A Scalable Bluetooth Low Energy Design Model for Sensor Detection for an Indoor Real Time Location System

被引:0
|
作者
Pancham, Jay [1 ]
Millham, Richard [1 ]
Fong, Simon James [2 ]
机构
[1] Durban Univ Technol, Durban, South Africa
[2] Univ Macau, Taipa, Macau, Peoples R China
关键词
Bluetooth Low Energy; BLE; Real Time Location System; RSSI; Indoor positioning;
D O I
10.1007/978-3-319-95171-3_25
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Indoor Real Time Location Systems (RTLS) research identifies Bluetooth Low Energy as one of the technologies that promise an acceptable response to the requirements of the Healthcare environment. A scalable dynamic model for sensor detection, which uses the latest developments of Bluetooth Low Energy, is designed to extend its range coverage. This design extends on our previous papers which tested the range and signal strength through multiple types of obstructions. The model is based on the scenarios and use cases identified for future use in RTLS within the Health care sector. The Unified Modelling Language (UML) is used to present the models and inspections and walkthroughs are used to validate and verify them. This model will be implemented using Bluetooth Low Energy devices for patients and assets with in the Health care sector.
引用
收藏
页码:317 / 330
页数:14
相关论文
共 50 条
  • [21] Bluetooth Low Energy Receiver System Design
    Pipino, Alessandra
    Liscidini, Antonio
    Wan, Karen
    Baschirotto, Andrea
    2015 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2015, : 465 - 468
  • [22] Analysis of Bluetooth Low Energy Detection Range Improvements for Indoor Environments
    Pancham, Jay
    Millham, Richard
    Fong, Simon James
    COMPUTATIONAL SCIENCE - ICCS 2018, PT III, 2018, 10862 : 598 - 609
  • [23] TraceMe - Indoor Real-Time Location System
    Silva, Pedro M. Mestre A.
    Paralta, Maximino
    Caldeirinha, Rafael
    Rodrigues, Jorge
    Serodio, Carlos M. J. A.
    IECON: 2009 35TH ANNUAL CONFERENCE OF IEEE INDUSTRIAL ELECTRONICS, VOLS 1-6, 2009, : 2573 - +
  • [24] TraceMe - Indoor real-time location system
    Mestre A Silva, Pedro M.
    Paralta, Maximino
    Caldeirinha, Rafael
    Rodrigues, Jorge
    Serôdio, Carlos M.J.A.
    IECON Proceedings (Industrial Electronics Conference), 2009, : 2721 - 2725
  • [25] Indoor Localization System Based on Bluetooth Low Energy for Museum Applications
    Giuliano, Romeo
    Cardarilli, Gian Carlo
    Cesarini, Carlo
    Di Nunzio, Luca
    Fallucchi, Francesca
    Fazzolari, Rocco
    Mazzenga, Franco
    Re, Marco
    Vizzarri, Alessandro
    ELECTRONICS, 2020, 9 (06) : 1 - 20
  • [26] Towards an Indoor Navigation System using Bluetooth Low Energy Beacons
    Campana, Fernando
    Pinargote, Adriano
    Dominguez, Federico
    Pelaez, Enrique
    2017 IEEE SECOND ECUADOR TECHNICAL CHAPTERS MEETING (ETCM), 2017,
  • [27] Remote Detection of Indoor Human Proximity using Bluetooth Low Energy Beacons
    Mavilia, Fabio
    Palumbo, Filippo
    Barsocchi, Paolo
    Chessa, Stefano
    Girolami, Michele
    2019 15TH INTERNATIONAL CONFERENCE ON INTELLIGENT ENVIRONMENTS (IE 2019), 2019, : 16 - 21
  • [28] Medical Equipment Real-Time Locating System in Hospitals Based on Bluetooth Low Energy
    Sherif, Fayroz F.
    Ahmed, Khaled S.
    BIOINFORMATICS AND BIOMEDICAL ENGINEERING, PT I, IWBBIO 2024, 2024, 14848 : 142 - 151
  • [29] Real-Time Occupancy Detection System Using Low-Resolution Thermopile Array Sensor for Indoor Environment
    Shubha, B.
    Shastrimath, V. Veena Devi
    IEEE ACCESS, 2022, 10 : 130981 - 130995
  • [30] A Real-Time Spine Orthopedic System Based on Bluetooth Low Energy and Internet of Things
    Xia, Kun
    Hou, Ruifeng
    Yang, Junlin
    Li, Xiang
    IEEE ACCESS, 2021, 9 : 153977 - 153984