IoTree: A Battery-free Wearable System with Biocompatible Sensors for Continuous Tree Health Monitoring
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- Tuan Dang, University of Texas at Arlington
- Trung Tran, Sungkyunkwan University
- Khang Nguyen, University of Texas at Arlington
- Tien Pham, University of Texas at Arlington
- Nhat Pham, University of Oxford
- Tam Vu, University of Colorado Boulder
- Phuc Nguyen, University of Texas at Arlington
In this paper, we present a low-maintenance, wind-powered, batteryfree, biocompatible, tree wearable, and intelligent sensing system, namely IoTree, to monitor water and nutrient levels inside a living tree. IoTree system includes tiny-size, biocompatible, and implantable sensors that continuously measure the impedance variations inside the living tree’s xylem, where water and nutrients are transported from the root to the upper parts. The collected data are then compressed and transmitted to a base station located at up to 1.8 kilometers (approximately 1.1 miles) away. The entire IoTree system is powered by wind energy and controlled by an adaptive computing technique called block-based intermittent computing, ensuring the forward progress and data consistency under intermittent power and allowing the firmware to execute with the most optimal memory and energy usage. We prototype IoTree that opportunistically performs sensing, data compression, and long-range communication tasks without batteries. During in-lab experiments, IoTree also obtains the accuracy of 91.08% and 90.51% in measuring 10 levels of nutrients, 𝑁𝐻3 and 𝐾2𝑂, respectively. While tested with Burkwood Viburnum and White Bird trees in the indoor environment, IoTree data strongly correlated with multiple watering and fertilizing events. We also deployed IoTree on a grapevine farm for 30 days, and the system is able to provide sufficient measurements every day
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@inproceedings{dang2022iotree,
title={ioTree: a battery-free wearable system with biocompatible sensors for continuous tree health monitoring},
author={Dang, Tuan and Tran, Trung and Nguyen, Khang and Pham, Tien and Pham, Nhat and Vu, Tam and Nguyen, Phuc},
booktitle={Proceedings of the 28th Annual International Conference on Mobile Computing And Networking},
pages={352--366},
year={2022}
}