Race Data AI Teilimeatraidh airson Rèisearaich Simulatair le Cansu Cetin

Tha Race Data AI Teilimeatraidh airson Rèisearaich Simulatair le Cansu Cetin na bhuannaiche air leth urramach anns an fharpais chliùitich 2025 Duais Iarainn A' Design Award ann an Roinn Farpais Dealbhadh Eadar-aghaidh, Eadar-obrachaidh agus Eòlas Cleachdaiche.

IarannEadar-aghaidh· 2025

Race Data AI Teilimeatraidh airson Rèisearaich Simulatair

le Cansu Cetin

Neach-ceannach: Driven AVS

Buannaiche Duais Iarainn A' Design Award ann an Roinn Eadar-aghaidh

13,338

Buannaiche Duais Dearbhaichte

Dearbhaich Inbhe na Duaise airson #167411

Tadhail air an Làrach Seall aig A' Design Award Brath Naidheachd Suaicheantas Duaise

Dathan

An Dealbhadh

Mu dheidhinn Race Data AI Teilimeatraidh airson Rèisearaich Simulatair

Tha am pròiseact seo ag ath-mhìneachadh anailis rèiseadh simulatair le bhith a' cruthachadh inneal teilimeatraidh a tha furasta a chleachdadh agus a tha a' ceangal rèiseadh bhiortual ris an fhìor-shaoghal. Tha e a' sìmpleachadh dàta iom-fhillte le mapaichean rèis eadar-ghnìomhach, deas-bhùird sho-ghnàthaichte, agus coimeasaidhean cuairt. Air a leasachadh le beachdan ath-chuairteach bho rèisearaich simulatair, tha an dealbhadh a' toirt seachad sealladhan so-ruigsinneach ach mionaideach gus an coileanadh a leasachadh. A' cothlamadh ùr-ghnàthachadh agus so-chleachdachd, tha e a' toirt cumhachd do rèisearaich piseach leantainneach a dhèanamh agus tuigse nas fheàrr fhaighinn air an dàta rèisidh aca.

An Aithneachadh

Mu dheidhinn Duais Iarainn A' Design Award

Tha Race Data AI Teilimeatraidh airson Rèisearaich Simulatair air Duais Iarainn A' Design Award a bhuannachadh, aithneachadh urramach a bheirear do dhealbhaidhean math a choinnicheas ris na riatanasan proifeiseanta is gnìomhachais a thathar a' sùileachadh bho chruthachaidhean a chaidh an dealbhadh gu math. Tha buannaichean Iarainn a' nochdadh sgil mhòr, speisealachadh àrd, tuigse eòlaiche agus comas cruthachail an luchd-cruthachaidh. Thathar an dùil gum bi Race Data AI Teilimeatraidh airson Rèisearaich Simulatair na chruthachadh air a bheil mòran meas, ion-mholta agus gràdhach a tha practaigeach agus ùr-ghnàthach. Tha an dealbhadh seo a bhuannaich Duais Iarainn A' Design Award a' cur nan cleachdaidhean as fheàrr sa ghnìomhachas còmhla agus tha feartan teignigeach comasach aige ceangailte ri eòlas-dèanamh agus tàlant. Tha meas air Race Data AI Teilimeatraidh airson Rèisearaich Simulatair airson a dhùrachd agus chaidh a dhealbhadh gus leasachaidhean càileachd beatha a thoirt seachad a chuidicheas le bhith a' dèanamh an t-saoghail na àite nas fheàrr.

Air Cùl an Dealbhaidh

Pasgan Naidheachd

Creideasan, buill sgioba agus fiosrachadh teicnigeach a chuir an dealbhaiche ri chèile.

Feartan Sònraichte: 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.
Tomhasan & Pacadh: 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.
Tagaichean: Telemetry analysis, real-time data processing, racing insights, sim racer tools, user experience design, user-centric design,
Teicneòlas Cinneasachaidh: 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.
Dùbhlan Dealbhaidh: 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.
Rannsachadh: 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.
Brosnachadh: 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.
Faid a' Phròiseict: The project started in May 2024 in Turkey and finished in December 2024 in Canada.
Sruth Obrachaidh: 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.