The newest trends in AI pet tech


Slowly but surely, artificial intelligence (AI) is making its way into pet technology to improve both safety and quality of life for cats and dogs.

In recent years, technological advances have touched nearly every human industry. Now the pet industry is starting to benefit, with this science at the heart of new technologies designed to boost the safety and quality of life for companion animals worldwide.

The enabling algorithm

AI’s implementation can be covert (the matching algorithm finding suitable dog sitters in the area, say) or overt – like cat flaps that use computer vision to identify the animal trying to enter the house. The more ambitious implementations could genuinely transform the industry, as well as the lives of pets entrusted to algorithmic assistance.

One of the most exciting frontiers in pet AI is the world of noseprint recognition. In South Korea alone, there are 2 firms working towards this: Petnow, an innovation award winner at the 2022 CES tech trade show organized by the Consumer Technology Association, and iSciLab, a company that made its name with its highly accurate human iris recognition.

Non-invasive tracking

Like a human’s fingerprints, a dog’s noseprint is unique and permanently fixed from around the age of 6 months, making it a potentially transformational way of reuniting missing animals with their owners.

Obviously, microchips have already performed this function for decades, but as Peter Jung, Business Development Manager at Petnow explains, uptake isn’t mandated in every country. Noseprint recognition is an inexpensive and non-invasive way of getting the same positive outcome, using nothing more than the phone in your pocket.

“Noseprints are just with them, and they cannot be damaged or lost like tags or microchips,” Jung says, noting that criminals sometimes remove microchips to resell stolen animals without being caught.

With anyone able to identify a registered animal using just a smartphone camera and the app, he sees this as a way of lowering pet insurance premiums, and moving towards the ultimate goal: a world without lost, abandoned or stolen pets.

Nose recognition – the pros and cons

iSciLab’s ambition is similar, and the company plans to commercialize both in Korea and abroad. “Having attained 99.99% matching accuracy for dogs, we are also seeking to progress our technology to cover cats as well as cattle in the near future,” says the company’s Chief Operating Officer, Meenho Sheen.

Petnow is also working on enabling cat nose recognition this year – a tougher proposition due to the smaller size and relative shallowness to a dog’s, explains Jung.

Though exciting, there are 2 possible drawbacks to noseprint recognition replacing the traditional microchip. The first is that getting a dog to stand still enough to scan a noseprint isn’t always straightforward – especially if it’s a stray that doesn’t trust you. The second drawback is also of a practical nature: to be effective, a noseprint database needs a critical mass of people to register and use the app.

The medical approach

Other players are looking at the medical potential of AI. Dogiz, a British canine health-tracking app, has a feature called Dr. Poop that will analyze the pet’s stools for medical red flags that could require vet attention. Korean TTcare, meanwhile, uses this science to look for pet conditions visible via an ocular or skin analysis.

“The AI has been trained with over 2 million pet image data samples with more than 90% accuracy as professional veterinarians continue to label and verify the signs on photos,” explains a spokesperson for AI For Pet, the company behind TTcare.

The company’s data shows that just over 47% of the dog-eye photos analyzed by the app have shown signs of abnormalities, with skin issues coming in second (42%).

While the AI’s training data is sourced from shelters, pet cafes and vets, much of the data samples come from the users themselves. That’s the beauty of AI: as it acquires more data via regular users, its effectiveness grows.

Indeed, initially, the app could only detect 4 irregularities in dogs’ eyes. Already that number has risen to 11, thanks to an ever-growing data set. TTcare plans to expand not only the number of abnormalities but also the areas that can be checked, such as joints and teeth.

A niche segment with potential?

Within the consumer pet market, AI is still very much in its infancy, and as such, getting market projections on it is tricky – in part because AI can be anything from the unique selling point (USP) of a product, to a background feature underpinning something else.

According to Kim Bill, Head of Purina’s Accelerator Lab, around a third of the hopeful start-ups vying for the company’s support use AI in some capacity. These include “a couple of applications with nose recognition,” she says.

Other examples include everything from computer vision programs to analyze pets’ body language, to Internet of things (IoT) devices tracking behavior. Indeed, Purina has its own take on the latter: a connected litter box that can keep an eye on cats’ behavior for early warnings of ailments from Urinary Tract Infection (UTI) to hyperthyroidism.

The limitations of technology

Generally upbeat about AI’s place in the pet market, Bill remains somewhat concerned about misdiagnoses made by medical tech. An AI-enabled IoT pet collar might report a dog with a dangerously high fever, when it really just sat near a radiator, for example. Worse, such tech could lull owners into a false sense of security if something is wrong that AI can’t yet detect.

But she still believes there’s a market for quality products that can help humans understand their animals’ needs. Just as long as AI doesn’t stand in the way of the essential emotional connection between pet and owner.

“I think if it’s used to replace that bonding element between pet owner and pet, then you know, it probably would not have such a high uptake,” she concludes.

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