INVESTIGATION OF BLUETOOTH COMMUNICATIONS FOR LOW-POWER EMBEDDED SENSOR NETWORKS IN AGRICULTURE

被引:2
|
作者
Balmos, A. D. [1 ]
Layton, A. W. [1 ]
Ault, A. [1 ]
Krogmeier, J. V. [1 ]
Buckmaster, D. R. [2 ]
机构
[1] Purdue Univ, Sch Elect & Comp Engn, W Lafayette, IN 47907 USA
[2] Purdue Univ, Dept Agr & Biol Engn, W Lafayette, IN 47907 USA
关键词
Bluetooth; Bluetooth Low Energy (LE/BLE); Farm data automation; Internet of Things (IoT); Low power; Sensor; Sensor network; PERFORMANCE;
D O I
10.13031/trans.59.11173
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
Internet of things (IoT) sensor networks that monitor agricultural equipment can provide useful data to optimize a farm's productivity. For such a network to become widely adopted, the sensors should have battery lives at least as long as a full farming season. While the standard low-power wireless sensor communication platforms, e.g., Zigbee and ANT, may potentially satisfy this requirement, they lack common hardware support in consumer devices. By using more ubiquitous technology, such as cellphones and tablets, the costs and complexity and be significantly reduced. Nearly all mobile devices currently on the market have Bluetooth capability, making it a viable wireless protocol choice. In addition, the recent release and adoption of the Bluetooth 4.0 Low Energy (BLE) standard has solidified it as a strong candidate for use in very low power, long battery life networking. This work investigates how various BLE configurations affect network size, network throughput, and sensor battery lifetimes. We present a strategy to select network parameters that achieve at least a certain sensor update interval and connection latency while simultaneously minimizing the sensor's energy requirements and data latency and conforming to network size and throughput constraints. We present a simple BLE energy model created from current consumption measurements of the commercially available TI CC2540 BLE module. The combination of this BLE energy model and a simple battery capacity model allows the estimation and validation of sufficient battery life. Sensor lifetimes on the order of multiple years can easily be achieved for large update interval and connection latency sensors, which would be typical in mobile agricultural equipment.
引用
收藏
页码:1021 / 1029
页数:9
相关论文
共 50 条
  • [31] A minimalistic approach to image processing for low-power sensor networks
    Ko, T
    Berry, N
    Kyker, R
    VISUAL INFORMATION PROCESSING XIII, 2004, 5438 : 51 - 62
  • [32] Low-power radio design for wireless smart sensor networks
    Fang, Wai-Chi
    Lin, Tsung-Hsien
    IIH-MSP: 2006 INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING, PROCEEDINGS, 2006, : 583 - +
  • [33] Low-Power Distributed Kalman Filter for Wireless Sensor Networks
    Abdelgawad, A.
    Bayoumi, M.
    EURASIP JOURNAL ON EMBEDDED SYSTEMS, 2011, (01)
  • [34] HYREP: A Hybrid Low-Power Protocol for Wireless Sensor Networks
    Kia, G.
    Hassanzadeh, A.
    INTERNATIONAL JOURNAL OF ENGINEERING, 2019, 32 (04): : 519 - 527
  • [35] Low-power cryptographic coprocessor for autonomous wireless sensor networks
    Olszyna, Jakub
    Winiecki, Wieslaw
    PHOTONICS APPLICATIONS IN ASTRONOMY, COMMUNICATIONS, INDUSTRY, AND HIGH-ENERGY PHYSICS EXPERIMENTS 2013, 2013, 8903
  • [36] WiseNET: An Ultra Low-Power Concept for Wireless Sensor Networks
    Decotignie, Jean-Dominique
    Enz, Christian
    Peins, Vincent
    Huebner, Michel
    TM-TECHNISCHES MESSEN, 2010, 77 (02) : 107 - 112
  • [37] Designing an Asynchronous FPGA Processor for Low-Power Sensor Networks
    Liu, Yijun
    Xie, Guobo
    Chen, Pinghua
    Chen, Jingyu
    Li, Zhenkun
    ISSCS 2009: INTERNATIONAL SYMPOSIUM ON SIGNALS, CIRCUITS AND SYSTEMS, VOLS 1 AND 2, PROCEEDINGS,, 2009, : 261 - 265
  • [38] Interference Test Method for Low-Power Wireless Sensor Networks
    Serra, Ramiro
    Nabi, Majid
    2015 IEEE INTERNATIONAL SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY (EMC), 2015, : 150 - 153
  • [39] A Low-Power LDPC Decoder for Multimedia Wireless Sensor Networks
    Xu, Meng
    Ji, Xincun
    Wu, Jianhui
    Zhang, Meng
    IEICE TRANSACTIONS ON COMMUNICATIONS, 2013, E96B (04) : 939 - 947
  • [40] Recovery Effect in Low-Power Nodes of Wireless Sensor Networks
    Rodrigues, Leonardo M.
    Montez, Carlos
    Vasques, Francisco
    Portugal, Paulo
    COMMUNICATION IN CRITICAL EMBEDDED SYSTEMS, WOCCES 2016, 2017, 702 : 45 - 62