# May the Extensive Farming System of Small Ruminants Be Smart?
## 1 Introduction
These include developed countries with high concentrations of sheep raised with relatively traditional approaches compared to cattle: high feed costs, vulnerability to predation, animal health problems, and negative environmental impacts [12; 13; 14; 19]. Small ruminant farming occupies a significant place in the Italian agricultural landscape, and sheep and goats represent about 10% of the total ruminant population in Italy. They are mainly present in some marginal areas, and over the last five years, there has been a reduction in the number of small farms and livestock [12; 13; 14; 20]. The population has about five million sheep and nine hundred thousand goats. A notable decrease in the number of farms has been noted, particularly in small family-run farms [12; 13; 14; 20]. Traditional extensive or semi-extensive farming, although still the predominant type for sheep and goats, must face challenges such as the abandonment of less profitable activities, reductions in the number of pastures, and the crisis in the wool market [12; 13; 14; 21]. However, the structure of these farms has changed; large modernised farms are increasing in number, especially in the dairy sheep sector. A substantial part of the population of small ruminants, more than two-thirds, is mainly located in Sardinia [12; 13; 14; 20]. With improved Precision Livestock Farming (PLF) practices, farmers are encouraged to adopt digital solutions for their sheep farms. They aspire to maximise profits by optimising costs and revenues through improved animal welfare, which is directly linked to higher yields. [PERSON] et al. [12; 13; 14] have analysed that the development of new sensors is focused on optimising technologies with smaller device dimensions, improved data transfer capabilities, and lower energy consumption. Applying these tools to intensive systems has produced excellent results thanks to elements adapted to the needs of digitalisation. [PERSON] et al. [1; 16] have reported on these elements, including environmental conditions, information and communication technologies, and perimeter areas [1; 16]. Moreover, climate instability, consumer tastes, sustainable development goals, and production efficiency have also constrained all farmers [12; 13; 14; 21]. With reductions in water availability, climate change negatively affects the quantity and quality of pasture and the production of feed for livestock. The extensive sheep and goat sector has seen a decline in the ratio of animal care workers to the total number of animals. Consumers have shifted their dietary preferences to favour animal-based proteins, mainly beef and cheese [12; 13; 14; 22]. These challenges are even more pronounced in extensive mountain systems, where high altitudes, steep slopes, and significant climatic variations make access and animal monitoring difficult. Consequently, these factors prevent the routine implementation of PLF within the production process in extensive systems [12; 13; 14; 23]. However, [PERSON] et al. [1; 16; 24] have reported that the application of intelligent systems enables extensive sheep farmers to strengthen sales, the integration of digitalisation and artificial intelligence (AI) has improved particularly intensive sheep farming, with greater efficiency in production yield and animal health status. [PERSON] et al. [12; 13; 14; 19], in fact, have highlighted that the combination of sensors and artificial intelligence (AI) can detect animal welfare on farms and during transportation. With the development of new sensor technologies and infrastructure for data transfer, the gradual application of these systems in grazing animals is now possible [3; 25]. Extensive farmers prioritise grazing methods with low financial investment and relatively simple management, which provide economic resilience to market fluctuations.