A design of a smart farm system for cattle monitoring

Abstract

<span>The integration of technology in agriculture has led to the adoption of smart farming systems, which are becoming increasingly popular for optimizing resources, reducing labor costs, and improving efficiency. This article presents a design of a smart cattle monitoring farm system, which focuses on monitoring individual animal behavior and health, improving resource management, and optimizing overall farm efficiency. The proposed system integrates various internet of things (IoT) sensors, communication technologies, and cloud computing to provide a real-time monitoring solution <span>for cattle farms. The system uses machine learning (ML) algorithms to analyze data on cattle behavior, health, and performance, which can be accessed through web and mobile applications by farmers to proactively monitor their herd. The adoption of the system promises good results for intelligently transforming traditional cattle farming by reducing manual monitoring time and achieving a good accuracy in early detection of diseases, automated tracking of estrus cycles, and location mapping of cattle across the farm fields.</span></span>

A comparative study on time series data-based artificial intelligence approaches for classifying cattle feeding behavior

“…Furthermore, there is a growing trend in the use of internet of things (IoT) sensors and wireless networks for real-time data transmission, ensuring that data acquisition and analysis become more immediate and streamlined [5]. As these sensor technologies continue to evolve, they promise to further empower researchers to comprehensively study and understand cattle behavior, ultimately contributing to improved livestock management practices and better overall productivity [6]. Time-series data, in the context of cattle feeding behavior analysis, possesses unique properties that demand specialized Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752  classification techniques [7].…”