Program Overview

This intensive 6-week program provides 100 hours of remote training for Higher Education Institution (HEI) teachers from Ukraine. The focus is on good practices in hands-on learning and knowledge transfer in AI and IoT, aligned with the outcomes of the Erasmus+ TransLeader project. The program will help participants integrate AI and IoT technologies into their teaching practices and foster collaborations between academia and industry.

Target Audience

- HEI teachers from Ukraine in the fields of IT, management, engineering, and related disciplines.

- Trainers aiming to enhance AI/IoT-based teaching approaches.

Learning Outcomes

Participants will:

1. Gain a deep understanding of AI and IoT applications in various sectors (education, management, healthcare, etc.).
2. Learn transferable models of knowledge transfer and collaboration between academia and industry.
3. Acquire practical skills to design hands-on learning experiences using AI/IoT.
4. Develop a strategy to enhance the relevance and quality of education using AI/IoT.

Program Structure

The 100-hour program will be delivered over 6 weeks, averaging 16-17 hours per week. Each week will include a mix of live lectures, workshops, group discussions, and hands-on practical sessions.

Week 1: Introduction to AI, IoT, and Knowledge Transfer in Higher Education (16 hours)

- Topics:

  - Overview of the TransLeader Project

  - Introduction to AI and IoT Technologies

  - AI and IoT in Higher Education: Use Cases and Applications

  - Knowledge Triangle: Trainers, Trainees, and Market Representatives

  - Challenges and gaps in AI/IoT skills within the SME sector

  - Identifying technological challenges and labor market needs

- Activities:

  - 4 hours – Live Webinar: Introduction to TransLeader project outcomes and AI/IoT use cases (08.11.2024 16:00-20:00 CET)

Video recording:        Part 1      Part 2

Presentations:  TransLeader_introduction       Terminology   Curriculum_structure    Methodology_collecting_good_practices

  - 4 hours – Interactive Q&A and discussion on AI/IoT in education (11.11.2024 17:00-21:00 CET)

Video recording:   Part 1    Part 2  

Presentation:   QandAsession

  - 4 hours – Group activity: Analyze a real-world AI/IoT business case (12.11.2024 17:00-21:00 CET)

Presentation template: Template.pptx

  - 4 hours – Individual Assignment: Identifying challenges in HEIs and AI/IoT opportunities for knowledge transfer (14.11.2024 17:00-21:00 CET)

Week 2: Best Practices in Academia-Industry Collaboration (17 hours)

- Topics:

  - Case studies: Knowledge transfer models between EU universities and industries

  - Collaboration frameworks between HEIs and SMEs

  - Promoting hands-on learning through student-industry partnerships

  - Adapting best practices from Kyiv University and EU partners

- Activities:

  - 4 hours – Workshop: Creating AI/IoT-based collaborative student-industry projects (18.11.2024 17:00-21:00 CET)

Video recording (dr Marcin Bernaś)

  - 4 hours – Case study discussion: Knowledge transfer models (EU vs. Ukraine) (20.11.2024 17:00-21:00 CET)      !!! Questionaire

  - 4 hours – Group project: Develop a plan for  AI/IoT Technologies and Solutions (21.11.2024 17:00-21:00 CET)

  - 5 hours – Individual Assignment: Evidencing how AI/IoT Tech addresses the identified problem (22.11.2024 17:00-22:00 CET)

 Week 3: AI in Education: Tools, Personalization, and Learning Outcomes (17 hours)

- Topics:

  - AI-based tools for adaptive learning and personalized education

  - Practical applications of AI to improve student outcomes

  - Designing AI-infused learning experiences for technical and non-technical disciplines

  - AI systems for classroom management and assessment

- Activities:

  - 4 hours – Workshop: Implementing AI-based research (25.11.2024 17:00-21:00 CET)

Video recording (dr Aleksandra Kłos-Witkowska)

Presentation (dr Aleksandra Kłos-Witkowska) 

- 4 hours – Q&A session: Setting up the requirements for AI-based research (26.11.2024 17:00-21:00 CET)

  - 4 hours – Group working: How to evaluate AI tools for research (28.11.2024 17:00-21:00 CET)

