
Research Article
Efficient Estimation of Cow’s Location Using Machine Learning Based on Sensor Data
@INPROCEEDINGS{10.1007/978-3-031-29126-5_7, author={Tomohide Sawada and Tom Uchino and Niken P. Martono and Hayato Ohwada}, title={Efficient Estimation of Cow’s Location Using Machine Learning Based on Sensor Data}, proceedings={Artificial Intelligence for Communications and Networks. 4th EAI International Conference, AICON 2022, Hiroshima, Japan, November 30 - December 1, 2022, Proceedings}, proceedings_a={AICON}, year={2023}, month={3}, keywords={Indoor localization Machine learning Sensor data Farm management Cow location}, doi={10.1007/978-3-031-29126-5_7} }
- Tomohide Sawada
Tom Uchino
Niken P. Martono
Hayato Ohwada
Year: 2023
Efficient Estimation of Cow’s Location Using Machine Learning Based on Sensor Data
AICON
Springer
DOI: 10.1007/978-3-031-29126-5_7
Abstract
Indoor localization of dairy cows is important for determining cow behavior and enabling an effective farm management. In this study, a low-cost localization system was constructed by attaching accelerometers to dairy cows kept indoors in a barn in order to obtain radio wave strength. Using link quality indicator (LQI) data, we employed four machine learning models to predict the position of the cow: LightGBM, logistic regression, support vector machine (SVM), and neural network. The prediction performance and computational cost of the models were compared and evaluated. In the monitoring and building of the prediction models for cow’s location, we considered various sizes of location (barn) compartments and evaluated the performance of each prediction model using with different compartments. The experimental results showed that LightGBM and neural networks have an accuracy of 46.6% at 9 m horizontal and 12 m vertical and an accuracy of 90% at 45 m horizontal and 15 m vertical. In terms of the computational score, we may consider whether to use neural network or LightGBM depending on the amount of data to be predicted at a time in the location estimation system.