International Journal of Molecular Zoology, 2024, Vol.14, No.6, 326-333 http://animalscipublisher.com/index.php/ijmz 332 between devices and stakeholders (Farooq et al., 2022). Collaborative security models are also necessary to address data privacy and security concerns. Training and capacity building are critical to ensure that farmers can effectively utilize smart technologies. Providing education and resources to farmers will enable them to integrate these technologies into their daily operations, thereby improving livestock management and productivity (Caria et al., 2019). 7.3 Policy and collaborative frameworks Government support through policies and incentives can accelerate the adoption of smart livestock monitoring technologies. This includes funding for research and development, subsidies for technology adoption, and the establishment of regulatory frameworks that support innovation. Collaborations between industry and academia are vital for advancing research and development in smart livestock monitoring. These partnerships can drive innovation, facilitate knowledge exchange, and lead to the development of cutting-edge technologies that address current challenges in livestock health monitoring (Neethirajan, 2019). Global initiatives aimed at standardizing the use of smart sensors in livestock monitoring can ensure consistency and interoperability across different systems. Such initiatives can also promote best practices and facilitate the global exchange of knowledge and technology (Neethirajan, 2017). Acknowledgments We are grateful to Mrs. Guo for critically reading the manuscript and providing helpful comments that improved the clarity of the text. Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Arshad J., Rehman A., Othman M., Ahmad M., Tariq H., Khalid M., Moosa M., Shafiq M., and Hamam H., 2022, Deployment of wireless sensor network and IoT platform to implement an intelligent animal monitoring system, Sustainability, 14(10): 6249. https://doi.org/10.3390/su14106249 Behjati M., Noh A., Alobaidy H., Zulkifley M., Nordin R., and Abdullah N., 2021, LoRa Communications as an enabler for internet of drones towards large-scale livestock monitoring in rural farms, Sensors, 21(15): 5044. https://doi.org/10.3390/s21155044 Caria M., Sara G., Todde G., Polese M., and Pazzona A., 2019, Exploring smart glasses for augmented reality: a valuable and integrative tool in precision livestock farming, Animals, 9(11): 903. https://doi.org/10.3390/ani9110903 Chen T., 2024, Artificial intelligence and drug design: future prospects and ethical considerations, Computational Molecular Biology, 14(1): 9-19. https://doi.org/10.5376/cmb.2024.14.0002 Church J., and Bork E., 2023, 66 Emerging precision ranching technology is enabling the development of a “smart” biome, Journal of Animal Science, 101(Supplement_3): 140-141. https://doi.org/10.1093/jas/skad281.171 Džermeikaitė K., Bačėninaitė D., and Antanaitis R., 2023, Innovations in cattle farming: application of innovative technologies and sensors in the diagnosis of diseases, Animals, 13(5): 780. https://doi.org/10.3390/ani13050780 Farooq M., Sohail O., Abid A., and Rasheed S., 2022, A survey on the role of iot in agriculture for the implementation of smart livestock environment, IEEE Access, 10: 9483-9505. https://doi.org/10.1109/ACCESS.2022.3142848 Go A., Reyes B., Lii J., Alipio M., Hall S., and Evanoso J., 2022, A taxonomy of intelligent wearable devices and biosensors for cattle health monitoring, 2022 37th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC), IEEE, 2022: 403-406. https://doi.org/10.1109/ITC-CSCC55581.2022.9895086 Halachmi I., Guarino M., Bewley J., and Pastell M., 2019, Smart animal agriculture: application of real-time sensors to improve animal well-being and production, Annual Review of Animal Biosciences, 7: 403-425. https://doi.org/10.1146/annurev-animal-020518-114851 Huang J., and Lin X.F., 2024, Advances in animal disease resistance research: discoveries of genetic markers for disease resistance in cattle through GWAS, Bioscience Evidence, 14(1): 24-31. https://doi.org/10.5376/be.2024.14.0004
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