RiseUpp Logo
Educator Logo

Capstone: Autonomous Runway Detection for IoT

Master IoT-based autonomous aircraft landing systems through hands-on implementation of embedded real-time processing and secure web connectivity.

Master IoT-based autonomous aircraft landing systems through hands-on implementation of embedded real-time processing and secure web connectivity.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Development of Secure Embedded Systems Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

4.6

(68 ratings)

5,682 already enrolled

English

پښتو, বাংলা, اردو, 3 more

Powered by

Provider Logo
Capstone: Autonomous Runway Detection for IoT

This course includes

30 Hours

Of Self-paced video lessons

Advanced Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Implement IoT-based autonomous aircraft landing systems

  • Develop embedded real-time processing solutions

  • Integrate secure web connectivity and cloud-based backends

  • Handle interfaces between multiple system components

  • Evaluate system efficiency and performance parameters

Skills you'll gain

Embedded Systems
IoT Development
Real-Time Systems
Aircraft Landing Systems
FreeRTOS
System Integration
Runway Detection
Web Security
Cloud Computing
System Architecture

This course includes:

0.6 Hours PreRecorded video

1 quiz, 1 programming assignment, 1 peer review

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

Created by

Provided by

Certificate

Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

icon-0icon-1icon-2icon-3icon-4

There are 3 modules in this course

This capstone project course integrates knowledge from real-time systems, web connectivity, security, and embedded hardware. Students develop a comprehensive system for IoT-based autonomous aircraft landing, implementing algorithms and handling interfaces between different actors and hardware platforms. The course emphasizes practical engineering tasks, system evaluation, and real-world parameters like energy consumption and cost, providing hands-on experience in modern embedded software development.

Introduction and methods

Module 1 · 3 Hours to complete

Implementation and integration

Module 2 · 7 Hours to complete

Project submission and Peer review

Module 3 · 19 Hours to complete

Fee Structure

Instructors

Farhoud Hosseinpour
Farhoud Hosseinpour

4.7 rating

48 Reviews

86,003 Students

4 Courses

Pioneering Research in Embedded Systems at EIT Digital

Farhoud Hosseinpour is a Doctoral Researcher at EIT Digital, where he focuses on advancing knowledge in the field of embedded systems and real-time technologies. His research encompasses several key areas, including "Capstone: Autonomous Runway Detection for IoT," "Development of Real-Time Systems," "Embedded Hardware and Operating Systems," and "Web Connectivity and Security in Embedded Systems." Through these courses, he aims to equip students with the skills necessary to design and implement innovative solutions in the rapidly evolving landscape of Internet of Things (IoT) and embedded systems. Farhoud's work not only contributes to academic research but also prepares students for practical challenges in technology development, emphasizing the importance of security and performance in modern applications.

Juha Plosila
Juha Plosila

4.5 rating

20 Reviews

23,174 Students

3 Courses

Associate Professor at the University of Turku

Dr. Juha Plosila is an Associate Professor in Digital Systems Design and Embedded Computing at the University of Turku (UTU), Finland. He has a robust academic background, having received his PhD in Electronics and Communication Technology from UTU in 1999. With over a decade of experience as an Academy Research Fellow, he leads the Embedded Computer and Electronic Systems (ECES) research unit and co-leads the Resilient IT Infrastructures (RITES) research program at the Turku Centre for Computer Science (TUCS). His research focuses on adaptive network-on-chip (NoC) based parallel embedded systems, emphasizing self-aware monitoring and control architectures.On Coursera, Dr. Plosila offers courses such as "Capstone: Autonomous Runway Detection for IoT" and "Web Connectivity and Security in Embedded Systems," designed to provide learners with practical skills in embedded systems and IoT applications. His involvement in European collaborations, including leading the Embedded Systems master’s program at EIT Digital, showcases his commitment to advancing education and research in digital technologies. Through his teaching and research initiatives, Dr. Plosila contributes significantly to the fields of digital systems and embedded computing.

Capstone: Autonomous Runway Detection for IoT

This course includes

30 Hours

Of Self-paced video lessons

Advanced Level

Completion Certificate

awarded on course completion

Free course

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.