SKEO

A large group of beginners is not satisfied with their skiing lessons and up to even 70 or 80 percent of them quit at the early stages of their training. It means that for every 10 people who try out skiing, 7 or 8 will resign.

Both Bode and Martin were disappointed with the underappreciation of their favorite sport and saw an opportunity to change it. They wanted to create a free platform being a training solution for skiers on every stage of advancement. It was supposed to help them measure their performance, improve their skills, check each others’ statistics, and gain access to useful coaching tips, being highly accessible at the same time. Everyone would be able to download the app on their phone.

Additionally, there was going to be a possibility of upgrading the experience by using three wearable sensors – one on each ski and one on the chest.

Developed by Bode Miller is a scoring ranking with a baseline metric to evaluate the user’s performance based on
a personal survey and data acquired during actual skiing.

Allow users to track their individual speed, turns, pace, vertical, mileage, and G-force with every slide.

For successful development, quests are applied to the elements that need to be improved and are adjusted individually to the user’s abilities.

The app was integrated with a visual depiction of the skier’s position based on the gathered movement analysis and helping provide professional feedback.

It lets the users follow each other within the app depending on their location and personal privacy preferences. They can compare the results and challenge one another to boost their overall performance.

Developed by Bode Miller is a scoring ranking with a baseline metric to evaluate the user’s performance based on a personal survey and data acquired during actual skiing.

Swift allowed us to provide robust performance, seamless synchronization, and appealing design. The language is known for its speed and clean, safe code allowing us to create a spot-on product for iPhones.

Kotlin was our choice for Android. We used it for its concise code, safety, productivity, compatibility, and easy maintenance.

It provides an objective ranking system which is able to evaluate skiers on different levels of advancement – from first-timers to World Cup Racers. The app gathers data about users’ performance and technique and ranks them from 1 to 100. The evaluation changes along with the skier’s performance – after taking part in various quests and collecting points.

UAR consists of 3 elements – survey, initial assessment, and regular quests completion, as well as progression.

We developed dedicated sensors that can be connected to the SKEO app to provide better and more accurate analysis and UAR measurements. A very important aspect of this project was to keep modular, layered architecture, respecting the technology stack needed on each layer.

The project is built of modules written in native mobile languages to provide native access to low-level system interfaces. Application also integrates Unity modules and Algorithms written natively in C++.

The app supports customers using tablets which requires responsive app views behaviour. Depending on the device size, we automatically scale views to the specific screen size or, in special cases, rearrange view elements to make them more user friendly.

The graphic layer of SKEO was quite a challenge. Client requirements were to show as much data as possible while maintaining the greatest possible readability. Thanks to the white interface combined with snowy colors, we’re sure that we achieved that. We wanted to create something user-friendly, easy and as intuitive as possible. Thanks to the great cooperation of our teams, and the implementation of a 3D avatar within the app, we have created a truly unconventional product that will be perfect for skiers and other people associated with this group.

We started the testing process by recognizing the project’s specifications. Our team received sensors coworking with the mobile application, but because the client tested the equipment’s performance before, we focused on connectivity tests. We verified how the app behaves when it loses bluetooth connection with sensors and how they react in such a situation. Additionally, we needed to check the correctness of pairing the device with sensors and if the launched app connects automatically to the paired device when it’s activated.

Developers supported the QA team in simulating the product’s performance in real-life conditions which allowed verifying the mobile app’s behavior. The tests were performed on Android and iOS – we verified all the functionalities and current updates to newest versions.

The app is appreciated by users and experts – it gets positive opinions and reviews in both the world of technology and sports, providing skiers with thorough analysis of their efforts and helping them enhance their skills.