Development of a Smart Sensor for Real-Time Monitoring of Dairy Calves

Description

Calf health is a major concern for the Quebec dairy industry. Respiratory and digestive diseases are the leading causes of morbidity, resulting in significant economic losses due to costly veterinary treatments, growth delays, and long-term negative impacts on animal performance.

Early detection of these diseases remains a challenge, as it still relies heavily on human observation, which is time-consuming and prone to error. Technologies such as automatic milk feeders (AMF) and accelerometers have shown promising potential, but no integrated, operational solution is currently available for producers.

Objective of the PhD Project:

This project aims to develop a new multifunctional ear sensor capable of real-time measurement of:

Activity (via embedded accelerometer)

Temperature (via infrared sensor oriented toward the inner ear)

This sensor will be used in combination with data from automatic milk feeders. Integrating all these data into artificial intelligence (AI) models will enable faster and more accurate detection of early signs of respiratory and digestive diseases in calves.

The ultimate goal is to design a practical, robust, and non-invasive solution that can be directly implemented under commercial conditions, helping to reduce antibiotic use, improve animal welfare, and minimize economic losses on dairy farms.

Scientific and Technological Challenges:

This project offers a unique opportunity to work on cutting-edge problems, including:

Hardware and embedded development: miniaturization of a multifunctional sensor (< 15 grams), real-time data transmission (Bluetooth/IoT), energy autonomy.

Signal processing and sensor data analysis: analysis of multivariate time series (activity, temperature, AMF data).

Applied artificial intelligence: development of robust models for early detection of health anomalies.

Field validation: deployment and testing of the system on commercial farms under real-world conditions.

What We Offer:

Competitive PhD funding for 4 years.

Access to a highly innovative project with a strong impact on the agri-food industry.

The opportunity to work with a unique sensor prototype and validate your research directly in the field.

Integration into a dynamic, multidisciplinary team (engineers, computer scientists, animal scientists, veterinarians).

Collaborations with industrial partners and opportunities for scientific dissemination (conferences, publications).

This PhD project is a collaboration between Professors Éric Paquet (https://paquetlab.fsaa.ulaval.ca/) and Benoit Gosselin (https://biomicrosystems.ca/).

Requirements and Conditions

We are looking for a motivated, creative, and rigorous candidate with:
- A Master's degree in computer science, computer engineering, electrical engineering, data science, or a related field.
- Skills in embedded systems development, electronics, or IoT (C/C++, Python, Arduino/ESP32, etc.) OR in machine learning and sensor data processing.
- A strong interest in real-world applications of AI and engineering for sustainable agriculture.
- Autonomy, initiative, and a willingness to work in a multidisciplinary environment (engineering, AI, animal sciences).

Application Deadline

September 26, 2025