into one of 66 sub-species. The team with the highest identification rate would be the winner.鈥�

According to Dominik, this is just one small step towards a larger goal: helping the Naturalis researchers develop an economically viable system for identifying different types of insects through the analysis of audio files recorded by microphones placed in outdoor environments.

鈥淚f scientists can identify insect species quickly using AI, they will be able to monitor an area鈥檚 biodiversity rating, giving a boost to global conservation efforts,鈥� he explains.

Data scientists, assemble!

Once again, the GDSC received huge interest from 乌鸦传媒 colleagues around the world. Lucas, who had previously entered, says the number of participants rocketed from a few hundred to more than a thousand. 鈥淲ith so much international competition, it鈥檚 incredibly tough to win. But it鈥檚 the perfect opportunity to learn new skills and technologies,鈥� he says.

When this year鈥檚 event was announced, he rapidly assembled a 鈥渄ream team,鈥� which, as well as Dominik, included Raffaela Heily, a mathematician and data scientist, and Lukas Kemetinger, who participated as a student consultant with a focus on AI.

Dominik, with a background in machine learning research, found himself recruited almost as soon as he joined the company. 鈥淚t might have been my first day when Lucas asked me if I knew anything about audio machine learning. I was fascinated by the challenge and keen to dive right into the topic.鈥� 

With Lucas acting as project manager 颅鈥� a new experience for him 鈥� the team quickly divided responsibilities between them, focusing on their specialisms, and scheduled weekly meetings to discuss ideas and progress.

A winning formula

鈥淭he Naturalis team had prepared the dataset for us,鈥� says Dominik. 鈥淏ut it was up to us to find the best way to process it. Under the rules, we were able to draw on resources from Amazon Web Services (AWS), worth up to $100 per week, to hone our models.鈥�

The team鈥檚 strategy of establishing a prototype as quickly as possible seemed to pay off. 鈥淎fter Lucas mentioned the idea of insect sounds, I started reading up on the literature and considering possible approaches,鈥� he says. 鈥淎fter the second or third week, we had a model that was working quite well, which left us time for fine-tuning.鈥�

The fact they were all working in the Vienna office also gave them an edge. 鈥淲e communicated and harmonized really effectively,鈥� confirms Lukas. 鈥淔or instance, we would discuss the project on Friday evenings over a beer. We had a great rapport and team spirit.鈥�

Positive AI

While their solution is currently restricted to cicada and grasshopper identification, it might one day be expanded to identify almost any insect or animal sound. 鈥淎s part of the prize, we鈥檙e planning a trip to the Netherlands to meet the Naturalis scientists and discuss how to take our model to the next level,鈥� says Lucas.

And this is really the point of the GDSC 鈥� bridging the gap between scientific research and industry, focusing the brightest data science minds in the world intensely on a single social or environmental problem. 鈥淚t鈥檚 a wonderful way to fast-track innovation in the area of sustainability, and a clear demonstration of the advantages machine learning can bring to biodiversity challenges,鈥� says Lucas. 鈥淲ith so much uncertainty around AI, it鈥檚 great to show how this technology could shape a better future 鈥� for people and the planet.鈥