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Investigation of Bluetooth Communications for Low-Power Embedded Sensor Networks in Agriculture
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: Transactions of the ASABE. 59(5): 1021-1029. (doi: 10.13031/trans.59.11173) @2016
Authors: Andrew D. Balmos, Alexander W. Layton, Aaron Ault, James V. Krogmeier, Dennis R. Buckmaster
Keywords: Bluetooth, Bluetooth Low Energy (LE/BLE), Farm data automation, Internet of Things (IoT), Low power, Sensor, Sensor network.
Abstract. 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.
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