Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Digitalization of Animal Farming

Version 1 : Received: 2 July 2020 / Approved: 3 July 2020 / Online: 3 July 2020 (12:29:39 CEST)

A peer-reviewed article of this Preprint also exists.

Neethirajan, S.; Kemp, B. Digital Livestock Farming. Sensing and Bio-Sensing Research, 2021, 32, 100408. Neethirajan, S.; Kemp, B. Digital Livestock Farming. Sensing and Bio-Sensing Research, 2021, 32, 100408.


As the global human population increases, animal agriculture must adapt to provide more animal products while also addressing concerns about animal welfare, environmental sustainability, and public health. The purpose of this review is to discuss the digitalization of animal farming with Precision Livestock Farming (PLF) technologies, specifically biosensors, big data, and block chain technology. Biosensors are noninvasive or invasive sensors that monitor an animal’s health and behavior in real time, allowing farmers to monitor individual animals and integrate this data for population-level analyses. The data from the sensors is processed using big data-processing techniques such as data modelling. These technologies use algorithms to sort through large, complex data sets to provide farmers with biologically relevant and usable data. Blockchain technology allows for traceability of animal products from farm to table, a key advantage in monitoring disease outbreaks and preventing related economic losses and food-related health pandemics. With these PLF technologies, animal agriculture can become more transparent and regain consumer trust. While the digitalization of animal farming has the potential to address a number of pressing concerns, these technologies are relatively new. The implementation of PLF technologies on farms will require increased collaboration between farmers, animal scientists, and engineers to ensure that technologies can be used in realistic, on-farm conditions. These technologies will call for data models that can sort through large amounts of data while accounting for specific variables and ensuring automation, accessibility, and accuracy of data. Issues with data privacy, security, and integration will need to be addressed before there can be multi-farm databases. Lastly, the usage of blockchain technology in animal agriculture is still in its infancy; blockchain technology has the potential to improve the traceability and transparency of animal products, but more research is needed to realize its full potential. The digitalization of animal farming can supply the necessary tools to provide sustainable animal products on a global scale.


Digitalization; sensor technology; block chain technology; data models; livestock


Engineering, Control and Systems Engineering

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