Landing is one of the most critical phases during a flight. It is the second thing a pilot learns in training after basic flight control and recovery techniques. Touchdown is the first phase. An aircraft has to dump all this kinetic energy that keeps the aircraft flying. It's a fine maneuver that should be done right, not too soft, not too hard. Landing also is one of the most dangerous phases and most aircraft accidents take place either during the take off or landing. Instrumental guidance systems are, therefore, a great advantage to the pilots. In this project, we focus on runway detection by using image filtering techniques. Our runway detection algorithm is based on video frames. This means that we have a camera mounted on the aircraft which is recording the approach. The frames captured by the camera is then forwarded to image processing algorithms. To easily spot the visual characteristic of the runway, we will filter out other details than the edges in the frame. This makes the image simpler to process because now the picture only contains the most basic properties for determining a square runway in an otherwise diverse landscape. Okay, so runway detection already exists but now we want to build the next generation of landing system based on IoT. Let's consider the aircraft being a complex sensor system capable of recording and sending filtered video frames. These frames can now be sent to a Cloud server on ground, in which high performance algorithms such as deep learning can be applied on the video frames to optimize the landing. This type of heavy processing can not be executed on site because of lacking processing power and it must therefore be forwarded to a Cloud server. Of course, with data transfer, we expose a risk to leak confidential information that could endanger the safety of the aircraft. Check out Norse, my website, that visualizes the realtime attempts to break IT security worldwise. The link must, therefore, be secured before data transfer can begin. Let's recap the project. Your task is to build an autonomous landing system or aircraft. The system should detect a wrong way from a video frame. This is done by recording the landing with a camera mounted on the aircraft, the image is filtered by an edge detection algorithm and the filtered image is encrypted and sent to a Cloud server for further processing over a secure link. This course is built on three previous courses of this specialization. From the course embedded operating system and hardware, you will apply your skills for planning the embedded hardware platform. Planning the performance required for the processing, the cost of building such system and the energy such a system would consume. You will need to program a lot in this course and most of the programming will be based on the course development of realtime systems. The realtime processing of system must match the system requirements and correct scheduling must be ensured. Finally, you will need to utilize your skills from course web connectivity and security in embedded systems to establish the web connectivity and ensure the secure transfer of data to the Cloud server. My name is and I am a teacher in computer science at the University of Turku in Finland. You can check out our website to learn more about the University of Turku.