Welcome to Brainless Intelligence Blog! This week we will discuss the Agriculture sector and in this blog we will focus the main implementations Artificial Intelligence has in Precision Livestock Farming. The farming industry has difficulties with enormous demands for production. However, the farmer’s main factor and concern before producing animal products is the health and welfare of the animal (Spain et al., 2018). The usage of digital technologies in farming, such as Artificial Intelligence (AI), is becoming more common to monitor livestock health and ease the job for the farmers (Neethirajan, 2020a). The main question is what Precision Livestock Farming (PLF) is and how Artificial Intelligence can become a new future to help farmers monitor and deliver improved results. Precision Livestock Farming with Artificial Intelligence uses sensors and specific models that allow automatic and continuous data collection, processing, and analysis to monitor the animals (Neethirajan, 2020b). Farm animals with this technology are monitored 24/7. Comparative data can be collected to monitor animal growth, production, and behaviour. Any physical or environmental parameters are collected and accessible to the farmer at any time (Halachmi and Guarino, 2016). Image Source: https://www.sciencedirect.com/science/article/pii/S2214180421000131#f0020 (Neethirajan and Kemp, 2021). Any triggered warnings can prevent disease or injury, improve production, and increase efficiency (Neethirajan and Kemp, 2021). The sensors, where the data is collected of the animal, can trigger the warning, and alarm the owner at early stages, sounds, images, and scanners can inform and allow the tracking of the animal’s activities, behaviour, location, any supplemented dietary and sleep cycles can be tracked remotely (Norton et al., 2019). The main objective of using Artificial Intelligence in Precision Livestock Farming is that crucial decisions can be made based on the data and feedback that humans can miss with their eyes. Applications where Artificial Intelligence applied: Artificial Intelligence can generate algorithms and examine animal body language to observe the emotional and mental state of an animal, this can prevent the early stages of diseases or sufferings of pain an animal can unexpectedly experience. (Neethirajan and Kemp, 2021). Artificial Intelligence with GPS and WSN tracking systems allows farmers to identify the location of their livestock in the grazing areas and will enable them to track the patterns and behaviours of the animal. The tracking system additionally is helpful to pinpoint which of the animal had close contact with sick livestock, and it can save and prevent any loss and any further spread of disease (Park and Park, 2020). Artificial Intelligence helps to understand and develop the growth of livestock. It gives insights into the very early stage to adult animals. The system uses sensors and data to establish the animal's observation traits, recorded and used to plan for animal development and manage the production cycles. Observations can prevent the damaging behaviours of the animals on the farm and improve the livestock’s welfare. Artificial Intelligence uses sensors, and farmers can design solutions to avoid detrimental actions. Farmers can use stimulations to check and predict their livestock behaviour which can be a valuable tool to improve the farm or provide deep insight into the reactions of sudden change or larger population. This advancement of Artificial Intelligence allows farmers to compare actual and virtual responses and livestock behaviours (Neethirajan and Kepm, 2021). Image Source: https://www.pashudhanpraharee.com/application-of-artificial-intelligence-ai-for-livestock-poultry-farm-monitoring/ (Singh, 2019). Artificial Intelligence in Agriculture sector allows farmers to have more control and helps to manage the livestock easier, the growing demand requires to have high efficiency and high production, which with the technologies like AI can be achieved. Stay tuned and find out more about Artificial Intelligence in Agriculture this week. references:Halachmi, I. and Guarino, M. (2016). ‘Editorial: Precision livestock farming: a “per animal” approach using advanced monitoring technologies.' Available at: https://www.sciencedirect.com/science/article/pii/S1751731116001142?via%3Dihub [Accessed: 05 March2022]. Park, J. K. and Park, E. Y. (2020) “Animal Monitoring Scheme in Smart Farm using Cloud-Based System”, ECTI Transactions on Computer and Information Technology (ECTI-CIT), 15(1), pp. 24–33. Available at: https://ph01.tci-thaijo.org/index.php/ecticit/article/view/240087 [Accessed: 03 March 2022]. Neethirajan, S. (2020a). 'Transforming the adaptation physiology of farm animals through sensors'. Animals, 10 (9), pp. 1-24. Available at: https://www.mdpi.com/2076-2615/10/9/1512 [Accessed: 03 March 2022]. Neethirajan, S. (2020b). 'The role of sensors, big data and machine learning in modern animal farming. Sensing and Bio-Sensing Research', 100367, pp. 1-8. Available at: https://www.sciencedirect.com/science/article/pii/S2214180420301343 [Accessed: 05 March 2022]. Neethirajan, S. and Kemp, B. (2021) ‘Digital Livestock Farming’, Sensing and Bio-Sensing Research. Elsevier B.V., 32(February), p. 100408. Available at: https://www.sciencedirect.com/science/article/pii/S2214180421000131 [Accessed: 05 March 2022]. Norton. T, C. Chen, M.L.V. Larsen, D. Berchamans (2019). ‘Review: Precision livestock farming: Building “digital representations” to bring the animals closer to the farmer’, Animal. Elsevier, 13(12), pp. 3009–3017. Available at: https://www.sciencedirect.com/science/article/pii/S175173111900199X [Accessed: 03 March 2022]. Singh, R. (2019). 'Application of Artificial Intelligence (AI) for livestock poultry farm monitor.' Available at: https://www.pashudhanpraharee.com/application-of-artificial-intelligence-ai-for-livestock-poultry-farm-monitoring/ [Accessed: 05 March 2022]. Spain CV, Freund D, Mohan-Gibbons H, Meadow RG, Beacham L. (2018). 'Are They Buying It? United States Consumers' Changing Attitudes toward More Humanely Raised Meat, Eggs, and Dairy.' Animals (Basel). 2018;8(8):128. Available at:
https://pubmed.ncbi.nlm.nih.gov/30044402/ [Accessed: 04 March 2022].
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