Related papers: Time Series Classification to Improve Poultry Welf…
Poultry farms are a major contributor to the human food chain. However, around the world, there have been growing concerns about the quality of life for the livestock in poultry farms; and increasingly vocal demands for improved standards…
Poultry farming plays a pivotal role in addressing human food demand. Robots are emerging as promising tools in poultry farming, with the potential to address sustainability issues while meeting the increasing production needs and demand…
Automated cattle activity classification allows herders to continuously monitor the health and well-being of livestock, resulting in increased quality and quantity of beef and dairy products. In this paper, a sequential deep neural network…
Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations.…
Deciphering the acoustic language of chickens offers new opportunities in animal welfare and ecological informatics. Their subtle vocal signals encode health conditions, emotional states, and dynamic interactions within ecosystems.…
We apply genetic programming techniques to the `shepherding' problem, in which a group of one type of animal (sheep dogs) attempts to control the movements of a second group of animals (sheep) obeying flocking behavior. Our genetic…
Poultry farming faces increasing pressure to meet productivity targets while ensuring animal welfare and environmental compliance. Yet many small and medium-sized farms lack affordable, integrated tools for continuous monitoring and…
In recent years, there have been unprecedented technological advances in sensor technology, and sensors have become more affordable than ever. Thus, sensor-driven data collection is increasingly becoming an attractive and practical option…
Recent years have witnessed major advances in the ability of computerized systems to track the positions of animals as they move through large and unconstrained environments. These systems have so far been a great boon in the fields of…
Ecological and conservation studies monitoring bird communities typically rely on species classification based on bird vocalizations. Historically, this has been based on expert volunteers going into the field and making lists of the bird…
Time series analysis is a field of data science which is interested in analyzing sequences of numerical values ordered in time. Time series are particularly interesting because they allow us to visualize and understand the evolution of a…
Chicken well-being is important for ensuring food security and better nutrition for a growing global human population. In this research, we represent behavior and posture as a metric to measure chicken well-being. With the objective of…
Animal sounds can be recognised automatically by machine learning, and this has an important role to play in biodiversity monitoring. Yet despite increasingly impressive capabilities, bioacoustic species classifiers still exhibit imbalanced…
One of the interests of modern poultry farming is the vocalization of laying hens which contain very useful information on health behavior. This information is used as health and well-being indicators that help breeders better monitor…
Livestock feeding behaviour is an influential research area for those involved in animal husbandry and agriculture. In recent years, there has been a growing interest in automated systems for monitoring the behaviour of ruminants. Despite…
Birds are important indicators for monitoring both biodiversity and habitat health; they also play a crucial role in ecosystem management. Decline in bird populations can result in reduced eco-system services, including seed dispersal,…
The presence of smart objects is increasingly widespread and their ecosystem, also known as Internet of Things, is relevant in many different application scenarios. The huge amount of temporally annotated data produced by these smart…
Robotic shepherding problem considers the control and navigation of a group of coherent agents (e.g., a flock of bird or a fleet of drones) through the motion of an external robot, called shepherd. Machine learning based methods have…
Time-series classification has attracted considerable research attention due to the various domains where time-series data are observed, ranging from medicine to econometrics. Traditionally, the focus of time-series classification has been…
Time series data, defined by equally spaced points over time, is essential in fields like medicine, telecommunications, and energy. Analyzing it involves tasks such as classification, clustering, prototyping, and regression. Classification…