Comparing the Performance of Indoor Localization Systems through the EvAAL Framework

被引:62
|
作者
Potorti, Francesco [1 ]
Park, Sangjoon [2 ]
Jimenez Ruiz, Antonio Ramon [3 ]
Barsocchi, Paolo [1 ]
Girolami, Michele [1 ]
Crivello, Antonino [1 ]
Lee, So Yeon [2 ]
Lim, Jae Hyun [2 ]
Torres-Sospedra, Joaquin [4 ]
Seco, Fernando [3 ]
Montoliu, Raul [4 ]
Martin Mendoza-Silva, German [4 ]
Perez Rubio, Maria Del Carmen [5 ]
Losada-Gutierrez, Cristina [5 ]
Espinosa, Felipe [5 ]
Macias-Guarasa, Javier [5 ]
机构
[1] CNR, ISTI Inst, I-56124 Pisa, Italy
[2] ETRI, Daejeon 34129, South Korea
[3] UPM, CSIC, Ctr Automat & Robot, Arganda Del Rey 28500, Spain
[4] Univ Jaume 1, Inst New Imaging Technol, Castellon De La Plana 12071, Spain
[5] Univ Alcala, Dept Elect, Alcala De Henares 28871, Spain
关键词
indoor localization; indoor navigation; indoor competition; standard evaluation metrics; benchmarking; performance evaluation; Active and Assisted Living; smartphone sensors; pedestrian dead reckoning; PEDESTRIAN TRACKING; LOCATION TRACKING; RECOGNITION;
D O I
10.3390/s17102327
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In recent years, indoor localization systems have been the object of significant research activity and of growing interest for their great expected social impact and their impressive business potential. Application areas include tracking and navigation, activity monitoring, personalized advertising, Active and Assisted Living (AAL), traceability, Internet of Things (IoT) networks, and Home-land Security. In spite of the numerous research advances and the great industrial interest, no canned solutions have yet been defined. The diversity and heterogeneity of applications, scenarios, sensor and user requirements, make it difficult to create uniform solutions. From that diverse reality, a main problem is derived that consists in the lack of a consensus both in terms of the metrics and the procedures used to measure the performance of the different indoor localization and navigation proposals. This paper introduces the general lines of the EvAAL benchmarking framework, which is aimed at a fair comparison of indoor positioning systems through a challenging competition under complex, realistic conditions. To evaluate the framework capabilities, we show how it was used in the 2016 Indoor Positioning and Indoor Navigation (IPIN) Competition. The 2016 IPIN competition considered three different scenario dimensions, with a variety of use cases: (1) pedestrian versus robotic navigation, (2) smartphones versus custom hardware usage and (3) real-time positioning versus off-line post-processing. A total of four competition tracks were evaluated under the same EvAAL benchmark framework in order to validate its potential to become a standard for evaluating indoor localization solutions. The experience gained during the competition and feedback from track organizers and competitors showed that the EvAAL framework is flexible enough to successfully fit the very different tracks and appears adequate to compare indoor positioning systems.
引用
收藏
页数:28
相关论文
共 50 条
  • [31] An Indoor Knowledge Graph Framework for Efficient Pedestrian Localization
    Guo, Sheng
    Niu, Guanchong
    Wang, Zewei
    Pun, Man-On
    Yang, Kai
    IEEE SENSORS JOURNAL, 2021, 21 (04) : 5151 - 5163
  • [32] Indoor Localization Based on Factor Graphs: A Unified Framework
    Yang, Lyuxiao
    Wu, Nan
    Li, Bin
    Yuan, Weijie
    Hanzo, Lajos
    IEEE INTERNET OF THINGS JOURNAL, 2023, 10 (05) : 4353 - 4366
  • [33] A sensor based indoor localization through fingerprinting
    Haque, Israat Tanzeena
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2014, 44 : 220 - 229
  • [34] A scheme for indoor localization through RF profiling
    Haque, Israat Tanzeena
    Nikolaidis, Ioanis
    Gburzynski, Pawel
    2009 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION WORKSHOPS, VOLS 1 AND 2, 2009, : 659 - 663
  • [35] A realistic evaluation of indoor positioning systems based on Wi-Fi fingerprinting: The 2015 EvAAL-ETRI competition
    Torres-Sospedra, Joaquin
    Moreira, Adriano
    Knauth, Stefan
    Berkvens, Rafael
    Montoliu, Raul
    Belmonte, Oscar
    Trilles, Sergio
    Nicolau, Maria Joao
    Meneses, Filipe
    Costa, Antonio
    Koukofikis, Athanasios
    Weyn, Maarten
    Peremans, Herbert
    JOURNAL OF AMBIENT INTELLIGENCE AND SMART ENVIRONMENTS, 2017, 9 (02) : 263 - 279
  • [36] Indoor Localization through Dynamic Time Warping
    Subbu, Kalyan Pathapati
    Gozick, Brandon
    Dantu, Ram
    2011 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2011, : 1639 - 1644
  • [37] RSSI Indoor Localization through a Bayesian Strategy
    Zhou, Fu
    Lin, Kaixian
    Ren, Aifeng
    Cao, Dongjian
    Zhang, Zhiya
    Rehman, Masood Ur
    Yang, Xiaodong
    Alomainy, Akram
    2017 IEEE 2ND ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC), 2017, : 1975 - 1979
  • [38] ENHANCED INDOOR LOCALIZATION THROUGH CROWD SENSING
    Arias-de-Reyna, Eva
    Dardari, Davide
    Closas, Pau
    Djuric, Petar M.
    2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2017, : 2487 - 2491
  • [39] A High Configurable Protocol for Indoor Localization Systems
    Robles, Jorge Juan
    Tromer, Sebastian
    Hidalgo, Jorge Perez
    Lehnert, Ralf
    2011 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION, 2011,
  • [40] Performance Evaluation of Refinement Method in Indoor Localization
    Ramadhani, Afifah Dwi
    Kristalina, Prima
    Sudarsono, Amang
    2018 INTERNATIONAL ELECTRONICS SYMPOSIUM ON ENGINEERING TECHNOLOGY AND APPLICATIONS (IES-ETA), 2018, : 183 - 188