Olympic and World Medalist Thomas Lurz Joined Swimming Analytics Startup, SwiMMinD

Thomas Lurz retired from swimming with an array of Olympic and World Championship medals to concentrate on working as a sports ambassador. Recently he joined the Video Analysis Startup, SwiMMinD because according to him “SwiMMinD focuses on beginner swimmers. With SwiMMinD, novice swimmers will get more feedback, including awards which will inspire them to swim more and swim according to well established coaching standards. While kids receive more feedback, they will be able to progress much faster.

SwiMMinD focuses on the beginner swimmers because nowadays people’s lives are intertwined with digital media and it is difficult to define how long people should be in front of a computer or mobile phone screen. Childhood obesity and diabetes continue to grow in alarming rates. Research reveals that children consume between 3 to 6 hours of media in a typical day. Because of that, children tend to avoid exercising.

In this respect, SwiMMinD promises to connect the digital world with the world of swimming. It focuses on the beginner swimmers and shall help them achieve their goals and empower their full aquatic potential. In other words, SwiMMinD aims to populate the swimming pools because it promises to help millions of people learn to swim or race globally in an easy, fun way!

The idea to have children to swim more via mobile application is AMAZING! Parents will be enabled to check with their mobile phones the progress of their kids.SwiMMinD will award their kids and allow them to compete globally.” Perfect symbiosis between digital and active life!

Another reason why SwiMMinD focuses on beginner swimmers is because traditional video analysis companies focus on elite level swimmer. Those companies provide video analysis tools that are very time-consuming. In other words, it is difficult for coaches to provide video analysis to all their swimmers because it takes hours to make the analysis with their drawing tools. In this respect, SwiMMinD thinks that faster analysis is much better. Therefore, SwiMMinD aims to develop AUTOMATIC AI video analysis to beginner swimmers.

In summary, SwiMMinD shall automatically deliver meaningful FEEDBACK and interactive digital AWARDS to beginner swimmers interested to build confidence in the water and shall provide them with video based competitions to RACE with swimmers around the world.  To this point, Lurz stated that “SwiMMinD will also allow swimmers to compete around the world without leaving their local pool. Can you imagine the smile of a kid from Würzburg who could compete with a kid from New York without leaving their local pools?”

Short after his retirement Thomas Lurz stated that “It is not easy to quit something in which one was the best in the world.” Thus, his mission became to support young people on how to be successful in life. He published a book titled “Auf der Erfoldswelle schwimmen” or “Float on the Wave of Success.” Now he supports the startup SwiMMinD because it also focuses on young people, on the grassroots of swimming, on beginner swimmers.

Thomas Lurz’s philosophy “Never give up” was adopted by the SwiMMinD ’s team which is comprised of highly skilled and experienced professionals ranging from AI Experts, Educators, Developers, Project Managers, Olympic Champions, World Record Holders and Learn to Swim Experts. There is no other competitor in the video analysis sector that has this unique combination of focused expertise and experience. This diverse and competent team dared to explore the problems in the video analysis.

To make the video analysis automatic, SwiMMinD’s team shall evaluate swimming videos by using machine learning algorithms to calculate whether a swimming skill was executed properly and whether and how fast a swimmer swam an event. This will augment coaches tremendously and will bring more joy to swimmers and parents.

The technology behind SwiMMinD is Borislav Popov(Bobi), who was a Head of Semantic Analytics at Ontotext where he built a team that developed a Dynamic Semantic Publishing platform used by leading media, scientific and financial institutions in Europe and the US. Bobi specialized in Natural Language Processing and his primary interests are the possibilities appearing from automatically linking unstructured information with semantically modeled structured data, as well as the resulting multi-paradigm indices and higher order analytics. He brought other AI experts to SwiMMinD whose primary R&D interests is in neural nets and deep learning. In summary, the AI Team of SwiMMinD has a head start because its members are behind the innovations in the proprietary machine learning libraries and personalized engine of Ontotext and are behind the applied AI solutions for Euromoney, BBC, FT, IET, S&P Global and others.

After over 15 years of working on how to make it easier for broadcasting corporations such as BBC to discuss sport events, it is time for me to get involved in the noble cause to make children more sports oriented … more active …get excitement from both the digital and the sports world” To achieve this, Bobi stated that SwiMMinD shall distinguish body parts and movements by accurately compiling images from videos. The event stream processing shall enable real-time image recognition using deep learning models. Bobi concluded that “By combining our deep learning models, we could train our models in memory in the cloud.

As a consequence of all of the above, in January 2018 SwiMMinD won “Most Business Value” Smarter Award from the International Olympic Committee and Alibaba Cloud.

Later SwiMMinD was exhibited at the 2018 Olympic Games in Pyeongchang, South Korea.

The next step is to raise funds from the crowd-sourcing platform Indiegogo.com. To stay tuned on SwiMMinD’s development or how or when to support SwiMMinD on Indiegogo.com follow and/or like SwiMMinD on its Facebook PAGE.

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