Sensor platform for real-time monitoring of animal health and welfare

The platform is integrating farm and (sub)clinical data and data obtained from individual animals using quantified animal technologies (for example wearable sensors) by employing data-driven modelling approaches, such as machine learning.

Monitoring dynamic energy consumption

In general, living things are very energy expensive. For example, the average energy consumed by one cow for one day is around 70 Mega Joules (19.4kWh » 5400 AA batteries), which is the same amount of energy needed to power a Tesla car for 100 km. This energy, which is the means for the animal to survive, is time-varying depending on many internal and external factors.

Hence, continuous monitoring of dynamic energy consumption is crucial for assessing the health, welfare, and productivity of animals.

Progress 2022

The researchers are working, in collaboration with KU Leuven University (Belgium), on developing a wearable sensor, called the EnergyTag, for real-time monitoring of animal’s (dairy cows and pigs) energy expenditure. The EnergyTag is a software sensor, which is a combination of hardware sensors, that measure for example temperature and heart rate, and an online estimation algorithm.

Progress September 2023: a soft-sensing platform for BRD

Bovine respiratory disease (BRD) is the most common cause of morbidity and mortality in cattle around the world, causing significant health problems (leading to mortality and low productivity) in all cattle husbandry systems. BRD is a multifactorial syndrome, with various predisposing factors (stressors) required to induce disease and affect disease severity. Hence, the BRD-related progression outcome is farm-dependent if not individual-dependent as well.

The researchers are developing a soft-sensing platform for predicting bovine respiratory diseased (BRD) related severity and mortality.