ICT tools for smart indoor farming

Max amount of FITech students: 20 adult learners

Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course.

This introductory course on Information and Communications Technologies (ICT) for smart indoor farming covers the key fundamentals of soilless agricultural practices, wireless connectivity of sensors and actuators, signal and information processing, and automation processes, which are relevant for the development of sustainable practices in future smart farms. The aim is to strengthen the “Vertical Farming” use case, providing to the participants the theoretical knowledge and practical skills that are needed to go beyond the State-of-the-Art in these smart farms to produce fresh good quality food in Argentina, Finland, and other countries in the rest of the world with similar geographical and demographical conditions. This course is part of the CITY-FARM project (Project No. 13/116/2022), which received funding from the Team Finland Knowledge (TFK) program funded by the Finnish National Agency for Education (FINE) to strengthen the collaboration in education between Finland and Latin America.

Course contents

The content of this course is divided into four different units, whose contents are expanded as follows:

Unit 1: Horticulture and Hydroponics. Generalities on hydroponic-based agricultural systems. Advantages and disadvantages with respect to traditional methods based on substrates (soil). Different types of hydroponic systems. Management of water and nutrients in soilless agriculture. Challenges in the automation of processes and in the use of artificial illumination. Lessons learnt in practical experiences carried out in Latin America and Europe.

Unit 2: Sensing and information processing. Commercial hardware and software for image processing in smart indoor farming. Examples of image processing algorithms to solve problems that are relevant to smart farming applications. Fundamentals of Artificial Intelligence (AI) for information processing in a smart farm. Sample implementation of simple Machine Learning (ML) algorithms for the classification of events in indoor smart farming.

Unit 3: Wireless communications and networking. Fundamentals of wireless communications. Short-range wireless communications (Bluetooth, Zigbee, RFID). Proprietary standards (LoRa) and 3GPP standards (LTE-M/NB-IoT) for the connectivity of IoT devices. Energy efficiency and energy saving in wireless communications. Visible Light Communications (VLC) for indoor smart farming: Challenges and potentials.

Unit 4: Automation and control. Fundamentals of distributed and event-driven control processes. Fundamentals of IEC 61499 standard. Automation processes in a smart farm. Use of Programmable Logic Controllers (PLC) in the automation processes of a smart farm. Closed-loop smart farming models as a cyber-physical system. Design of a control system for smart farming utilizing functional blocks of IEC 61499 standard.

Learning outcomes

At the end of the course, the student will be able to

• know the theoretical background of the ICT tools that are needed for the sensing, wireless connectivity, signal and information processing, and automation processing of the so-called “vertical farming” use case
• become aware of the fundamentals of soilless farming, identifying requirements and limitations of their implementation in indoor environments
• know the hardware and software tools that exist in the market for the implementation of the different modules of a vertical farm, combining them to improve production of fast growing vegetables in indoor environments
• identify an overall architecture of a vertical farm, with the needed control processes, to enable plants growing in environmental conditions found in Finland, Argentina, and other countries with similar conditions.

Course material

Course slides, short articles and recorded presentations. All this material will be distributed via MyCourses, the learning environment for Aalto University courses.

Teaching schedule

Lectures (afternoons) and onsite group work (mornings) from MON 10.6. to FRI 14.6. 9–18 (whole day).

Teaching will be held onsite in Otaniemi Campus of Aalto University on week 24 (10-14.6.). Content will be lectured in an intensive fashion, covering four hours of lectures per day 14–18. Group work will be held in the mornings 9–13.

Suoritustapa

Group project work, quizzes and learning diaries.

More information in the Aalto University study guide.

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