Task 4

Smart dairy farming: innovative solutions to improve herd productivity

Task 4 - Automatic oestrus detection

The identification of the fertile period of dairy cows is an increasingly pressing need for farmers who are often required to recognize visually the optimal time to subject the animal to artificial insemination, the failure of which entails significant economic losses for the farm. Together with the analysis of other physiological parameters, the identification of the estrous phase can take place by monitoring the activity of dairy cows since it generally undergoes a significant increase. The aim of the project is to develop an automatic prototype system for the detection of estrus based on wearable sensors installed in collars and podometers. The climatic parameters of the barn environment will be measured in order to relate the estrous phase with the possible onset of heat stress.

The experimental activities will be carried out at a livestock farm located in the province of Ragusa, Sicily.

The specific objectives and the activities in which the task is divided are:

  1. hardware design of the automatic monitoring system through the development of fixed devices for the detection of environmental data, and mobile devices (collars and podometers) for the detection of behavioral data.
  2. design, modeling and 3D printing of casings, specially designed for the functioning of the devices in the barn.
  3. implementation of an estrus detection software through the processing of data acquired from mobile devices aimed at the development of a decision support system for the management of cows during estrus events.
  4. implementation of a software for detecting microclimatic conditions by processing the data acquired from fixed devices aimed at developing a decision support system for the management of cows in environmental conditions of heat stress.
  5. validation and comparison: the reliability of the system developed will be validated through diagnostic tests conducted in situ and the performance will be compared with current systems on the market.


The project is funded within the scope of Research Projects of relevant National Interest - Call for Proposals 2017