UI/UX Articles and Interesting Tidbits of the Week
November//4//2022
Here are some interesting finds on UI/UX of the week!
1.
TomTom’s Maps Platform. While this isn’t the typical newsletter highlight, since in essence it is a product release communication, it showcases the evolution TomTom as a technology company is going through, and just as importantly, their stance on sharing the innovation that they’re producing and delivering to market. It also stands as a testament to how this technology and overall feature is being used (and licensed) throughout the world. Well worth the read. Highlight of the article includes:
“Over the years, TomTom improved the PND to bring drivers more useful features, such as live traffic, hazard warnings and phone integration. In the mid-2000s, TomTom launched its MapShare Reporter, which crowdsourced more than 5 million map edits, to improve the detail of its map. Eventually the tech that powered the PND found its way into the dashboard of vehicles all over the world, and TomTom continued making maps and crunching location data. There are now more than 600 million vehicles, devices and apps around the world that include some of TomTom’s tech. But, beneath it all, the PND wasn’t just a device that helped drivers get to where they needed to go more easily, it was the thing that pushed TomTom to build better maps — to hone how it gathers and processes location data to make smart and useful maps.”
2.
Mobile Navigation. Another article from Vitaly Friedman published on Smashing Magazine, this time around focused on the topic of finessing Mobile Navigation. When it comes to interaction paradigms, it’s important to always consider the principles of that discipline, namely Discoverability/Signifiers/Feedback/Mental Models/Mappings/Constraints and Consistency/Familiarity. The author showcases quite a few examples of applications that showcase questionable navigation behaviors, while also presenting good alternatives for it and advocating for good practices while at it. The article also features quite a few resources worth reading through. Highlight of the article includes:
“In complex environments, navigation usually mirrors the way the organization is structured internally, and without that prior knowledge finding the right route to the right page is difficult at best. In that case, once a user is looking for something very specific, they seem to use search rather than traversing the navigation tree up and down. This becomes apparent especially when the contrast between levels isn’t obvious, such as on WHO, for example (pictured below).”
3.
Media Intelligence and Marketing Opportunities. Interesting article from author Shelby Britton on the topic of Rich Media, and how machine learning tools can tap into that vast repository of data and leverage it to better understand users, behaviors and patterns. This of course can in turn potentiate more opportunities for organizations to pitch all sorts of products and solutions. While it is indeed a self promotion article from Cloudinary, it still holds relevance for aspect of automation and AI integration that it suggests (and it’s always worth reading more about natural language processing for instance here). Highlight of the article includes:
“A semantic segmentation model creates a different mask for different object types within an image, cropped or not. In fact, in some cases, this model understands the object type better on the entire (uncropped) image, which has more context. Preprocessing by cropping can create a higher resolution with segmentation models. For the Nike example earlier, you can analyze with a segmentation model only the part of the image that contains the shoe. To facilitate that task, you could use a detection model like the Cloudinary one for human anatomy to discard the irrelevant portions of the image before processing the image-segmentation mask.”
