Sensors and Automation for Precision Livestock
A.Y. 2022/2023
Learning objectives
Providing an in-depth knowledge of the main sensor systems and automation solutions that can potentially be implemented in a livestock farms. Within case studies developed in the integrated course of "Precision livestock farming", acquiring methods and competences for extracting, analyzing and interpreting data generated by sensor systems to optimize the breeding management in a precision livestock farming perspective.
Expected learning outcomes
Ability to evaluate the introduction of precision livestock farming systems in different productive contexts, from the individual sensors to an integrated precision farming management system.
Acquisition of a method for extracting, analyzing and interpreting data generated by sensor systems.
Acquisition of a method for extracting, analyzing and interpreting data generated by sensor systems.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Course syllabus
First part
Description and operating principles of the main sensors used in Precision Livestock Farming systems.
· Practical applications of sensors: operating, installation, output signals. Interconnection and data bus.
· Microcontroller and automation systems.
· Electric, pneumatic, hydraulic actuators: operating, applications and automatic control.
Second part
The technologies and the basic principles of the Precision Livestock Farming applied to bovine herds
· The on-board sensors of automatic milking systems (AMS) and automatic feeding systems (AFS). Collection and
analysis of the data recorded through farm information systems.
· The birth alarm systems: typologies, operating principles, elements of operational choices. Application examples
· Indoor (in the barn) and outdoor (for grazing) animal positioning systems. Examples.
Third part
The main categories of optical instruments available on the market for "Precision Livestock Farming" applications. Knowledge of the main multivariate data processing techniques.
Topics discussed:
· Interaction of the electromagnetic radiation with matter. Optical properties of agricultural products. Vibrational
spectroscopy. Absorption bands of the spectrum in the visible and near infrared range (vis/NIR).
· Instrumentation analysis (vis/NIR spectroscopy, image analysis and hyperspectral imaging, thermal imaging).
Bench top and portable instruments.
· Spectra interpretation. Data pretreatments. Exploratory analysis of multivariate data: principal components
analysis (PCA). Data modeling: qualitative classification models and quantitative predictive models. Model
calibration and validation. Practical exercises of data analysis using specific software.
· Analysis of real case studies.
The program is the same for attending and non-attending students.
Description and operating principles of the main sensors used in Precision Livestock Farming systems.
· Practical applications of sensors: operating, installation, output signals. Interconnection and data bus.
· Microcontroller and automation systems.
· Electric, pneumatic, hydraulic actuators: operating, applications and automatic control.
Second part
The technologies and the basic principles of the Precision Livestock Farming applied to bovine herds
· The on-board sensors of automatic milking systems (AMS) and automatic feeding systems (AFS). Collection and
analysis of the data recorded through farm information systems.
· The birth alarm systems: typologies, operating principles, elements of operational choices. Application examples
· Indoor (in the barn) and outdoor (for grazing) animal positioning systems. Examples.
Third part
The main categories of optical instruments available on the market for "Precision Livestock Farming" applications. Knowledge of the main multivariate data processing techniques.
Topics discussed:
· Interaction of the electromagnetic radiation with matter. Optical properties of agricultural products. Vibrational
spectroscopy. Absorption bands of the spectrum in the visible and near infrared range (vis/NIR).
· Instrumentation analysis (vis/NIR spectroscopy, image analysis and hyperspectral imaging, thermal imaging).
Bench top and portable instruments.
· Spectra interpretation. Data pretreatments. Exploratory analysis of multivariate data: principal components
analysis (PCA). Data modeling: qualitative classification models and quantitative predictive models. Model
calibration and validation. Practical exercises of data analysis using specific software.
· Analysis of real case studies.
The program is the same for attending and non-attending students.
Prerequisites for admission
The course requires basic mathematical and statistical knowledge to face the crucial aspects of the theory and of the described instrumentation. These prerequisites are the same for attending and non-attending students.
Teaching methods
The teaching methods consist of:
a) frontal lesson
b) classroom exercises also with group work
c) field visits
The course does not have compulsory attendance, but it is strongly recommended the lessons participation.
a) frontal lesson
b) classroom exercises also with group work
c) field visits
The course does not have compulsory attendance, but it is strongly recommended the lessons participation.
Teaching Resources
Notes of the lessons published on the Ariel website
Monographic articles indicated during the lessons
The teaching material is the same for attending and non-attending students
Monographic articles indicated during the lessons
The teaching material is the same for attending and non-attending students
Assessment methods and Criteria
The exam consists of a unique oral interview concerning the arguments discussed during the course.
The exam mark will be based on:
- theoretical knowledge of the topics of the course;
- practical knowledge of the subject matter of the course:
- ability to speak technical language correlated with the course.
The final mark will be expressed in thirty.
The exam procedure is the same for non-attending students.
The exam mark will be based on:
- theoretical knowledge of the topics of the course;
- practical knowledge of the subject matter of the course:
- ability to speak technical language correlated with the course.
The final mark will be expressed in thirty.
The exam procedure is the same for non-attending students.
AGR/09 - AGRICULTURAL MACHINERY AND MECHANIZATION - University credits: 6
Lessons: 48 hours
Educational website(s)
Professor(s)
Reception:
by appointment only
Department of Agricultural and Environmental Sciences - via Celoria 2, Milano
Reception:
By appointment only
Department of Agricultural and Environmental Sciences - Agricultural Engineering area
Reception:
make an appointment
via Celoria 2 - Building 10: Ingegneria Agraria