mSAIL: milligram-scale multi-modal sensor platform for monarch butterfly migration tracking

mSAIL: milligram-scale multi-modal sensor platform for monarch butterfly migration tracking
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mSAIL:用于帝王蝶迁徙跟踪的毫克级多模态传感器平台

DOI:
10.1145/3447993.3483263
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发表时间:
2021
期刊:
International Conference On Mobile Computing And Networking
影响因子:
--
通讯作者:
Lim, Jaechan
Lim, Jaechan
中科院分区:
--
文献类型:
--
作者:
Lee, Inhee;Hsiao, Roger;Carichner, Gordy;Hsu, Chin-Wei;Yang, Mingyu;Shoouri, Sara;Ernst, Katherine;Carichner, Tess;Li, Yuyang;Lim, Jaechan

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每年秋天,美国北方和加拿大的数百万只帝王蝶都会迁徙4,000公里,在墨西哥中部的同一群山峰上过冬。为了精确地跟踪帝王蝶并研究它们的导航,帝王蝶跟踪者必须在蝴蝶3个月的旅程中每天获得蝴蝶的位置。而且,跟踪器必须在数十毫克(mg)的重量和几毫米(mm)的尺寸下执行此任务,以避免干扰君主的飞行。本文提出了mSAIL,8 × 8 × 2.6 mm和62 mg嵌入式系统,用于君主迁移跟踪,使用8个先前定制设计的IC构建,提供太阳能收集,超低功耗处理器,光/温度传感器,电源管理和无线收发器,所有集成和3D堆叠在微型PCB上,带有8 × 8 mm印刷天线。该系统旨在记录和压缩迁移过程中的光和温度数据,同时收集太阳能以实现能源自主,并在墨西哥的越冬地点无线传输数据,从中可以使用基于深度学习的定位算法估计蝴蝶的日常位置。在室外植物园的一只活蝴蝶上进行了为期2天的mSAIL试验,证明了个体蝴蝶定位和跟踪的可行性。
Each fall, millions of monarch butterflies across the northern US and Canada migrate up to 4,000 km to overwinter in the exact same cluster of mountain peaks in central Mexico. To track monarchs precisely and study their navigation, a monarch tracker must obtain daily localization of the butterfly as it progresses on its 3-month journey. And, the tracker must perform this task while having a weight in the tens of milligram (mg) and measuring a few millimeters (mm) in size to avoid interfering with monarch's flight. This paper proposes mSAIL, 8 × 8 × 2.6 mm and 62 mg embedded system for monarch migration tracking, constructed using 8 prior custom-designed ICs providing solar energy harvesting, an ultra-low power processor, light/temperature sensors, power management, and a wireless transceiver, all integrated and 3D stacked on a micro PCB with an 8 × 8 mm printed antenna. The proposed system is designed to record and compress light and temperature data during the migration path while harvesting solar energy for energy autonomy, and wirelessly transmit the data at the overwintering site in Mexico, from which the daily location of the butterfly can be estimated using a deep learning-based localization algorithm. A 2-day trial experiment of mSAIL attached on a live butterfly in an outdoor botanical garden demonstrates the feasibility of individual butterfly localization and tracking.
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