Race Data AI Su'esu'ega Fa'akomepiuta Mo Tagata Ta'alo Ta'avale e Cansu Cetin

O le mamanu Race Data AI Su'esu'ega Fa'akomepiuta Mo Tagata Ta'alo Ta'avale e Cansu Cetin o se manumalo maualuga tele o le fa'ailoga mamalu 2025 A' Design Award Uʻamea i le Vaega Tauva Mamanu Fa'asavali.

UʻameaFa'asavali· 2025

Race Data AI Su'esu'ega Fa'akomepiuta Mo Tagata Ta'alo Ta'avale

na mamanuina e Cansu Cetin

Tagata Fa'atau: Driven AVS

Manumalo o le A' Design Award Uʻamea i le Vaega Fa'asavali

12,994

Manumalo Fa'ailoga Fa'amaonia

Fa'amaonia le Tulaga o le Fa'ailoga mo #167411

Asiasi i le Saite Va'ai i le A' Design Award Fa'asalalauga Pailesi o le Fa'ailoga

Lanu

Le Mamanu

E Uiga ia Race Data AI Su'esu'ega Fa'akomepiuta Mo Tagata Ta'alo Ta'avale

O lenei poloketi ua toe fa'atulagaina ai su'esu'ega o ta'aloga ta'avale fa'akomepiuta e ala i le fatuina o se meafaigaluega telemetry e faigofie ona fa'aogaina, e feso'ota'i ai le lalolagi fa'akomepiuta ma ta'aloga ta'avale moni. E fa'afaigofie fa'amaumauga lavelave e ala i fa'afanua ta'aloga fegalegaleai, laulau fa'atulagaina e tusa ai ma mana'oga, ma fa'atusatusaga o ta'amilosaga. Na atia'eina e ala i manatu fa'asolosolo mai tagata ta'alo ta'avale fa'akomepiuta, o le mamanu e ofoina atu ai malamalama aoga ae fa'amanino e fa'aleleia ai le fa'atinoga. E tu'ufa'atasia le fouga fou ma le faigofie ona fa'aogaina, ma e fa'amalosia ai tagata ta'alo e fa'aauau pea ona fa'aleleia ma malamalama lelei atili i a latou fa'amaumauga ta'aloga.

Le Fa'ailogaina

E Uiga i le A' Design Award Uʻamea

O le A' Design Award Uʻamea na manumalo ai Race Data AI Su'esu'ega Fa'akomepiuta Mo Tagata Ta'alo Ta'avale, o se faamaoniga mamalu e tuuina atu i mamanu lelei e faataunuu ai manaʻoga faapolofesa ma pisinisi e faamoemoeina mai galuega ua mamanuina lelei. O ē manumalo i le Uʻamea e faaalia ai le tomai tele, le faapitoa maualuga, le malamalama o tagata poto ma le mafai fatufatuaʻi o ē na faia. E faamoemoeina Race Data AI Su'esu'ega Fa'akomepiuta Mo Tagata Ta'alo Ta'avale e avea ma mea ua matuā vivii, mataʻina ma pelepelea e aogā ma fou. O lenei mamanu na manumalo i le A' Design Award Uʻamea e tuufaatasia ai faiga sili o le pisinisi ma e iai uiga faatekonolosi mafai ua fesoʻotaʻi ma le poto ma le taleni. Ona o lona faatuatuaina, e tatau ai Race Data AI Su'esu'ega Fa'akomepiuta Mo Tagata Ta'alo Ta'avale ona faaaloalogia ma ua mamanuina e tuuina mai ai faaleleiga o le olaga e fesoasoani e faia ai e le lalolagi se nofoaga e sili atu ona lelei.

I Tua o le Mamanu

Pepa Fa'asalalau

Fa'amaoniaga, sui o le 'au ma fa'amatalaga fa'atekinisi na saunia e le tagata mamanu.

Uiga Fa'apitoa: This design transforms sim racing analysis with intuitive data visualization and advanced telemetry tools, providing racers with actionable insights. Its user-focused approach ensures accessibility while maintaining technical depth, featuring interactive track maps, customizable dashboards, and seamless lap comparisons. Personalized analysis tools and community-driven feedback make it a standout solution for improving performance and bridging the gap between virtual and real racing.
Fua & Fa'apipi'i: The design was developed with a focus on responsiveness, ensuring compatibility across various screen sizes. The layout adapts seamlessly from 1024x768px to 1792x1024px for larger displays. Interactive elements were optimized for touch and mouse input, with clickable areas sized for ease of use across devices. Data visualization tools were engineered for high performance, processing telemetry data in real-time with minimal latency, ensuring smooth user experience even with large datasets.
Fa'ailoga: Telemetry analysis, real-time data processing, racing insights, sim racer tools, user experience design, user-centric design,
Tekonolosi Gaosiga: The design was developed using an iterative UX/UI process, emphasizing user feedback from sim racers. Wireframes and prototypes were created to test and refine key functionalities, such as telemetry data visualization and lap comparisons. Agile methodology was employed to allow for continuous improvement based on user testing. A modular design approach ensured flexibility, while data-driven insights guided the creation of interactive features that prioritize performance optimization and ease of use.
Lu'itau o le Mamanu: The hardest part of this design was simplifying complex telemetry data without losing essential details. The challenge lay in balancing technical depth with user accessibility, as racers needed both detailed insights and easy navigation. Historical perspectives of traditional racing tools influenced the design, but new technology offered opportunities to innovate. External factors, such as varying levels of user expertise and limited research on specific racing behaviors, also presented obstacles, requiring extensive user feedback to refine the product.
Su'esu'ega: The research combined qualitative and user-centered studies to understand sim racers' needs and behaviors. The goal was to simplify telemetry data presentation to enhance performance. Insights were gathered through interviews, surveys, and online community observations, involving both casual and competitive sim racers. Results revealed a preference for simplified, interactive interfaces, informing a design that improves performance and user experience in virtual and real-world racing.
Fa'aosofia: The project was inspired by the challenges sim racers face in translating virtual performance to real-world racing. Recognizing the complexity of existing telemetry tools, the goal was to simplify data analysis while enhancing usability. Drawing from user interviews, market research, and technical studies, the design combines intuitive features with a user-centered approach to help racers optimize performance and make the most of limited practice time.
Umi o le Poloketi: The project started in May 2024 in Turkey and finished in December 2024 in Canada.
Fa'agasologa o Galuega: This design helps sim racers improve their performance by providing easy-to-understand data about their racing. Users can view their racing line, speed, and other key information to see where they can improve. By comparing laps, racers can find areas to optimize, such as braking and acceleration points. The design allows for simple interactions like clicking on turns to get more detailed feedback, making it easier to focus on key areas for improvement and achieve better results over time.