Internet of Things to network smart devices for ecosystem monitoring
Authors: Li, X; Zhao, N; Jin, R; Liu, SM; Sun, XM; Wen, XF; Wu, DX; Zhou, Y; Guo, JW; Chen, SP; Xu, ZW; Ma, MG; Wang, TM; Qu, YH; Wang, XW; Wu, FM; Zhou, YK
Volume: 64 Issue: 17 Pages: 1234-1245 Published: SEP 15 2019 Language: English Document type: Article
Smart, real-time, low-cost, and distributed ecosystem monitoring is essential for understanding and managing rapidly changing ecosystems. However, new techniques in the big data era have rarely been introduced into operational ecosystem monitoring, particularly for fragile ecosystems in remote areas. We introduce the Internet of Things (IoT) techniques to establish a prototype ecosystem monitoring system by developing innovative smart devices and using IoT technologies for ecosystem monitoring in isolated environments. The developed smart devices include four categories: large-scale and nonintrusive instruments to measure evapotranspiration and soil moisture, in situ observing systems for CO2 and delta C-13 associated with soil respiration, portable and distributed devices for monitoring vegetation variables, and Bi-CMOS cameras and pressure trigger sensors for terrestrial vertebrate monitoring. These new devices outperform conventional devices and are connected to each other via wireless communication networks. The breakthroughs in the ecosystem monitoring IoT include new data loggers and long-distance wireless sensor network technology that supports the rapid transmission of data from devices to wireless networks. The applicability of this ecosystem monitoring IoT is verified in three fragile ecosystems, including a karst rocky desertification area, the National Park for Amur Tigers, and the oasis-desert ecotone in China. By integrating these devices and technologies with an ecosystem monitoring information system, a seamless data acquisition, transmission, processing, and application IoT is created. The establishment of this ecosystem monitoring IoT will serve as a new paradigm for ecosystem monitoring and therefore provide a platform for ecosystem management and decision making in the era of big data. (C) 2019 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved.