New App Digitalizes Hunting Process – Labs of Latvia

Latvian business aQode has developed Huntgate, a mobile app for digitalising the hunting process. It gives hunters the chance to collect and structure information from video cameras monitoring the movements of forest animals.

Over the past few years, hunters worldwide have widely used these kinds of cameras to identify animal trails and determine movement times. Although hunters now have a large volume of photos and videos available, there has been nothing convenient to help them systematise and analyse their data until now. The app can be linked to the most popular camera models.

“The idea for this app came about when I was studying and working in Michigan, U.S., where one in two inhabitants are hunters. In the U.S., I saw how tens of thousands of cameras were placed in the forest, but without a convenient tool to structure the obtained data and understand what animal is located where at exactly what time,” explains Staņislavs Vaišļa, aQode Chairman of the Board.

Huntgate’s developers have already received positive feedback from hunters in the U.S., Australia, Canada, Brazil and elsewhere. “In our beginning phase, we particularly appreciated the responses from Latvian hunters, which gives us the chance to gain fast feedback and help to develop the app’s functionality. For example, currently the user categorises the forest animals, but we hope that artificial intelligence will play a much larger role in the future and be able to differentiate a deer from an elk, or a hare from a fox,” he says.

One of Huntgate’s popular functions is providing overall statistics, which can be used to analyse the weather, moon phases and other factors which could impact the movement of wild animals.

Registered trail camera users can share their images with others, for example, the members of their hunting collective, by entering their email address or phone number. Nominated users will gain access to shared camera images and will also be able to view the basing and additional statistics associated with an image.