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H2020Докторантска мрежа2019–2023

RAIS · Real-time Analytics for the Internet of Sports

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период
2019-01-01 → 2023-06-30
Финансиране от ЕС
3 612 495 €
Участници
12
Схема
MSCA-ITN

Линиите свързват координатора с партньорите.

Накратко на български

Децентрализираният анализ на големи данни в спорта проучва как информация от носими устройства да се обработва локално, вместо в централни облачни сървъри. Това помага за намаляване на разходите за инфраструктура и подобрява защитата на личните данни на потребителите.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

RAIS: Real-time Analytics for the Internet of Sports

New emerging sensing technologies of the Internet of Things (IoT) in our global interconnected world present us with unprecedented amounts of data, available at highly heterogeneous and distributed data sources. IoT is a greenfield market. New players, with new business models, approaches, and solutions, appear and overtake incumbents. Existing IoT solutions are expensive because of the high infrastructure and maintenance costs associated with centralized clouds, large server farms and networking equipment. The sheer amount of communication that will have to be handled when IoT devices grow to tens of billions will increase those costs substantially. Even if the unprecedented economical and engineering challenges are overcome, cloud servers will remain a bottleneck and point of failure that can disrupt the entire network. This makes Privacy-Preserving Decentralized Big Data Analytics a main challenge for the success of future IoT initiatives that capitalize on mining data coming from personal devices by uncovering the collective behaviour and latent phenomenon arising in such systems. The main objectives of the RAIS project were to lay the groundwork and develop essential key technologies for such Privacy-Preserving Decentralized Big Data Analytics in future large-scale distributed IoT systems, as well as provide comprehensive training to a new generation of 14 early-stage researchers (ESRs) in key technical subjects of Big Data Analytics on the Edge, Data Stream Processing, Distributed & Decentralized Machine Learning, and Security & Privacy. The project specifically focused on the Internet of Sports (IoS) as an application domain heavily impacted by IoT. The project successfully reached all the targeted research and ESR training objectives.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

Over the past few years, we have been witnessing an increasing presence and usage of wearable sensing and quantified- self devices. The rise of embedded and wearable computing is expected to bring the next revolution of the Internet of Sports, enhancing fitness, performance health, productivity and safety as well as creating new jobs and opening new markets. Nevertheless, at a European level, there is a recognized shortage of highly skilled researchers, scientists and engineers with transferable skills and entrepreneurial experience, trained in building IT platforms and service infrastructures capable of hosting innovative collective sensing services and applications. The RAIS consortium comprising 6 beneficiaries and 7 fully committed partner organizations, aspires to establish the core for a fertile multidisciplinary research and innovation community with strong entrepreneurial culture that will advance:1) wearable sport-sensing and quantified-self devices and accompanying middleware;2) technologies of Big Data mining and analytics that are needed to capture a broad range of users’ sports- and wellness-related information.The main objective of RAIS is to provide world class training for a next generation of researchers, computer scientists, and data engineers, emphasizing a strong combination of advanced understanding in both theoretical and experimental approaches, methodologies and tools that are required to develop decentralized, scalable, and secure collective sensing infrastructures and platforms. RAIS training network will fund 14 ESRs, 3 workshops, 1 Hackathlon event, 1 entrepreneurship event, 3 summer schools and a final Conference. To meet this goal, RAIS will focus on developing new technologies on Big Data Analytics on the Edge, Data Stream Processing, Distributed and Decentralized Machine Learning, Blockchain as well as Security/Privacy. These topics include important and timely research challenges with an immediate exploitation potential.

Оригинален текст от CORDIS (на английски).

Участници

Връзки

Данни: CORDIS, © Европейски съюз