Collaborative Research: IIBR Multidisciplinary: mSAIL (Michigan Small Animal Integrated Logger): a milligram-scale, multi-modal sensor and analytics monitoring platform
Collaborative Research: IIBR Multidisciplinary: mSAIL (Michigan Small Animal Integrated Logger): a milligram-scale, multi-modal sensor and analytics monitoring platform
批准号:
2045017
负责人:
Delbert Green
金额:
$61.36万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-04-15 至 2025-03-31
中文摘要
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英文摘要
An award is made to the University of Michigan and the University of Pittsburgh to develop and demonstrate a new logger and analytics platform for small terrestrial animal monitoring called mSAIL (Michigan Small Animal Integrated Logger). mSAIL is a millimeter-scale miniaturized tag attached to animals to record, store, and relay environmental, physiological, and behavioral data. This information is critical not only for a richer mechanistic understanding of animal and ecosystem function, but also in order to predict how these systems will change as Earth’s climate changes. This research and resulting technology will have a significant broad impact such as engaging the public and raising scientific literacy because the machine learning algorithms for mSAIL will be trained using real-world data collected by community volunteers. As well, this work will provide substantial mentoring and training opportunities for diverse participants in a cross-disciplinary environment.This research program tackles technical challenges for developing and applying millimeter-scale data loggers with improved information processing and visualization. The program aims to build a 50 mg millimeter-scale mSAIL device that 1) simultaneously measures light intensity, temperature, air pressure, and acceleration, 2) stores the recorded data in non-volatile memory, and 3) wirelessly communicates collected data. An integrated, chip-size battery will support device operation for one month and an energy-harvesting photovoltaic cell will provide essentially perpetual operation with as little as 500 lux light level. Using mSAIL, increasingly complex datasets that simultaneously document animal behavior and environment will be acquired from an expanded repertoire of species, down to those of sub-gram weight. mSAIL will spur cross-disciplinary collaborations to address a range of problems including the impact of anthropogenic environmental change (e.g. light pollution) on wildlife and the long-range migration of small animals such as monarch butterflies. This award is co-funded with support from the Animal Behavior Program in the Division of Integrative Organismal Systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
Migrating Monarch Butterfly Localization Using Multi-Modal Sensor Fusion Neural Networks
使用多模态传感器融合神经网络迁移帝王蝶定位
DOI:
10.23919/eusipco47968.2020.9287842
发表时间:
2021
期刊:
2020 28th European Signal Processing Conference (EUSIPCO
影响因子:
--
作者:
[Yang, Mingyu, Hsiao, Roger, Carichner, Gordy, Ernst, Katherine, Lim, Jaechan, Green, Delbert A., Lee, Inhee, Blaauw, David, Kim, Hun-Seok]
通讯作者:
Kim, Hun-Seok
NSF Postdoctoral Fellowship in Biology FY 2015
-
批准号:1523759
-
项目类别:Fellowship Award
-
资助金额:$20.7万
-
财政年份:2015
-
负责人:Delbert Green
-
依托单位:
国内基金
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