Dairy farms worldwide are increasing in size. This makes the health monitoring of individual cows and the timely detection of anomalies a very labour-intensive task, leading to significant additional costs for the farmer. To manage the intensification of livestock production in an economically efficient way, the modern dairy farms have to rely on automated systems for the collection and the interpretation of animal behavioural data. The accurate interpretation of the sensors’ data is able to provide a profound knowledge of the health and welfare status of the animals. Currently available research focuses on one specific aspect of animal welfare by monitoring few parameters (e.g., body temperature sensor for calving, accelerometer for oestrus). Meanwhile, the increasing availability of positioning systems for constrained devices unlock the potential of using location data for the benefit of cow and farmer. Therefore, as a first objective, this research proposal aims to design algorithms for calving, lameness, and oestrus in dairy cows using a combination of accelerometer and localisation sensors. The second objective investigates the feasibility of real-time in-body data collection. Therefore, I intend to characterise the in-to-out body wireless communication link between a sensor in the cow’s body and a nearby gateway to assess the signal power loss and the required energy budget to realise a reliable collection of in-body data.