Name
Title | ||
|---|---|---|
Migrating Monarch Butterfly Localization Using Multi-Modal Sensor Fusion Neural Networks |
Abstract | ||
|---|---|---|
Details of Monarch butterfly migration from the U.S. to Mexico remain a mystery due to lack of a proper localization technology to accurately localize and track butterfly migration. In this paper, we propose a deep learning based butterfly localization algorithm that can estimate a butterfly's daily location by analyzing a light and temperature sensor data log continuously obtained from an ultra-low power, millimeter (mm)-scale sensor attached to the butterfly. To train and test the proposed neural network based multi-modal sensor fusion localization algorithm, we collected over 1500 days of real world sensor measurement data by 82 volunteers all over the U.S. The proposed algorithm exhibits a mean absolute error of < 1.7 degrees in latitude and < 0.6 degrees in longitude Earth coordinate, satisfying our target goal for the Monarch butterfly migration study. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.23919/Eusipco47968.2020.9287842 | 28TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2020) |
Keywords | DocType | ISSN |
light-level geolocation, Monarch migration, neural networks, maximum likelihood estimation | Conference | 2076-1465 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingyu Yang | 1 | 1 | 1.37 |
| Roger Hsiao | 2 | 0 | 0.34 |
| Gordy Carichner | 3 | 0 | 0.68 |
| Katherine Ernst | 4 | 0 | 0.34 |
| Jaechan Lim | 5 | 69 | 9.34 |
| Delbert A. Green II | 6 | 0 | 0.34 |
| Inhee Lee | 7 | 275 | 33.89 |
| David Blaauw | 8 | 8916 | 823.47 |
| Hun-Seok Kim | 9 | 294 | 27.15 |