Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/82092 |
Resumo: | Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements. |
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Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competitionSensor phenomena and characterizationIndoor navigationTestingStandardsSatellite broadcastingRecurrent neural networksReceived signal strength indicatorIndoor positioning and navigationevaluationsmartphone-based positioningfoot-mounted IMUpositioning in industrial scenarios and factoriesvehicle-positioningCiências Naturais::Ciências da Computação e da InformaçãoScience & TechnologyEvery year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001.IEEEet. al.Universidade do MinhoPotorti, FrancescoTorres-Sospedra, JoaquínQuezada-Gaibor, DarwinJimenez, Antonio RamonSeco, FernandoPerez-Navarro, AntoniOrtiz, MiguelZhu, NiRenaudin, ValerieIchikari, RyosukeShimomura, RyoOhta, NozomuNagae, SatsukiKurata, TakeshiWei, DongyanJi, XinchunZhang, WenchaoKram, SebastianStahlke, MaximilianMutschler, ChristopherCrivello, AntoninoBarsocchi, PaoloGirolami, MichelePalumbo, FilippoChen, RuizhiWu, YuanLi, WeiYu, YueXu, ShihaoHuang, LixiongLiu, TaoKuang, JianNiu, XiaojiYoshida, TakutoNagata, YoshiteruFukushima, YutoFukatani, NobuyaHayashida, NozomiAsai, YusukeUrano, KentaGe, WenfeiLee, Nien-TingFang, Shih-HauJie, You-ChengYoung, Shawn-RongChien, Ying-RenYu, Chih-ChiehMa, ChengqiWu, BangZhang, WeiWang, YankunFan, YongleiPoslad, StefanSelviah, David R.Wang, WeixiYuan, HongYonamoto, YoshitomoYamaguchi, MasahiroKaichi, TomoyaZhou, BaodingLiu, XuGu, ZhiningYang, ChengjingWu, ZhiqianXie, DoudouHuang, CanZheng, LingxiangPeng, AoJin, GeWang, QuLuo, HaiyongXiong, HaoBao, LinfengZhang, PushuoZhao, FangYu, Chia-AnHung, Chun-HaoAntsfeld, LeonidSilva, Ivo Miguel MenezesPendão, Cristiano GonçalvesMeneses, FilipeNicolau, Maria JoãoCosta, AntónioMoreira, AdrianoCock, Cedric DePlets, DavidOpiela, MiroslavJakub Džama,Zhang, LiqiangLi, HuChen, BoxuanLiu, YuYean, SeanglidetLim, Bo ZhiTeo, Wei JieLee, Bu SungOh, Hong Lye2022-03-152022-03-15T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/82092engF. Potortì et al., "Off-Line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences From IPIN 2020 Competition," in IEEE Sensors Journal, vol. 22, no. 6, pp. 5011-5054, 15 March15, 2022, doi: 10.1109/JSEN.2021.3083149.1530-437X10.1109/JSEN.2021.3083149https://ieeexplore.ieee.org/document/9439493info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-12-30T01:22:49Zoai:repositorium.sdum.uminho.pt:1822/82092Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:47:09.716882Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition |
title |
Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition |
spellingShingle |
Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition Potorti, Francesco Sensor phenomena and characterization Indoor navigation Testing Standards Satellite broadcasting Recurrent neural networks Received signal strength indicator Indoor positioning and navigation evaluation smartphone-based positioning foot-mounted IMU positioning in industrial scenarios and factories vehicle-positioning Ciências Naturais::Ciências da Computação e da Informação Science & Technology |
