If you are willing to learn new technologies, use open-source software and promote your novel ideas about Linux, Automotive and Embedded, Linux Embedded Challenge is your opportunity to amaze everybody. Form your team (1-3 members) and research a project idea related to Automotive which can be realized using Freescale Linux BSP and platform. Challenge yourself and enroll to Linux Embedded Challenge by sending an e-mail at linuxemb@freescale.com. The format of the e-mail is: Subject: [LinuxEmbbededChallenge] [TEAMNAME] Project Name Team Description Project Description: Describe your idea in detail Include architectural diagrams and  used technologies Mention the improvements it brings to Automotive world. Please send you submissions in English. Enrollment period:  1 - 20 June, 2014. Extended Enrollment Period:  1 June - 4 July, 2014.

The sample applications for the LEC 2015 graphics workshop

Linux Embedded Challenge is a Linux contest for Automotive topics. Its goal is to promote Linux and Open Source software in the student world. It also targets to prove Linux can be successfully used as support for Automotive software development. Linux Embedded Challenge is aimed towards students in the terminal years from either Politechnica University of Bucharest or Military Technical Academy who have had in the past previous experience with programming on Linux.

When judging the projects we aim to be as fair as possible and identify the projects which are better than ordinary. We are looking for original ideas, something new or something that is improving what existed before, projects well executed and well documented. Each project will be ranked in two parts: During the Development period we will rank certain milestones.       Each milestone will have an associated number of points and deadline. The number of the milestones, interval and assigned points depend on the project itself. During the final we will judge the projects after they have been finalized and presented. Judging during the final The jury will be formed by NXP experienced engineers from two business groups who will try to be as objective as possible and determine the top three projects. The criterion and their weights are depicted below. Criterion Explanation Weight Originality Is this something new or improving something that existed before ? 20% Execution Does it do what it should do? Does it behave according to documentation in multiple scenarios ? Are there stability problems? 40% Usability Is the project easy to use and/or integrate ? Is it easy to understand and learn? 10% Utility Does it have applicability within the IoT or Automotive domains ? 10% Documentation Is the documentation easy to be read and understood? Is anyone with average knowledges on embedded able to reproduce the projects? 20%

The attached lecture is a short introduction about Computer Vision and additionally, you can find attached Octave Demos for Computer Vision.

IoT presentation

The attached archive contains the starting point for developing an OpenVG-based embedded graphics application on the Wandboard. It contains 2 items: 1) The training presentation:      These are the support slides for the OpenVG presentation held during the Linux Embedded Challenge workshop. 2) The support application:      This is a sample application meant to aid in setting up the platform for an OpenVG-based application.      In order to compile it directly on the Wandboard, you will need the arm-linux-gnueabi-g++ compiler. If it is not already installed on the board, you can obtain it by installing the g++-arm-linux-gnueabi package:      sudo apt-get install g++-arm-linux-gnueabi      Use the provided Makefile to build the application. It provides an example on how to: Set up the platform (using X11) and the EGL objects (context, rendering surface etc.) Create an OpenVG path Create a linear gradient paint Create a pattern paint based on a user-generated image Fill and stroke a path Use transformation matrices to scale, rotate and translate a rendered object  

Workshop challenges – 10 points Workshop Challenges – 6 points •Challenge 0: Boot Linux on UDOO •Challenge 1: ‘Hello World’ App on UDOO •Challenge 2: Led Blinking •Challenge 3: ATMEL – i.MX6 Communication Post-workshop Challenge – 4 points •Challenge 4: Connect a sensor to UDOO Project Development – 60 points •Each milestone has its score •Each milestone’s score is gained when: •The code is summited in the GIT repo •The video is send via email •Each day of delay will determine a loss of 5% from the milestone’s score •Bonus: 20%*Project_Development_Score Final Presentation – 30 points Judging Criteria Originality Execution Usability   Documentation

Check out some photos from last week Linux Embedded Programming Workshop.

The topics below are proposed by Freescale. Chosing one of them is not mandatory, you are free to come with your own idea for a topic. HMI - Human Machine Interface An HMI is a car system that allows the driver to easily use different information and entertainment car services. The HMI is usually found at the center of the car, between the driver and the passenger. A typical HMI can be a touchscreen allowing access to Radio & Audio subsystems as well as Navigation and Phone Connectivity. The teams chosing this project will need to design a graphical interractive application that allow the user to: Play media from various external devices (SD card or smartphone) Adjust audio and video settings Make and receive phonecalls from a smartphone connected to the Wandboard Use the navigation system Examples of HMI below: http://www.youtube.com/watch?v=iZsviUeLmmg Audi New HMI at CES2014 - YouTube Freescale Automotive Vision Freescale i.MX 6 Automotive Technology Audio Post Processing Filter Audio post processing, is the intentional alteration of auditory signals, or sound, often through an audio effect or effects unit. When listening to radio or music in a car, the surroundings around the listener can reduce the quality of listening experience. Traffic or wheel noise, people talking can contribute a lot of noise -- so much noise that some of the soft pieces in the music may become inaudible.Audio post processing can be used to improve the user experiencer by supressing the effects produced.by various noises. The teams chosing this project will have to show sample audio streams recorded with noises and the resulted output after the post processing alghorithms have been applied. Check out the links below dor more details: DSP-based audio post processing enhances audio quality | EE Times Audio signal processing - Wikipedia, the free encyclopedia Real Time Collision Detection A collision avoidance system is a system designed to reduce the severity of an accident. Also known as precrash system, forward collision warning system or collision mitigating system, it uses radar and sometimes laser and camera sensors to detect an imminent crash. Once the detection is done, these systems either provide a warning to the driver when there is an imminent collision or take action autonomously without any driver input (by braking or steering or both). One of the first phases in collision avoidance collision detection or detecting an approaching obstacle. A typical application will process images received through a camera connected to the Wandboard, detect objects that are getting closer and closer (having a certain speed as a threshold) and warn by playing a sound or showing a warning message on the screen.  For more details, visit: HowStuffWorks "Pre-collision Systems and Radar" Collision detection - Wikipedia, the free encyclopedia Safety Critical Linux A life-critical system or safety-critical system is a system whose failure or malfunction may result in: death or serious injury to people, or loss or severe damage to equipment or environmental harm. Automotive software is an example of a safety critical system. There is currently a lot of debate on whether Linux SW can be part of a such a system and there are open source projects aimed towards proving this. One of the examples of such project is the OSADL Project: Safety Critical Linux. A team chosing this topic might contribute to this project with applications or tools that control Linux application behaviour in Autmotive environment Check out the links below for more information: https://www.osadl.org/Presentations-and-Documents.safety-critical-documents.0.html http://elinux.org/images/9/96/LinuxInSCEnvironment.pdf AFS - Adaptive Front-light System Approximately 70% of vehicle to pedestrian accident occured in night time. The AFS adapts automatically to the traffic situation and weather conditions for increased safety and greater driving comfort. The teams chosing this project will have to create a prototype for controlling the front-light to different situations: curves, bumps, other traffic vehicles. Check out the links below for more information: Adaptive Frontlight System (AFS) - YouTube BMW Adaptive Headlights - YouTube https://techinfo.honda.com/rjanisis/pubs/om/JA0606/JA0606O00139A.pdf