Fitness tracking is one of the most popular provisions on all app stores and even physical smart devices.
Being able to track your calories and nutrition can help no matter the kind of diet or workout regimen you follow, and it also takes some of the guesswork out of planning each daily adjustment. If an app can help see the exact ingredient specification of a product you scan, you may be able to avoid certain nutrients or even allergies.
As many of the most popular fitness trackers have built robust products over time, they’ve been somewhat reticent about stuffing in AI features for the sake of it. That’s of course a healthy principle – sometimes less is more in product design and adding provisions without clear intention is usually a bad idea.
In this post, we hope to offer new innovative developers a chance to think about the various utilities fitness tracking apps could integrate thanks to AI, and what principles to think through as you do it:
Health Habit Trends
AI has the potential to better showcase trends in daily life that most people wouldn’t notice on their own.
It might show how workouts drift later into the evening as the week goes on, or that when people eat more spinach, they tend to stick below their caloric target that day. Brought forward in a gentle way, those patterns can give someone a clearer picture of what’s really happening behind their routine.
If you frame it right, you an also make such insights feel supportive, taking the persona of a coach quietly pointing something out, and not a system wagging its finger, which some cold number systems can unfortunately come across as. It’s much more encouraging to have something of a new insight each week, they can decide for themselves what that means in emotive terms.
Better Scanning & Image Rendering
Most of us log food through the camera or its barcode scanner now, as a photo of a meal gets logged faster than typing everything out, and the numbers are more accurate or can be edited nutritionally.
AI can recognize what’s on the plate and how much of it there is, which helps with getting the calorie count closer to what’s real.
If implemented well, this scanning tech can handle ingredient lists on packaging too, pulling out nutritional data but without the need to squint at tiny print. Being able to use SIFT algorithm through labels and get a clean breakdown will allow for better image rendering, and that way the app can suggest similar foods if something isn’t in the database yet, learning what shows up in someone’s diet and making the process feel more natura for them.
Privacy Tools
Health data is at the heart of what makes someone vulnerable because no one wants our weight or fitness performance public on our profile.
Fitness apps hold plenty of that information and so it’s important to be mindful of its management. AI can help by processing data locally on the device, meaning sensitive information doesn’t have to leave someone’s phone to get useful insights, and that creates a better safety standard and how safe people feel using these tools.
We’d suggest you empower your customers, letting users control what gets stored, how long it stays, and who can see it. It’s a sign of respect and your customers will no doubt notice it.
With this advice, we believe your AI will improve your fitness tracking app.