Filippo Bonora
Papers
1
Total Citations
23
H-Index
1
About
Filippo Bonora is a researcher whose work sits at the intersection of precision livestock farming and data-driven agricultural management. His primary research focus is on the application of advanced modeling techniques—particularly cluster-graph models—to improve herd characterization and welfare in dairy operations equipped with automatic milking systems. His most-cited paper, "A cluster-graph model for herd characterisation in dairy farms equipped with an automatic milking system" (2018, 23 citations), represents a significant contribution to the field by offering a novel framework for analyzing complex behavioral and productivity data from automated systems. This work helps farmers and veterinarians identify distinct herd subgroups, enabling more targeted management interventions. Bonora’s impact is evident in how his model bridges the gap between raw sensor data and actionable insights, a critical step toward sustainable, high-efficiency dairy farming. Beyond this flagship study, his broader research portfolio explores the integration of IoT and machine learning in livestock environments, positioning him as a key figure in the digital transformation of agriculture. For students and researchers, Bonora’s work exemplifies how computational tools can solve real-world challenges in animal science.
Research Focus
Key Achievements
Top Papers
- 1