title_short |
Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition |
title_full |
Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition |
title_fullStr |
Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition |
title_full_unstemmed |
Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition |
title_sort |
Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition |
author |
Potorti, Francesco |
author_facet |
Potorti, Francesco Torres-Sospedra, Joaquín Quezada-Gaibor, Darwin Jimenez, Antonio Ramon Seco, Fernando Perez-Navarro, Antoni Ortiz, Miguel Zhu, Ni Renaudin, Valerie Ichikari, Ryosuke Shimomura, Ryo Ohta, Nozomu Nagae, Satsuki Kurata, Takeshi Wei, Dongyan Ji, Xinchun Zhang, Wenchao Kram, Sebastian Stahlke, Maximilian Mutschler, Christopher Crivello, Antonino Barsocchi, Paolo Girolami, Michele Palumbo, Filippo Chen, Ruizhi Wu, Yuan Li, Wei Yu, Yue Xu, Shihao Huang, Lixiong Liu, Tao Kuang, Jian Niu, Xiaoji Yoshida, Takuto Nagata, Yoshiteru Fukushima, Yuto Fukatani, Nobuya Hayashida, Nozomi Asai, Yusuke Urano, Kenta Ge, Wenfei Lee, Nien-Ting Fang, Shih-Hau Jie, You-Cheng Young, Shawn-Rong Chien, Ying-Ren Yu, Chih-Chieh Ma, Chengqi Wu, Bang Zhang, Wei Wang, Yankun Fan, Yonglei Poslad, Stefan Selviah, David R. Wang, Weixi Yuan, Hong Yonamoto, Yoshitomo Yamaguchi, Masahiro Kaichi, Tomoya Zhou, Baoding Liu, Xu Gu, Zhining Yang, Chengjing Wu, Zhiqian Xie, Doudou Huang, Can Zheng, Lingxiang Peng, Ao Jin, Ge Wang, Qu Luo, Haiyong Xiong, Hao Bao, Linfeng Zhang, Pushuo Zhao, Fang Yu, Chia-An Hung, Chun-Hao Antsfeld, Leonid Silva, Ivo Miguel Menezes Pendão, Cristiano Gonçalves Meneses, Filipe Nicolau, Maria João Costa, António Moreira, Adriano Cock, Cedric De Plets, David Opiela, Miroslav Jakub Džama, Zhang, Liqiang Li, Hu Chen, Boxuan Liu, Yu Yean, Seanglidet Lim, Bo Zhi Teo, Wei Jie Lee, Bu Sung Oh, Hong Lye |
author_role |
author |
author2 |
Torres-Sospedra, Joaquín Quezada-Gaibor, Darwin Jimenez, Antonio Ramon Seco, Fernando Perez-Navarro, Antoni Ortiz, Miguel Zhu, Ni Renaudin, Valerie Ichikari, Ryosuke Shimomura, Ryo Ohta, Nozomu Nagae, Satsuki Kurata, Takeshi Wei, Dongyan Ji, Xinchun Zhang, Wenchao Kram, Sebastian Stahlke, Maximilian Mutschler, Christopher Crivello, Antonino Barsocchi, Paolo Girolami, Michele Palumbo, Filippo Chen, Ruizhi Wu, Yuan Li, Wei Yu, Yue Xu, Shihao Huang, Lixiong Liu, Tao Kuang, Jian Niu, Xiaoji Yoshida, Takuto Nagata, Yoshiteru Fukushima, Yuto Fukatani, Nobuya Hayashida, Nozomi Asai, Yusuke Urano, Kenta Ge, Wenfei Lee, Nien-Ting Fang, Shih-Hau Jie, You-Cheng Young, Shawn-Rong Chien, Ying-Ren Yu, Chih-Chieh Ma, Chengqi Wu, Bang Zhang, Wei Wang, Yankun Fan, Yonglei Poslad, Stefan Selviah, David R. Wang, Weixi Yuan, Hong Yonamoto, Yoshitomo Yamaguchi, Masahiro Kaichi, Tomoya Zhou, Baoding Liu, Xu Gu, Zhining Yang, Chengjing Wu, Zhiqian Xie, Doudou Huang, Can Zheng, Lingxiang Peng, Ao Jin, Ge Wang, Qu Luo, Haiyong Xiong, Hao Bao, Linfeng Zhang, Pushuo Zhao, Fang Yu, Chia-An Hung, Chun-Hao Antsfeld, Leonid Silva, Ivo Miguel Menezes Pendão, Cristiano Gonçalves Meneses, Filipe Nicolau, Maria João Costa, António Moreira, Adriano Cock, Cedric De Plets, David Opiela, Miroslav Jakub Džama, Zhang, Liqiang Li, Hu Chen, Boxuan Liu, Yu Yean, Seanglidet Lim, Bo Zhi Teo, Wei Jie Lee, Bu Sung Oh, Hong Lye |
