Abstract
Precision livestock farming (PLF) refers to utilize sensors and IT management system in cyber-physical farm to introduce more intelligence in farming activities. PLF hardware including sensors as data capturing device and computer as data processing unit. PLF software is for connecting sensors, processing data and visualizing result in real-time. This technology can reduce human error, minimize the number of labours and providing evidence-based decision making. The software which connected to sensors should be flexible and easy to use, able to extend by allowing new type of sensors to be effectively integrated. Although many works have been done for PLF such as object recognition, tracking, weight measuring etc. [4, 5]. however, there still lacks a generic platform which could integrate various algorithms and providing instant information for shareholders. This paper will present the technology stack involved in developing the platform.
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Acknowledgment
This study is partially funded by the Knowledge Transfer Partnership (KTP) project (10798) from Innovate UK and Innovent Technology Ltd. in partnership with the University of Strathclyde to redesign the existing precision livestock farming system.
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Han, Y., Ren, J., Zhu, Q., Barclay, D., Windmill, J. (2020). IoT and Cloud Enabled Evidence-Based Smart Decision-Making Platform for Precision Livestock Farming. In: Ren, J., et al. Advances in Brain Inspired Cognitive Systems. BICS 2019. Lecture Notes in Computer Science(), vol 11691. Springer, Cham. https://doi.org/10.1007/978-3-030-39431-8_55
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