# May the Extensive Farming System of Small Ruminants Be Smart?
## 1 Introduction  
Livestock management practices that rely solely on farmers' observations, judgment, and experience may not meet the requirements of modern livestock farming. Therefore,precision agriculture, with the support of information technologies, has become an inevitable innovation in contemporary breeding. Due to the urgent need to integrate new technologies, artificial intelligence, and innovative animal husbandry development, the livestock industry is rapidly advancing toward a new era of fusion-integrated innovation [1]. Digitalisation has become an integral part of animal husbandry production and refers to various innovations such as automated milking systems, sensor technology, and electronic data processing. In recent years, the research on \"Precision Livestock Farming\" (PLF) has made significant progress in improving the economic, environmental, and social sustainability of livestock production [2; 3]. PLF is a multidisciplinary concept that describes a complex of sensor technology, algorithms, and applications for gathering information to enhance both the production system as well as the welfare and health of the animal and the environment [4; 5; 6]. The interaction of sensors and information technologies facilitates farm management, allowing for fewer veterinary interventions, behavioural identification in real time, feeding and reproduction optimisation, and lots of data available for the evaluation of the productive and reproductive conditions of individual animals, their physiological states, and environmental factors [7]. Intelligent systems could be used to monitor climate change-related factors, such as temperature, humidity, and emissions [3], or to improve grazing animal management and water use, contributing to more sustainable practices in response to large fluctuations in weather patterns [8]. Highly productive animals are more susceptible to heat stress; on the contrary, local and more rustic populations are more resilient to harsh climates thanks to different morphological and genetic adaptations to their developed environments [9]. PLF provides farmers with objective and continuous data collection directly on smartphones and computers, making it possible to improve management by promptly correcting one or more production inputs, the early recognition of diseases, and the monitoring of changes in animal behaviour. The application of PLF technologies has been most developed in dairy cows, considered high-value animals, to be monitored in various aspects, such as physiological [4], reproductive, behavioural, and productive aspects [10]. PLF technologies can provide crucial information on calf growth and health status, addressing increasing concerns for the welfare of young animals. Monitoring devices and sensors in cattle farming enable real-time livestock health and location monitoring and improve animal welfare [11; 12]. In recent years, various technologies have been developed to measure and predict animal body parameters to improve the maintenance of health and to maximise production efficiency--boluses, collars, radio frequency identification device (RFID) tags, noseband sensors, camera analysis models for position detection and methane emission estimation, and sound analysis systems for dairy production [12; 13; 14]--in dairy goats [15; 16], cow [5], poultry [17], and pigs [18]. Integrating intelligent technologies based on artificial intelligence (AI) and machine learning (ML) has transformed the beef and dairy cattle sector. The evolution of equipment, sensor technology, and new algorithms has enabled animal management and welfare optimisation, identifying anomalies, minimising risks, and maximising productivity [12; 13; 14]. The use of new technologies helps increase transparency and traceability, thus promoting customer trust and improving food safety measures [18]. The central sheep farming regions are Australia, South America, New Zealand, Northern Europe, and Asia.