TY - JOUR
T1 - Evaluating Indoor Positioning Systems in a Shopping Mall
T2 - The Lessons Learned from the IPIN 2018 Competition
AU - Renaudin, Valerie
AU - Ortiz, Miguel
AU - Perul, Johan
AU - Torres-Sospedra, Joaquin
AU - Jimenez, Antonio Ramon
AU - Perez-Navarro, Antoni
AU - Martin Mendoza-Silva, German
AU - Seco, Fernando
AU - Landau, Yael
AU - Marbel, Revital
AU - Ben-Moshe, Boaz
AU - Zheng, Xingyu
AU - Ye, Feng
AU - Kuang, Jian
AU - Li, Yu
AU - Niu, Xiaoji
AU - Landa, Vlad
AU - Hacohen, Shlomi
AU - Shvalb, Nir
AU - Lu, Chuanhua
AU - Uchiyama, Hideaki
AU - Thomas, Diego
AU - Shimada, Atsushi
AU - Taniguchi, Rin Ichiro
AU - Ding, Zhenxing
AU - Xu, Feng
AU - Kronenwett, Nikolai
AU - Vladimirov, Blagovest
AU - Lee, Soyeon
AU - Cho, Eunyoung
AU - Jun, Sungwoo
AU - Lee, Changeun
AU - Park, Sangjoon
AU - Lee, Yonghyun
AU - Rew, Jehyeok
AU - Park, Changjun
AU - Jeong, Hyeongyo
AU - Han, Jaeseung
AU - Lee, Keumryeol
AU - Zhang, Wenchao
AU - Li, Xianghong
AU - Wei, Dongyan
AU - Zhang, Ying
AU - Park, So Young
AU - Park, Chan Gook
AU - Knauth, Stefan
AU - Pipelidis, Georgios
AU - Tsiamitros, Nikolaos
AU - Lungenstrass, Tomas
AU - Morales, Juan Pablo
AU - Trogh, Jens
AU - Plets, David
AU - Opiela, Miroslav
AU - Fang, Shih Hau
AU - Tsao, Yu
AU - Chien, Ying Ren
AU - Yang, Shi Shen
AU - Ye, Shih Jyun
AU - Ali, Muhammad Usman
AU - Hur, Soojung
AU - Park, Yongwan
N1 - Funding Information:
Corresponding authors: Valerie Renaudin (valerie.renaudin@ifsttar.fr), Joaquín Torres-Sospedra (jtorres@uji.es), Antonio Ramón Jiménez (antonio.jimenez@csic.es), Antoni Pérez-Navarro (aperezn@uoc.edu), Boaz Ben-Moshe (benmo@g.ariel.ac.il), Xingyu Zheng (380407078@qq.com), Yu Li (yulinav@whu.edu.cn), Hideaki Uchiyama (uchiyama@limu.ait.kyushu-u.ac.jp), Zhenxing Ding (cw0216@sina.com), Nikolai Kronenwett (nicolai.kronenwett@kit.edu), Soyeon Lee (sylee@etri.re.kr), Dongyan Wei (weidongyan@aoe.ac.cn), Ying Zhang (yingzhang@google.com), Stefan Knauth (stefan.knauth@hft-stuttgart.de), Georgios Pipelidis (georgios.pipelidis@tum.de), Tomás Lungenstrass (tomas@ararads.com), Jens Trogh (jens.trogh@ugent.be), Miroslav Opiela (miroslav.opiela@upjs.sk), Shih-Hau Fang (shfang@saturn.yzu.edu.tw), Ying-Ren Chien (yrchien@niu.edu.tw), and Yongwan Park (ywpark@yu.ac.kr) This work was supported in part by the French Pays de la Loire Regional Council through Etoiles Montantes under the organization of IPIN2018 international competition under Grant 2017-10671, in part by the Atlantis Shopping Mall, in part by the Project REPNIN Plus under Grant TEC2017-90808-REDT, in part by the ICT Research and Development Program of MSIT/IITP, South Korea, (Development of Precise Positioning Technology for the Enhancement of Pedestrian Position, Spatial Cognition and Sports Competition Analysis), through the ETRI Team under Grant 2017-0-00543, in part by the JSPS KAKENHI through the Kyushu Team under Grant JP18H04125, in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovak, through UPJS Team, under Grant 1/0056/18, in part by the Slovak Research and Development Agency through UPJS Team under Contract APVV-15-0091, in part by the German federal Ministry of Education and Research Programme ‘‘FH-Impuls 2016’’through HFTS Team under Contract 13FH9I01IA, in part by the Ministry of Science and Technology (MOST), Taiwan, through the YAI Team under Grant MOST 108-2634-F-155-001, and in part by the Strategic Priority Research Program of the Chinese Academy Sciences under Grant XDA17040202.
Publisher Copyright:
© 2013 IEEE.
PY - 2019
Y1 - 2019
N2 - The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-Time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future.
AB - The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-Time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future.
UR - http://www.scopus.com/inward/record.url?scp=85077705668&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85077705668&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2019.2944389
DO - 10.1109/ACCESS.2019.2944389
M3 - Article
AN - SCOPUS:85077705668
VL - 7
SP - 148594
EP - 148628
JO - IEEE Access
JF - IEEE Access
SN - 2169-3536
M1 - 8852722
ER -