Smartphone-based Floor Detection in Unstructured and Structured Environments

被引:0
|
作者
Adorno, Jorge [1 ]
DeLaHoz, Yueng [2 ]
Labrador, Miguel A. [2 ]
机构
[1] Univ Puerto Rico Bayamon, Dept Comp Sci, Bayamon, PR 00956 USA
[2] Univ S Florida, Dept Comp Sci & Engn, Tampa, FL 33620 USA
关键词
Fall prevention; Android; Navigation system; Segmentation; SLIC; Super-pixels;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Fall related injuries are one of the biggest problem the elderly and the visually impaired populations face everyday. The Center for Disease Control and Prevention reported that about one-third of Americans over the age of 65 fall every year. And according to the American Foundation for the Blind, 25 million Americans suffer from total or partial vision loss, which are twice as likely to fall as their sighted counterparts. This creates a need for preventative systems that would allow for the detection of objects that may constitute a tripping hazard. This paper relates to the implementation of a component that will be part of a much larger system that will allow elderly and visually impaired people navigate safely in indoors environments using off-the-shelf smartphones. The component refers to a floor detection module that will identify the floor ahead of the walking person in structured and unstructured environments in real time. A structured environment is an area with a well defined shape such as hallway, and an unstructured environment is an area without a known shape (not all rooms are the same). Floor detection is a challenging task considering the real time nature of the system, and the use of resource-constrained devices such as smartphones. The evaluation of the system showed that it can work in real time with a run time of 1s. The accuracy of the floor detection module in unstructured environments was measured at 87.6% and 93% in structured environment.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] Smartphone-based Transport Mode Detection for Elderly Care
    Cardoso, Nuno
    Madureira, Joao
    Pereira, Nuno
    2016 IEEE 18TH INTERNATIONAL CONFERENCE ON E-HEALTH NETWORKING, APPLICATIONS AND SERVICES (HEALTHCOM), 2016, : 261 - 266
  • [42] Mining Acceleration Data for Smartphone-based Fall Detection
    Piparunaekaporn, Luepol
    Wichinawakul, Puritud
    Kamolsantiroj, Suwatchai
    2018 10TH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SMART TECHNOLOGY (KST 2018) - CYBERNETICS IN THE NEXT DECADES, 2018, : 74 - 79
  • [43] Smartphone-based low light detection for bioluminescence application
    Huisung Kim
    Youngkee Jung
    Iyll-Joon Doh
    Roxana Andrea Lozano-Mahecha
    Bruce Applegate
    Euiwon Bae
    Scientific Reports, 7
  • [44] Application of a Smartphone-based SPR platform for Glyphosate detection
    Freire, Carmonizia da Silva
    Moreira, Cleumar da Silva
    de Souza Filho, Carlos Alberto
    Santa Cruz, Rossana Moreno
    Falqueto, Alessandro
    Valle, Anderson Luis
    Goulart Filho, Luiz Ricardo
    de Medeiros, Eliton Souto
    Ferreira, Kaline do Nascimento
    2019 IEEE SENSORS APPLICATIONS SYMPOSIUM (SAS), 2019,
  • [45] Smartphone-based road manhole cover detection and classification
    Zhou, Baoding
    Zhao, Wenjian
    Guo, Wenhao
    Li, Linchao
    Zhang, Dejin
    Mao, Qingzhou
    Li, Qingquan
    AUTOMATION IN CONSTRUCTION, 2022, 140
  • [46] Smartphone-based detection of dyes in water for environmental sustainability
    Ozdemir, Gizem Kocakusak
    Bayram, Abdullah
    Kilic, Volkan
    Horzum, Nesrin
    Solmaz, Mehmet E.
    ANALYTICAL METHODS, 2017, 9 (04) : 579 - 585
  • [47] A smartphone-based detection of fall portents for construction workers
    Fang, Yi-Cho
    Dzeng, Ren-Jye
    CREATIVE CONSTRUCTION CONFERENCE 2014, 2014, 85 : 147 - 156
  • [48] Spectrofluorimetric and smartphone-based detection methods for determination of gentamicin
    Kubacki, Karol
    Mermer, Karolina
    Paluch, Justyna
    Bak, Magdalena
    Strzelak, Kamil
    Kozak, Joanna
    MONATSHEFTE FUR CHEMIE, 2024, 155 (8-9): : 899 - 909
  • [49] Online Detection of Spoof Fingers for Smartphone-based Applications
    Li, Dongju
    Kunieda, Hiroaki
    Kumpituck, Supawan
    Isshiki, Tsuyoshi
    2015 IEEE 17TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS, 2015 IEEE 7TH INTERNATIONAL SYMPOSIUM ON CYBERSPACE SAFETY AND SECURITY, AND 2015 IEEE 12TH INTERNATIONAL CONFERENCE ON EMBEDDED SOFTWARE AND SYSTEMS (ICESS), 2015, : 1292 - 1297
  • [50] Validation of a smartphone-based event recorder for arrhythmia detection
    Narasimha, Deepika
    Hanna, Nader
    Beck, Hiroko
    Chaskes, Michael
    Glover, Robert
    Gatewood, Robert
    Bourji, Mohamad
    Gudleski, Gregory D.
    Danzer, Susan
    Curtis, Anne B.
    PACE-PACING AND CLINICAL ELECTROPHYSIOLOGY, 2018, 41 (05): : 487 - 494