  - 5 hours – Project work: Design a plan integrating AI for research (29.11.2024 17:00-22:00 CET)

 Week 4: IoT Systems in Education (17 hours)

 - Topics:

  - IoT applications in engineering, management, and logistics education

  - Smart research and  education solutions using IoT

  - Enhancing accessibility and inclusivity with IoT technologies

  - Addressing challenges in IoT security and privacy in educational settings

- Activities:

  - 4 hours – Hands-on workshop: Designing IoT-based systems in Research and Education (02.12.2024 17:00-21:00 CET)

Video recording  (by dr Łukasz Więcław)

  - 4 hours – Q&A session: IoT for HEIs: teaching, research, security,  educational logistics (03.12.2024 17:00-21:00 CET)

Questionnaire

  - 4 hours – Group working: Challenges and ethical concerns in IoT for education (05.12.2024 17:00-21:00 CET)

  - 5 hours – Practical assignment: Develop a proposal for using IoT in the project (06.12.2024 17:00-21:00 CET)

 Week 5: Hands-on Learning and Practical AI Projects (16 hours)

  - Topics:

  - Principles for designing project-based learning experiences in AI/IoT

  - Collaborative AI/IoT projects involving students and real cases

  - AI/IoT in addressing social, art and ethical challenges

  - Ethical considerations and data privacy in AI/IoT education

- Activities:

  - 4 hours – Workshop: Designing hands-on AI art projects for students (09.12.2024 17:00-21:00 CET)

  - 4 hours – Q&A session: Addressing real-world social, art, and ethical challenges using AI/IoT (10.12.2024 17:00-21:00 CET)

  - 4 hours – Group working: Peer review and feedback on AI/IoT project designs (12.12.2024 17:00-21:00 CET)

  - 4 hours – Individual assignment: Create a student project outline for a practical AI/IoT solution (13.12.2024 17:00-21:00 CET)

(to be continued)

 Week 6: Dissemination, Evaluation, and Future Trends in AI and IoT (17 hours)

 Assessment and Certification:

Participants will be assessed through:

- Active participation in webinars, workshops, and discussions.

- Group projects, including presentations and collaboration.

- Individual assignments and peer feedback.

- A final project presentation.

Upon completion, participants will receive a certificate recognizing their expertise in AI and IoT applications, knowledge transfer, and innovative educational practices, as part of the Erasmus+ TransLeader project.

 Materials Provided:

- TransLeader project reports, best practice guidelines, and toolkits.

- Access to AI and IoT software tools.

- Webinar recordings and downloadable resources.

- Ongoing support through discussion forums and peer mentoring.

20 real-world AI/IoT business cases that can be analyzed by the teams 

1. Smart Agriculture: Precision Farming

• AI/IoT Tech: IoT sensors for soil moisture, temperature, and weather data; AI models for crop yield prediction.
• Business Case: Using AI and IoT to optimize irrigation, monitor soil health, and predict crop diseases to improve yield and reduce costs in farming operations.

2. Smart Cities: Traffic Management Systems

• AI/IoT Tech: IoT-enabled traffic sensors, AI-based traffic prediction models.
• Business Case: AI-powered traffic management solutions that optimize traffic flow, reduce congestion, and improve public transport scheduling.

3. Healthcare: Remote Patient Monitoring

• AI/IoT Tech: Wearable devices, IoT-connected health trackers, AI for predictive analytics.
• Business Case: AI and IoT solutions for remote monitoring of patients' vital signs (e.g., heart rate, blood sugar levels) to enable early detection of health issues.

4. Retail: Personalized Shopping Experience

• AI/IoT Tech: IoT sensors, AI-driven recommendation engines.
• Business Case: Implementing IoT sensors in physical stores to track customer movements, combined with AI to deliver personalized offers or product suggestions.

5. Smart Homes: Energy Management

• AI/IoT Tech: IoT-enabled thermostats, AI-driven energy consumption analysis.
• Business Case: Using AI and IoT to optimize energy consumption in smart homes, reducing electricity bills and enhancing sustainability by predicting and managing energy needs.

6. Logistics and Supply Chain: Inventory Optimization

• AI/IoT Tech: RFID sensors, AI for demand forecasting.
• Business Case: IoT devices to track goods in real-time, combined with AI to predict demand, optimize stock levels, and minimize stockouts or overstocking.

