Received strength signal intensity performance analysis in wireless sensor network using Arduino platform and XBee wireless modules

被引:13
|
作者
Cama-Pinto, Alejandro [1 ]
Pineres-Espitia, Gabriel [1 ]
Caicedo-Ortiz, Jose [1 ]
Ramirez-Cerpa, Elkin [1 ]
Betancur-Agudelo, Leonardo [2 ]
Gomez-Mula, Francisco [3 ]
机构
[1] Univ Costa, Fac Engn, Calle 58 55-66, Barranquilla 080002, Colombia
[2] Univ Pontificia Bolivariana, Fac Engn, Medellin, Colombia
[3] Univ Granada, Higher Tech Sch Informat Technol & Telecommun Eng, Andalucia, Spain
关键词
XBee; wireless sensor network; radio propagation model; packet loss; received strength signal intensity level;
D O I
10.1177/1550147717722691
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Today, through the monitoring of agronomic variables, the wireless sensor networks are playing an increasingly important role in precision agriculture. Among the emerging technologies used to develop prototypes related to wireless sensor network, we find the Arduino platform and XBee radio modules from the DIGI Company. In this article, based on field tests, we conducted a comparative analysis of received strength signal intensity levels, calculation of path loss with "log-normal shadowing" and free-space path loss models. In addition, we measure packet loss for different transmission, distances and environments with respect to an "Arduino Mega" board, and radio modules XBee PRO S1 and XBee Pro S2. The tests for the packet loss and received strength signal intensity level show the best performance for the XBee Pro S2 in the indoor, outdoor, and rural scenarios.
引用
收藏
页数:9
相关论文
共 50 条
  • [31] Using received signal strength variation for energy efficient data dissemination in wireless sensor networks
    Erdogan, Senol Zafer
    Hussain, Sajid
    DEXA 2007: 18TH INTERNATIONAL CONFERENCE ON DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS, 2007, : 620 - +
  • [32] A Recurrent Learning Method Based on Received Signal Strength Analysis for Improving Wireless Sensor Localization
    Amr Tolba
    Zafer Al-Makhadmeh
    Circuits, Systems, and Signal Processing, 2020, 39 : 1019 - 1037
  • [33] A Recurrent Learning Method Based on Received Signal Strength Analysis for Improving Wireless Sensor Localization
    Tolba, Amr
    Al-Makhadmeh, Zafer
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2020, 39 (02) : 1019 - 1037
  • [34] An Accurate Anchor-Free Contextual Received Signal Strength Approach Localization in a Wireless Sensor Network
    Zaarour, Nour
    Hakem, Nadir
    Kandil, Nahi
    SENSORS, 2024, 24 (04)
  • [35] Received signal strength in large-scale wireless relay sensor network: a stochastic ray approach
    Hu, L.
    Chen, Y.
    Scanlon, W. G.
    IET MICROWAVES ANTENNAS & PROPAGATION, 2011, 5 (14) : 1738 - 1743
  • [36] Real Time Validation of Efficient Received Signal Strength Based Localization Algorithm in Wireless Sensor Network
    Bhuvaneswari, P. T., V
    Vaidehi, V.
    AD HOC & SENSOR WIRELESS NETWORKS, 2014, 23 (3-4) : 159 - 185
  • [37] Gradient Descent Localization Algorithm Based on Received Signal Strength Technique in a Noisy Wireless Sensor Network
    Hijazi, Hussein
    Kandil, Nahi
    Zaarour, Nour
    Hakem, Nadir
    2019 FOURTH INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTATIONAL TOOLS FOR ENGINEERING APPLICATIONS (ACTEA), 2019,
  • [38] Research on Wireless Sensor Network Security Location Based on Received Signal Strength Indicator Sybil Attack
    Wang, Hongbin
    Feng, Liping
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2020, 2020
  • [39] SPAE: A DYNAMIC WIRELESS SENSOR NETWORK PERFORMANCE ANALYSIS AND EVALUATION PLATFORM
    Xie, Dongliang
    Wang, Guoying
    2011 4TH IEEE INTERNATIONAL CONFERENCE ON BROADBAND NETWORK AND MULTIMEDIA TECHNOLOGY (4TH IEEE IC-BNMT2011), 2011, : 545 - 548
  • [40] Received signal strength based positioning for multiple nodes in wireless sensor networks
    Lin, Lanxin
    So, H. C.
    Chan, Y. T.
    DIGITAL SIGNAL PROCESSING, 2014, 25 : 41 - 50