Digital agriculture or Agriculture 4.0 is the emerging international paradigm for crop and livestock farming, which is distinguished from previous models by the degree to which information and communication technologies (ICT) are integrated into traditional agricultural practices. Technologies such as Remote Sensing, Internet of Things (IoT), Unmanned Aerial Vehicles (UAVs), Big Data Analytics (BDA) and Machine Learning (ML) are particularly promising and can bring about a new shift in agricultural practices.
Agronomists and field technicians are the main actors and users of these technologies and need reliable and timely information in order to be able to acquire more decision-making elements, useful for the elaboration of the most correct and effective field strategies.
This course intends to increase the level of training on the technologies and digital skills necessary for the entire agricultural and technical chain to be able to act in the smart farming context, bringing positive developments to the agronomic and technical-economic management of the entire farm.
The Course presents the following main contents:
1) To know the phases of a Project for the digitisation of processing systems and management processes of the Agricultural Enterprise
2) To be able to recognise digital solutions that can be applied to different processes, to improve productivity and make efficient use of resources in agriculture
3) To evaluate cost-benefit issues in digitalisation of agriculture processes.
4) To know how to outline the priorities to implement a digitisation system for the agricultural enterprise, in line with the policies and regulatory framework of the European Union (Green Deal, From Farm to Fork, etc.) and the financial support for agricultural innovation, at European and national level (PNRR National Recovery and Resilience Plan in Italy and equivalent in the other EU countries).Learning Outcomes
The main learning outcomes of the course are:
1. ability to distinguish between a mechanical system and a digital system applied to agriculture
2. ability to define the result to be achieved by applying the digital system to a given agricultural process
3. ability to identify (or be able to interact with ITC technicians to select) digital technologies consistent with the result to be achieved
4. knowledge and ability to delineate a cause-effect relationship between data collected (data analysis, from micro-data to decision-making)
5. ability to identify strengths and weaknesses in the application of digital techniques for agriculture