PMData: A sports logging dataset

Thambawita, Vajira; Hicks, Steven A.; Borgli, Hanna; Pettersen, Svein Arne; Stensland, Håkon Kvale; Jha, Debesh; Johansen, Dag; Johansen, Håvard D.; Kupka, Tomas; Grønli, Tor‐Morten; Fredriksen, Per Morten; Eg, Ragnhild; Hansen, Kjeld; Fagernes, Siri; Biørn-Hansen, Andreas; Dang-Nguyen, Duc-Tien; Hammer, Hugo Lewi; Jain, Ramesh; Riegler, Michael; Halvorsen, Pål

doi:10.31219/osf.io/k2apb

Cited by 18 publications

(21 citation statements)

References 13 publications

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“…Recently it has been possible to collect datasets, anonymize them and monitor a large population according to the General Data Protection Regulation (GDPR) [11]. This could be one of the promising solutions for identifying an individual with viral symptoms and monitoring large populations to address the challenges related to COVID-19 and other related future pandemics.…”

Section: Arxiv:220804704v1 [Cscy] 19 Jul 2022mentioning

confidence: 99%

COROID: A Crowdsourcing-based Companion Drones to Tackle Current and Future Pandemics

Rauniyar

Hagos

Jha

et al. 2022

2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM)

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Due to the current COVID-19 virus, which has already been declared a pandemic by the World Health Organization (WHO), we are witnessing the greatest pandemic of the decade. Millions of people are being infected, resulting in thousands of deaths every day across the globe. Even the world's best healthcare-providing countries could not handle the pandemic because of the strain of treating thousands of patients at a time. The count of infections and deaths is increasing at an alarming rate because of the spread of the virus. We believe that innovative technologies could help reduce pandemics to a certain extent until we find a definite solution from the medical field to handle and treat such pandemic situations. Technology innovation has the potential to introduce new technologies that could support people and society during these difficult times. Therefore, this paper proposes the idea of using drones as a companion to tackle current and future pandemics. Our COROID drone is based on the principle of crowdsourcing sensors data of the public's smart devices, which can correlate the reading of the infrared cameras equipped on COROID drones. To the best of our knowledge, this concept has yet to be investigated either as a concept or as a product. Therefore, we believe that the COROID drone is innovative and has a huge potential to tackle COVID-19 and future pandemics.

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Section: Arxiv:220804704v1 [Cscy] 19 Jul 2022mentioning

confidence: 99%

COROID: A Crowdsourcing-based Companion Drones to Tackle Current and Future Pandemics

Rauniyar

Hagos

Jha

et al. 2022

2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM)

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“…The dataset combines input from Fitbit Versa 2 smartwatch wristbands, the PMSys sports logging smartphone allocation, and Google forms. Refer to [9] for more details.…”

Section: Performance Evaluation a Data Sourcementioning

confidence: 99%

Service resource allocation problem in the IoT driven personalized healthcare information platform

Ji¹,

Lee²,

Wang³

2022

Preprint

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With real-time monitoring of the personalized healthcare condition, the IoT wearables collect the health data and transfer it to the healthcare information platform. The platform processes the data into healthcare recommendations and then delivers them to the users. The IoT structures in the personalized healthcare information service allows the users to engage in the loop in servitization more convenient in the COVID-19 pandemic. However, the uncertainty of the engagement behavior among the individual may result in inefficient of the service resource allocation. This paper seeks an efficient way to allocate the service resource by controlling the service capacity and pushing the service to the active users automatically. In this study, we propose a deep reinforcement learning method to solve the service resource allocation problem based on the proximal policy optimization (PPO) algorithm. Experimental results using the real world (open source) sport dataset reveal that our proposed proximal policy optimization adapts well to the users' changing behavior and with improved performance over fixed service resource policies.

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“…A mobile application with graphical visualization feedback provides the players with a timeline overview. The data collected via the PMSys system is also used in several follow up research that is focusing on players performance [8], [29]- [31].…”

Section: Individual Subjective Reports (Pmsys)mentioning

confidence: 99%

Video Analytics in Elite Soccer: A Distributed Computing Perspective

Jha¹,

Rauniyar²,

Johansen³

et al. 2022

Preprint

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Ubiquitous sensors and Internet of Things (IoT) technologies have revolutionized the sports industry, providing new methodologies for planning, effective coordination of training, and match analysis post game. New methods, including machine learning, image and video processing, have been developed for performance evaluation, allowing the analyst to track the performance of a player in real-time. Following FIFA's 2015 approval of electronics performance and tracking system during games, performance data of a single player or the entire team is allowed to be collected using GPS-based wearables. Data from practice sessions outside the sporting arena is being collected in greater numbers than ever before. Realizing the significance of data in professional soccer, this paper presents video analytics, examines recent state-of-the-art literature in elite soccer, and summarizes existing real-time video analytics algorithms. We also discuss real-time crowdsourcing of the obtained data, tactical and technical performance, distributed computing and its importance in video analytics and propose a future research perspective.

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PMData: A sports logging dataset

Cited by 18 publications

References 13 publications

COROID: A Crowdsourcing-based Companion Drones to Tackle Current and Future Pandemics

COROID: A Crowdsourcing-based Companion Drones to Tackle Current and Future Pandemics

Service resource allocation problem in the IoT driven personalized healthcare information platform

Video Analytics in Elite Soccer: A Distributed Computing Perspective

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