IKT435 Wireless Embedded Systems and Sensor Networks
- ECTS Credits:
- 7.5
- Responsible department:
- Faculty of Engineering and Science
- Course Leader:
- Baltasar Enrique Beferull Lozano
- Lecture Semester:
- Autumn
- Teaching language:
- English
- Duration:
- 1 term
The course is connected to the following study programs
- Artificial Intelligence and The Internet of Things, Master's Programme
- Artificial Intelligence, 5-year master programme
Teaching language
EnglishRecommended prerequisites
MA-430-G Probability Theory and Stochastic Processes. Algebra and Calculus for Engineers, Basic programming skills, Basic knowledge of Computer Networks.
Course contents
The course covers the following topics: Introduction, motivation and applications of WSNs, node architecture, hardware platforms, operating systems, characteristics of MAC protocols for WSNs, contention-based MAC protocols, contention-free MAC protocols, routing protocols for WSNs (datacentric routing, proactive routing, on-demand routing), power management schemes, time synchronization protocols, collaborative data gathering, cooperative in-network data processing, iterative methods for distributed computation and inference (e.g. decentralized estimation, detection, control, learning), consensus and gossip self-organized algorithms, cross-layer design, application of network optimization tools, sensor network programming, node-centric programming, dynamic wireless re-programming, introduction to middleware and WSN management. Some of the concepts will be illustrated with practical examples drawn from state-of-the-art standards and implementation on real mote devices.
Learning outcomes
On successful completion of this course, the students should be able to:
- understand the essential theoretical tools (communications, networking protocols, optimization, signal processing and control) that are necessary to cope with Wireless Embedded Systems and Sensor Networks
- provide the basic understanding and engineering criteria about how to design, implement (programming) and deploy practical wireless sensor networks (WSNs) for different applications
- understand the advantages and limitations of different technologies used in the design and implementation of WSNs
Teaching methods
Lectures, laboratory assignments, self-study and group work.
The work load for the average student is approximately 200 hours.
Evaluation
The person responsible for the course decides, in cooperation with student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.
Assessment methods and criteria
The evaluation will consist of two parts: a) final written exam of 3 hours (60 %), b) Portfolio with homework and laboratory assignments (40 %). Graded assessment. Information about the portfolio will be given in LMS at the startup of the course.
Reduction of Credits
This course’s contents overlap with the following courses. A reduction of credits will occur if one of these courses is taken in addition:
| Course | Reduction of Credits |
|---|---|
| IKT432 – Wireless Embedded Systems and Sensor Networks | 5 |