IoT Technologies for Herd Management

Recently, the scientific community has shown increasing interest in the adoption of wearable sensors in intensive livestock systems for monitoring animals and, more generally, to improve the quality of production. In extensive livestock farming, the use of wearable sensors can be significantly useful, since in this type of breeding system there is an infrequent farmer-to-animal contact. Furthermore, extensive livestock systems generate various environmental impacts, among which the most significant concern greenhouse gas emissions and soil degradation. However, it is not easy to quantify and model the environmental impact of the extensive breeding systems, unlike intensive ones, as it is not possible continuous long-distance monitoring of the herd. A valid solution to the above reported issues could be provided by IoT technologies, which recently are becoming increasingly efficient and reliable. Cow location and tracking are crucial information to study environmental impacts of grazing cows. By analysing such data in a Geographical Information System (GIS), it is possible to have very useful information about the activities of animals around the grazing areas, the spatial heterogeneity of the areas occupied by the animals, the pasture utilization, and soil degradation. The aims of the present study were: to investigate, in an extensive livestock farm-ing, the feasibility of a locating and tracking system based on space–time data provided by a prototype of an IoT-based low-power global positioning system (LP-GPS); to test the battery life of the LP-GPS prototype and the signal coverage of the low-power network in rural locations; and to analyse the activities of animals around the considered grazing area by using GIS tool.