Artificial intelligence in the pet industry

Artificial intelligence and robotics have the potential to revolutionize the entire pet industry, from food processing to medical care and disease prevention.

Let's delve a little deeper into manufacturing and preventive medicine, two of the sectors with the greatest implementation of AI today.

AI in food production

Automation, artificial intelligence, and robotics are becoming increasingly important in food and beverage processing, both for humans and pets. While the ultimate goal is not to incorporate AI in certain stages of the process, but rather to systematically and comprehensively integrate it into all production operations, advances and testing logically vary by sector:

Quality control

Palletizing robots have long been used in the palletizing industry. AI is breaking into these operations, providing the ability to improve quality inspections. For example, a palletizing robot with a vision system makes it possible to better detect defective or poor-quality food batches, allowing the process to be stopped before completion, thus saving time, costs, and effort.

When it comes to quality control, any type of product classification is complex and necessary. Typically, a person would perform these inspections, but now we have vision systems that can detect anomalies and take action by removing defective products or helping the employees in charge of this task make better decisions.

Predictive disease models

The pet care industry is moving toward a prediction: instead of addressing diseases once they appear, there is a growing focus on extending pet health and preventing health problems.

Today, we can collect a wealth of data on pets, from veterinary medical records, diets, daily activity, and even genetic makeup. Within this data lie patterns that, when connected, will help us better understand animals' behavior and responses to certain stimuli.

Artificial intelligence allows us to cross-reference and review these patterns efficiently and effectively. In a way, it unlocks the latent power of data from one pet and millions of other pets.

The implementation of AI seeks not only to understand how a pet's genetics and behavior can reveal powerful information about its overall health, but also to understand the collective construct: by combining patterns, behaviors, and analysis, we will find new ways to help animals developing a problem or disease.

Use cases

In the case of dogs that scratch, for example, we can use AI to detect movement patterns in dogs diagnosed with a skin condition and detect in advance when they will start scratching more frequently by monitoring their activity with a sensor on their collar.

The same technology can also be used to detect when a dog begins to develop joint problems such as osteoarthritis. AI can be used to detect subtle variations in gait with activity trackers, to identify possible arthritis preemptively or earlier in the disease's development.

In the case of obesity, we face the challenge that veterinary examinations and inspections are not performed uniformly: sometimes they are recorded as notes, sometimes as a body condition score, etc. This makes it difficult to obtain an adequate set of standards for pet weight and body condition scoring in a large sample.

To address this, Mars Petcare developed a natural language processing (NLP) algorithm for veterinary hospitals that would efficiently extract this information. The model has helped detect 30% more cases of obese pets and identify a specific problem with overweight and obesity in cats. This allows veterinarians, in a subsequent step, to explore treatment pathways after diagnosis, assessing which interventions were most successful and making the best decision for each particular case.

Because many diseases have better outcomes if detected and treated earlier, predictive models have the potential to be transformative for veterinary care. However, the goal goes beyond prevention: if we can even treat diseases early or halt part of their progression, we are already gaining more lifespan.

Wearable Pet Devices and AI Innovation

We're already seeing an explosion of AI tools in the pet industry, and this will continue in the coming years: it's the new generation of wearable devices, now for pets, that use AI to interpret data.

A clear demonstration of evolution and innovation is activity trackers. These are no longer limited to tracking the number of steps a pet has taken; today they seek to identify behaviors and patterns that may impact health. For example, monitoring animals' scratching and licking can help owners and veterinarians assess whether there is an underlying cause when these behaviors increase or change.

In 2022, it's difficult and even illogical to think that a growing industry like the pet industry won't be transformed by artificial intelligence. In our case, we'll see increasing improvements and implementation in veterinary care, diagnostics, and pet food production.

It's clear that we're moving toward a reality where AI puts the focus on what belongs there: food manufacturers, pet owners, and veterinarians at the service of artificial intelligence to care for and improve the quality of life of all pets.

Ultimately, anything that involves improving their nutrition and care means working toward a longer, happier, and healthier life.

Source: All Pet Food