Special Issue "Technology and Engineering Solutions in Livestock Farming"
Deadline for manuscript submissions: 31 December 2021.
Interests: machine vision; artificial intelligence; precision livestock farming; robotics in agriculture
Special Issues, Collections and Topics in MDPI journals
Due to the increase in world population and market demand for meat and milk products, the scale of animal husbandry must increase. Therefore, addressing the issue of animal health and welfare becomes more essential for the farm owners as well as scientists. Precision livestock farming, as a management tool of livestock production for monitoring of animal health and behavior, and evaluating the environmental impact on livestock production and technology solutions to improve animal welfare has been increasingly utilized in recent years to support both commercial and research stakeholders in addressing these challenges. In this context, innovative technologies and techniques as well as machine learning and statistical models make it possible for a deeper understanding of precision livestock management systems which have led to the improvement of animal welfare and performance as well as sustainability. There has been some rapid advancements in sensor and low-cost technologies application in animal monitoring, data processing and optimization, disease, behavior and stress prediction in animal farming, indoor and outdoor reliable optical and non-optical based sensors application.
Therefore, the object of this Special Issue is to promote a deeper understanding of the latest findings in precision livestock farming research, engineering, and management solutions in all fields of livestock farming. We invite original research and review articles that cover a broad range of topics in livestock farming. The intention of this Special Issue is to focus on the most recent techniques in the research areas that include (but are not limited to):
- Technology application (e.g., camera, microphone, accelerometer, temperature, air quality sensors, etc.) in assessment/monitoring of behaviors, health and welfare of animals
- Application of artificial intelligence, machine learning, big data and statistical models in livestock farming
- Modeling and/or simulation of livestock barn and/or environmental conditions
- Investigation/analysis as well as modeling of nutritional status of animals
- Sensor fusion and signal processing
- Engineering-based methodology to develop advanced farm management systems
- Assessment of economic and environmental aspects associated with livestock farming management
Dr. Abozar Nasirahmadi
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Animals is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- livestock management
- artificial intelligence
- machine learning
- image and signal processing
- animal health and welfare
- big data
- digital technology