This course is designed for individuals who are interested in leveraging technology to solve practical problems in rural farming environments. It aims to equip participants with the knowledge and skills to implement IoT solutions effectively, thereby enhancing agricultural productivity and sustainability. The target audience for this course is the following:

1. Farmers and Agricultural Professionals: Individuals directly involved in farming or agricultural management who are looking to integrate modern technology into their practices to enhance productivity and efficiency.
2. Agricultural Technologists and Engineers: Professionals specializing in agricultural technology and engineering who seek to deepen their knowledge of IoT applications in agriculture for innovation and development purposes.
3. Agricultural Extensionists: Professionals who work directly with farmers and agricultural businesses to apply research and scientific knowledge to agricultural practices.
4. Policy Makers and Rural Development Planners: Those involved in rural development and planning, including government officials and policy makers, who aim to understand how IoT can be leveraged to improve agricultural practices and rural livelihoods.
5. Agricultural Students and Researchers: Students and academic researchers focusing on agriculture, technology, and related fields who are interested in exploring the potential of IoT in transforming rural agricultural practices.
6. Tech Entrepreneurs and Startups: Entrepreneurs and startup companies focusing on agricultural technology solutions who are looking for opportunities to develop and implement IoT-based products and services for the agricultural sector.
7. NGO and Community Leaders: Representatives from non-governmental organizations and community groups working in rural development and agricultural improvement who wish to learn about IoT applications to support their communities.

This is an intermediate course, basic knowledge of ICT technology, Internet and wireless technologies, including 4G/5G  mobile networks and general IoT knowledge is recommended but not mandatory, as the fundamental concepts of these points will be covered in a brief review manner. Also, an understanding of basic agricultural principles and practices is recommended, but not mandatory. This could be through formal education, work experience, or personal involvement in farming or agricultural activities.

Upon completion of this course, participants will be able to:

• Fundamental Principles of IoT: Describe the core concepts of the Internet of Things, including how devices communicate and interact within a network to collect and exchange data;
• Agricultural Applications of IoT: Discuss how IoT technologies can be applied to various aspects of agriculture, such as soil care, irrigation, crop management, livestock monitoring, and precision farming, to improve efficiency and productivity;
• Technological Components: Differentiate the sensors, devices, and platforms used in IoT systems, including their functionalities and how they can be applied in agricultural contexts;
• Connectivity and Communication Protocols: Compare with various communication technologies and protocols suitable for rural environments, ensuring reliable data transmission between devices and servers;
• Real-World Applications and Case Studies: Analyze successful IoT implementations in agriculture, including the challenges faced and solutions developed, providing a practical perspective on how IoT can be effectively utilized.

This course is based on a learning approach consisting of a number of pre-recorded videos with a duration of 15 to 20 minutes each and instructor moderation/interaction via the forum component of the course. The videos will be produced using the latest industry standards regarding the presentation and using embedded quizzes to prevent the “fast forwarding effect” and to engage learners and reinforce key concepts.

For the benefit of varying instructional methods, interactive presentations (Course Presentation) will also be used to deliver certain course contents to replace pre-recorded videos. In addition to those videos and interactive presentations, supplementary texts/articles/webpages will be provided, offering learners an opportunity to deepen their understanding and explore the topics covered in more detail. The texts will be chosen to complement the offered content and provide learners with additional insights and perspectives. This methodology is intended to provide a comprehensive and interactive learning experience, enabling learners to engage with the course material at their own pace and from different perspectives.

Also, a tutor will monitor the course forum weekly in order to answer questions, promote relevant discussions, challenges, questions and problems, in addition to publish news on the subject. The course tutor will also encourage the students to share national contexts, situations - as these would be beneficial for the other participants, encouraging social learning.

The assessment and grading methodology include an evaluation through multiple-choice tests for each of the three course modules, a final test and one open-ended question. Each test will contain five questions, each with four answer choices, with only one correct answer. The final test will contain ten questions, each with four choices, with only one correct answer. The questions will be designed at different levels of complexity, aiming to explore the topic covered in each course module. The open-ended question will be designed so that the participant demonstrates their knowledge and opinions on a relevant topic covered during the course.

In order to obtain the ITU digital badge, the participant must obtain at least 70 points out of 100 total points distributed on the course activities by the following way:

1. 3 Multiple choice quizzes. Total weight=30%.
2. 1 open ended question Total weight=30%
3. Course final test in a total of 10 questions. Total weight=40%;

Module 1 IoT Applications

1) Introduction to IoT in Agriculture

2) Precision Farming

3) Smart Irrigation Systems

4) Livestock Monitoring

Key learning points

1) Explain the application of IoT technologies in the agricultural sector, identifying both benefits and challenges.

2) List IoT techniques to monitor and manage variability in agricultural production, aiming to increase efficiency and productivity.

3) Describe IoT solutions to optimize water usage by analyzing soil moisture and weather data.

4) Utilize IoT devices for the health monitoring, tracking, and management of livestock to enhance animal welfare and farm productivity.

Training activities details

• Watch two 15-20 mim. videos

• Interact with two 15-20 mim. dynamic course presentation

• One extra suggested reading

• Take the MCQ knowledge test

• Contribute to the course forum

Module 2 IoT Technical aspects

1) Connectivity Solutions

2) IoT Devices and Sensors

3) IoT Platforms and Tools

4) Security and Privacy

Key learning points

1) Evaluate and select appropriate connectivity solutions, including communication protocols and network technologies like LoRaWAN and NB-IoT, for rural and agricultural environments.

2) Describe the range of IoT devices and sensors used in agriculture, such as soil moisture sensors, weather stations, and GPS trackers, and their applications.

3) Explain the functionalities of various IoT platforms and tools, including cloud-based solutions and edge computing, for managing IoT devices and data in agriculture.

4) Evaluate the security challenges and the best practices for protecting data and devices in IoT agricultural systems.

Training activities details

• Watch two 15-20 mim. videos

• Interact with two 15-20 mim. dynamic course presentation

• One extra suggested reading

• Take the MCQ knowledge test

• Contribute to the course forum

Module 3 IoT application real use cases

1) Case Studies

2) Lessons Learned

3) Innovative and Future Trends

Key learning points

1) Analyze case studies of successful IoT implementations in rural agriculture, focusing on objectives, processes, challenges, and outcomes to understand their impact.

2) Identify and summarize lessons learned from real-world experiences, including common pitfalls and best practices, for deploying IoT solutions in rural settings.

3) Evaluate emerging technologies and trends in IoT for agriculture, including the integration of AI and machine learning, and predict their potential impact on the sector.

Training activities details

• Watch two 15-20 mim. videos

• Interact with one 15-20 mim. dynamic course presentation

• One extra suggested reading

• Take the MCQ knowledge test

• Contribute to the course forum

Final test and assignment

1) Final test

2) Open Ended Question