7. Manufacturing: Predictive Maintenance

• AI/IoT Tech: IoT sensors for machine health monitoring, AI-driven predictive models.
• Business Case: Using IoT sensors to monitor machinery health and AI to predict failures before they happen, reducing downtime and maintenance costs.

8. Smart Agriculture: Livestock Health Monitoring

• AI/IoT Tech: IoT wearables for animals, AI for health monitoring and predictive analytics.
• Business Case: AI-powered IoT solutions that monitor livestock for early signs of disease, optimize feeding schedules, and improve overall herd health management.

9. Energy Sector: Smart Grid Management

• AI/IoT Tech: IoT sensors for energy consumption, AI for grid optimization.
• Business Case: Using AI and IoT to manage energy distribution, detect faults, and predict energy demand for more efficient and sustainable grid management.

10. Retail: Smart Shelves and Automated Checkout

• AI/IoT Tech: IoT sensors, AI-powered checkout systems.
• Business Case: IoT-enabled smart shelves that track inventory and detect stockouts in real-time, coupled with AI-powered automated checkout systems to improve customer experience.

11. Environmental Monitoring: Air Quality Management

• AI/IoT Tech: IoT sensors for air quality monitoring, AI-based pollution prediction models.
• Business Case: Deploying IoT devices to monitor air quality in cities and using AI to predict pollution trends, providing actionable insights for urban planning and public health.

12. Automotive: Autonomous Vehicles

• AI/IoT Tech: IoT-connected vehicle sensors, AI for autonomous driving.
• Business Case: The development of autonomous vehicles powered by IoT sensors and AI algorithms for real-time decision-making, navigation, and accident prevention.

13. Smart Healthcare: AI-Powered Diagnostic Tools

• AI/IoT Tech: IoT-enabled medical devices, AI for image recognition and diagnosis.
• Business Case: Using IoT devices for data collection (e.g., images, vital signs) and AI models to assist in diagnosing diseases such as cancer or diabetes based on patient data.

14. Smart Buildings: Building Automation Systems

• AI/IoT Tech: IoT sensors for lighting, HVAC, and occupancy; AI for energy optimization.
• Business Case: Implementing IoT to automate building functions like lighting, heating, and air conditioning, with AI algorithms to optimize energy consumption based on real-time occupancy data.

15. Insurance: AI in Risk Assessment

• AI/IoT Tech: IoT data collection (e.g., for vehicle or property monitoring), AI for risk prediction.
• Business Case: Using IoT devices to gather real-time data on insured assets (vehicles, homes) and applying AI to assess risks, set premiums, and detect fraud.

16. Telecommunications: Network Traffic Optimization

• AI/IoT Tech: IoT network sensors, AI for predictive traffic management.
• Business Case: AI and IoT solutions for optimizing network performance by predicting peak demand periods, adjusting resources dynamically, and improving overall service quality.

17. Retail: Smart Vending Machines

• AI/IoT Tech: IoT-enabled vending machines, AI for inventory tracking and consumer behavior analysis.
• Business Case: Deploying IoT-enabled smart vending machines that monitor stock, predict demand, and use AI to tailor product recommendations to consumers.

18. Construction: Smart Site Monitoring

• AI/IoT Tech: IoT sensors for safety, AI for site management.
• Business Case: Using IoT devices to monitor construction site safety (e.g., worker location, equipment usage) and AI for project management, risk detection, and resource allocation.

19. Supply Chain: Cold Chain Monitoring

• AI/IoT Tech: IoT temperature and humidity sensors, AI for supply chain tracking.
• Business Case: Implementing IoT sensors to track temperature-sensitive goods (e.g., pharmaceuticals, food) in real time, ensuring the integrity of the cold chain with AI-driven anomaly detection.

20. Customer Support: AI Chatbots in Customer Service

• AI/IoT Tech: AI-powered chatbots, IoT for customer interaction data.
• Business Case: Deploying AI chatbots for customer service that can access real-time data from IoT devices (e.g., smart home products) and provide personalized assistance, troubleshooting, or product recommendations.