author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
et. al. Universidade do Minho |
dc.contributor.author.fl_str_mv |
Potorti, Francesco Torres-Sospedra, Joaquín Quezada-Gaibor, Darwin Jimenez, Antonio Ramon Seco, Fernando Perez-Navarro, Antoni Ortiz, Miguel Zhu, Ni Renaudin, Valerie Ichikari, Ryosuke Shimomura, Ryo Ohta, Nozomu Nagae, Satsuki Kurata, Takeshi Wei, Dongyan Ji, Xinchun Zhang, Wenchao Kram, Sebastian Stahlke, Maximilian Mutschler, Christopher Crivello, Antonino Barsocchi, Paolo Girolami, Michele Palumbo, Filippo Chen, Ruizhi Wu, Yuan Li, Wei Yu, Yue Xu, Shihao Huang, Lixiong Liu, Tao Kuang, Jian Niu, Xiaoji Yoshida, Takuto Nagata, Yoshiteru Fukushima, Yuto Fukatani, Nobuya Hayashida, Nozomi Asai, Yusuke Urano, Kenta Ge, Wenfei Lee, Nien-Ting Fang, Shih-Hau Jie, You-Cheng Young, Shawn-Rong Chien, Ying-Ren Yu, Chih-Chieh Ma, Chengqi Wu, Bang Zhang, Wei Wang, Yankun Fan, Yonglei Poslad, Stefan Selviah, David R. Wang, Weixi Yuan, Hong Yonamoto, Yoshitomo Yamaguchi, Masahiro Kaichi, Tomoya Zhou, Baoding Liu, Xu Gu, Zhining Yang, Chengjing Wu, Zhiqian Xie, Doudou Huang, Can Zheng, Lingxiang Peng, Ao Jin, Ge Wang, Qu Luo, Haiyong Xiong, Hao Bao, Linfeng Zhang, Pushuo Zhao, Fang Yu, Chia-An Hung, Chun-Hao Antsfeld, Leonid Silva, Ivo Miguel Menezes Pendão, Cristiano Gonçalves Meneses, Filipe Nicolau, Maria João Costa, António Moreira, Adriano Cock, Cedric De Plets, David Opiela, Miroslav Jakub Džama, Zhang, Liqiang Li, Hu Chen, Boxuan Liu, Yu Yean, Seanglidet Lim, Bo Zhi Teo, Wei Jie Lee, Bu Sung Oh, Hong Lye |
dc.subject.por.fl_str_mv |
Sensor phenomena and characterization Indoor navigation Testing Standards Satellite broadcasting Recurrent neural networks Received signal strength indicator Indoor positioning and navigation evaluation smartphone-based positioning foot-mounted IMU positioning in industrial scenarios and factories vehicle-positioning Ciências Naturais::Ciências da Computação e da Informação Science & Technology |
topic |
Sensor phenomena and characterization Indoor navigation Testing Standards Satellite broadcasting Recurrent neural networks Received signal strength indicator Indoor positioning and navigation evaluation smartphone-based positioning foot-mounted IMU positioning in industrial scenarios and factories vehicle-positioning Ciências Naturais::Ciências da Computação e da Informação Science & Technology |
description |
Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-03-15 2022-03-15T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/82092 |
url |
https://hdl.handle.net/1822/82092 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
F. Potortì et al., "Off-Line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences From IPIN 2020 Competition," in IEEE Sensors Journal, vol. 22, no. 6, pp. 5011-5054, 15 March15, 2022, doi: 10.1109/JSEN.2021.3083149. 1530-437X 10.1109/JSEN.2021.3083149 https://ieeexplore.ieee.org/document/9439493 |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
IEEE |
publisher.none.fl_str_mv |
IEEE |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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