  The development of precision livestock farming which adjusts the food needs
of each animal requires detailed knowledge of its behavior and particularly
physical activity. Individual differences between animals can be observed for
group-housed sows. Accelerometer technology offers opportunities for automatic
monitoring of animal behavior. The aim of the first step was to develop a
methodology to attach the accelerometer on the sow's leg, and an algorithm to
automatically detect standing and lying posture. Accelerometers (Hobo Pendant
G) were put in a metal case and fastened with two cable ties on the leg of 6
group-housed sows. The data loggers recorded the acceleration on one axis every
20 s. Data were then validated by 9 hours of direct observations. The automatic
recording device showed data of high sensitivity (98.8%) and specificity
(99.8%). Then, accelerometers were placed on 12 to 13 group-housed sows for 2
to 4 consecutive days in 6 commercial farms equipped with electronic sow
feeding. On average each day, sows spent 259 minutes ($\pm$ 114) standing and
changed posture 29 ($\pm$ 12) times. The sow's standing time was repeatable day
to day. Differences between sows and herds were significant. Based on
behavioral data, 5 categories of sows were identified. This study suggests that
the consideration of individual behavior of each animal would improve herd
management.
