How close is close enough? Calibrating and validating RSSI-based proximity sensors for livestock social interaction studies
Abstract
Abstract Background Understanding social contacts in livestock is essential for behavioural research, welfare assessment and modelling pathogen transmission. Proximity sensors based on received signal strength indicator (RSSI) offer a promising tool to quantify fine-scale social interactions in the context of precision livestock farming, but their performance depends strongly on environmental conditions and sensor configuration, requiring careful calibration and validation. In this study, we calibrated and validated commercially available RSSI-based proximity sensors under controlled indoor and outdoor conditions and through in vivo trials with sheep. Results Calibration experiments conducted across distances ranging from 0.5 to 5 m showed a predictable decrease in RSSI with increasing distance, modulated by environmental setting and sensor orientation, with both factors significantly influencing signal attenuation. Probability-based modelling demonstrated that RSSI reliably predicts biologically relevant proximity thresholds (≤ 0.5, 1.0 and 1.5 m), supporting the derivation of context-specific RSSI cut-offs rather than universal thresholds. The in vivo validation, combining proximity sensor data with image-based distance measurements matched to each individual RSSI detection event, demonstrated an overall classification accuracy of 82%, with per-class F1-scores ranging from 0.76 for distances greater than 1.5 m to 0.86 for distances of 1 m or less. Conclusions When appropriately calibrated, RSSI-based proximity sensors can reliably detect biologically meaningful social interactions in sheep across a range of inter-individual distances. These findings support the use of proximity sensing as a precision livestock farming tool for the study of social behaviour, welfare assessment, management and contact-based disease processes.
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Authors: Edoardo Fiorilla, Marco Pittarello, Clara Bordin, Marco Cianchetti, Stefano Nurisso, Giovanni Perona, Achille Schiavone, Laura Ozella
Institutions: University of Turin, Foro Italico University of Rome