Max amount of FITech students: 25
Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course.
This course explores the integration of remote sensing, wireless communications, and data processing in disaster risk reduction. It examines how ICT infrastructures facilitate resilient connectivity and situational awareness during different natural disaster events. With a specific focus on the socio-economic complexities of target regions, aim is to analyse the application of AI/ML for predictive modeling and early-warning systems.
Course contents
The content of this course is divided into four different units, whose contents are expanded as follows:
- Unit 1: Information acquisition. Information acquisition to prevent natural disasters. Satellite system architecture, orbits and monitoring system elements. Space, aerial and terrestrial instrumentation for monitoring. Use of drone technology for natural disasters.
- Unit 2: Wireless connectivity. Wireless connectivity in emergency response. Mobile technologies (4G & 5G) and wireless technologies (Bluetooth, Wi-Fi). Satellite communications and non-terrestrial networks (HAPs, drones). Machine-type communications and low-power wide area network technologies (LoRa, MTC, NB-IoT).
- Unit 3: Information processing. Information processing for emergency response. AI/ML for wireless communications in natural disasters. AI/ML methods for disaster prediction.
- Unit 4: Management of natural disasters. Challenges for natural disaster management. Overview of seismic disaster management. Early warning systems for landslide monitoring. Overview of natural disasters related to floods. Behavioral design in natural disasters.
Learning outcomes
By the end of this course, the students
- know the specific challenges and characteristics of managing major natural hazards in India (e.g., earthquakes, landslides, and floods)
- can evaluate appropriate monitoring, early-warning, and response strategies based on regional environmental, technological, and socio-economic conditions in India
- know the fundamentals of different technologies for acquiring environmental and disaster-related data, including satellite platforms, aerial systems, and terrestrial sensors, with the aim to determine their role in the monitoring of natural disasters
- can compare and assess different wireless communication technologies (e.g., cellular networks, satellite communications, IoT systems, and short-range wireless) for reliable data transmission in disaster monitoring and emergency contexts
- understand the data processing techniques, including artificial intelligence and machine learning methods, that could be used to extract relevant patterns from the monitoring data that is used in early warning systems for disaster prediction
- know how to plan technological solutions for disaster risk management, including drone-based monitoring, real-time sensing systems, and digital decision-support tools for natural disaster mitigation and response.
Course material
The course utilises lecture slides and supplementary reading materials, such as academic articles and technical reports recommended by the instructors. All materials will be distributed digitally via the learning management platform (i.e., MyCourses).
Teaching schedule
Lectures, visits, and other group activities will take place intensively during 18-22 May 2026, from 9.00-17.00 (week #21). No final exam.
Completion methods
Quizzes, learning diaries, and group work presentations.
More information in the Aalto University study guide.
You can get a digital badge after completing this course.