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- Hiroyuki Ito
- Creator
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- Ken-ichi Takeda
- Creator
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- Korkut Kaan Tokgoz
- Creator
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- Ludovico Minati
- Creator
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- Masamoto Fukawa
- Creator
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- Li Chao
- Creator
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- Jim Bartels
- Creator
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- Ikumi Rachi
- Creator
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- Sihan A
- Creator
Metadata
- Published
- 2021-09-24
- Size
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- v2.0.0
- DOI
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- 10.5281/zenodo.5399258
- 10.5281/zenodo.5399259
- 10.5281/zenodo.5849025
- Publisher
- Zenodo
- Creator Name (e-Rad)
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- Hiroyuki Ito
- Ken-ichi Takeda
- Korkut Kaan Tokgoz
- Ludovico Minati
- Masamoto Fukawa
- Li Chao
- Jim Bartels
- Ikumi Rachi
- Sihan A
Description
Licensed under:<br> Attribution-NonCommercial-NoDerivatives 4.0 International<br> https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode Japanese Black Beef Cow Behavior Classification Dataset This dataset contains tri-axial accelerometer sensor data with thirteen different labeled cow behaviors. This data was gathered with a 16bit +/- 2g Kionix KX122-1037 accelerometer attached to the neck of six different Japanese Black Beef Cows (`cow1.csv`-`cow6.csv`) at a cow farm of Shinshu University in Nagano, Japan on the 12th of June, 2020. The data gathering took place over the course of one day in which the cows were allowed to roam freely in two different areas, namely, a grass field and farm pens, while being filmed with Sony FDR-X3000 4K video cameras. The timestamps of the video and accelerometer data were matched while human observers which included behavior experts and non-experts labeled the data from the video footage. The labeling and data gathering took a total of 69 person-hours. 567 minutes of unlabeled data were parsed into 197 minutes of high-quality labeled data comprising thirteen behaviors by means of majority voting with three annotators. The time per behavior in number of samples (@25Hz) and their respective descriptions are shown in the following table: Cow 1 Cow 2 Cow 3 Cow 4 Cow 5 Cow 6 Description RES 35814 47059 20501 15735 11025 19996 Resting in standing position RUS 1620 25930 11156 14523 0 0 Ruminating in standing position MOV 6376 8437 7532 17248 4846 5760 Moving GRZ 2416 2199 0 2707 2442 7849 Grazing SLT 204 0 10654 0 0 0 Salt licking FES 6809 0 0 0 1125 0 Feeding in stanchion DRN 1176 0 1300 0 0 0 Drinking LCK 0 0 649 297 0 356 Licking REL 0 360 0 404 0 0 Resting in lying position URI 239 0 383 0 0 0 Urinating ATT 57 50 0 62 0 197 Attacking ESC 0 0 0 128 0 0 Escaping BMN 0 54 0 0 0 0 Being mounted ETC 105917 103084 129297 62064 53922 100571 Other behaviors BLN 151249 82599 88431 111744 61544 45128 Data without video, no label Sum 311876 269772 269903 224912 134904 179857 Accelerometer sampling rate was set to 25Hz. The data is split into six .csv files which represents each of the 6 cows above. The columns of these files are defined as follows: TimeStamp_UNIX [-] TimeStamp_JST [-] AccX [g] AccY [g] AccZ [g] Label [-] GPS timestamp in UNIX GPS timestamp in JST X-axis acceleration Y-axis acceleration z-axis acceleration labeled behavior The gathering of this data with these cows was reviewed and approved by the Institutional Animal Care and Use Committee of Shinshu University. Version History v1.0.0: Release on 24th of September, 2021. First version. v2.0.0: This version. UNIX and Japan Standard Time (JST) time stamps are added for each .csv file of cow1-6. Added explanations of behaviors for ETC and BLN. More information on publications that use this dataset, data logger software that has been developed for this project. Data logger open source software Software developed for the data logger that was used to gather this dataset, Sony's IoT development board SPRESENSE, CXD5602PWBMAIN1. The function of this data logger is to write inertia sensor data along with timestamps. Timestamp data is corrected with GPS signal. Available in Arduino development environment. https://zenodo.org/record/5848608#.YeFF9NHP3Z8 Publications using this dataset [1] Li, Chao, et al. "Data Augmentation for Inertial Sensor Data in CNNs for Cattle Behavior Classification." IEEE Sensors Letters 5.11 (2021): 1-4. [2] Bartels, Jim, et al. "A 216 microW, 87% Accurate Cow Behavior Classifying Decision Tree on FPGA With Interpolated Arctan2." 2021 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2021.