Sensor based disease detection: A case study using accelerometers to recognize symptoms of Bovine Ephemeral Fever

Abstract

Bovine Ephemeral Fever affects livestock across Africa, Asia, and Australia with symptoms of fever, lameness, and inappetence. Currently, cattle producers must visually observe symptoms to detect Bovine Ephemeral Fever. The aim of this study is to determine the potential for accelerometer sensors deployed on the animal to identify when cattle are becoming ill with Bovine Ephemeral Fever. Two of 8 heifers fitted with 3-axis accelerometers became ill and were diagnosed with Bovine Ephemeral Fever by a veterinarian. Movement intensity was calculated from the x, y, z axes of the accelerometer readings recorded at 25 Hz and then averaged into 1-hour epochs. Accelerometer data from the two heifers that became ill were compared to three different sets of two randomly selected healthy heifers 2 days before and during the 24-hours before the onset of visually observable symptoms. Movement intensity of diagnosed heifers was lower (P ≤ 0.01) during the 24-hours before the symptoms were observed compared control heifers and levels observed 2 days before diagnosis. Accelerometers provided a clear signal that heifers were becoming ill before symptoms were observed by the manager and before diagnosis by a veterinarian. This case study shows that on-animal accelerometer sensors have the potential to remotely detect a disease such as Bovine Ephemeral Fever.