Biological rhythms are essential for life. There is evidence that the circadian rhythm of activity is disrupted under chronic stress. It may also be less marked during diseases. We investigated if we could detect a circadian rhythm of activity of dairy cow s in commercial settings using a real - time positioning system. We used the CowView (GEA Farm Technologies) to detect regularly the individual positions of 3 50 cows in a Danish dairy farm for five months , and to infer the cows’ activity ( resting , feed ing , standing, and walking ) from their position and their movements . We ran a factorial analysis of correspondence s of the cows’ activities and used t he 1 st component of this analysis to express the variations in activity . On this axis, the four activities obtained the following weights: resting, - .19; standing , +0.12; walking, +.26; and feeding, +.29. Applying these weights to the proportions of time each cow spent on each of the four activities, we could describe a circadian rhythm of a ctivity. We noticed that t he average level of activity of a cow on a given day and its variations during that day var ied with specific states: heat, lameness, disease. This offers the possibil ity to design models to predict physiological or pathological st ates of cows from real time positioning.