In the field of embedded systems, computers embedded into machines ranging from microwaveovensto assembly lines impact the physical world. They do so under tight real-time constraintswith ever-increasing demand for computing power and performance. Development of higher speedprocessors have been hampered by diminishing returns on power consumption as clock frequency isfurther increased. For this reason, today, embedded processor development is instead moving towardfurther concurrency with multi-core processors being considered more and more every day. Withparallelism comes challenges, such as interference caused by shared resources. Contention betweenprocessor cores, such as shared memory, result in inter-core interference which is potentially unpredictableand unbounded. The focus of this thesis is placed on minimizing inter-core interferencewhile meeting local task timing requirements by utilizing scheduling heuristics. A scheduling heuristicis designed and a prototype scheduler which implements this algorithm is developed. Thescheduler is evaluated on randomly generated test cases, where its ability to keep inter-core datapropagationdelays low across different core counts and utilization values was evaluated. The algorithmis also compared with constraint programming in a real world industrial test case. Theobtained results show that the algorithm can produce schedules with low inter-core delays in a veryshort time, although not being able to optimize them fully compared to constraint programming.

Musical Instrument Digital Interface(MIDI) is a technical standard that specifies acommunication protocol for digital instrument data and is mainly used by computers,synthesizers and electronic keyboards. A MIDI controller is any hardware or software that cangenerate and transfer MIDI data to a MIDI device, usually to play a sound or change controlparameters within a music software. An important property of a MIDI controller is to intuitively go from idea to execution withminimal effort. In this respect machine learning has really opened up for new musicalexpressions within musical devices. During this project a prototype with an implementedmachine learning algorithm which could deliver a wider array of functionality with a simplerinterface. The device developed should also be able to play Hi-Fi audio with at least 96 kHzsampling frequency and 24-bit bit-resolution. Without professional measurement equipment audio quality could not be completelymeasured. However, the development of the completed prototype as a whole was successful. Drawn symbols could be classified with a 70% accuracy, Hi-Fi audio could be played and MIDI-messages could be sent over USB to a music software.

This project aimed to create a simple open-source embedded graphical user interface library that could be used on more or less any microcontroller platform. The programming language was intended to be C++ for the GUI but as the project evolved C was chosen above C++. This was a decision based primarily on the fact that STM's development environment, STMCubeIDE, is less compatible with C++. The IDE offers great hardware support which in the end was more important than the advantages given by C++. The hardware used in this project was an STM32F469 microcontroller. It has an ARM CortexM4 processor core and 2 Mbyte of flash memory and 384 Kbytes of RAM. Wrapper functions for the Board Support Package, BSP, were written as a part of the library to allow easy access tothe BSP needed for the hardware configuration. The first part of the project goal was achieved, a simple GUI library was created. The resulting GUI library supports user interaction through buttons, it can display the current time andvisualizes given data in graphs. The graph function can display the data live, as a scatter plot, a bar plot and a line plot. The library also supports an alarm function that allows the user to decide what will happen after the alarm time is up. However, even though the GUI library was written to be device-independent, the product has not been tested on other platforms. For further development, this GUI library could be tested on another microcontroller. This would provide answers to how much software changes are needed to make the product as hardwareindependent as possible. To make the library lighter and faster, there is a possibility of optimizing the GUI core.

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<p>This rapport describes how a security and control system has been developed for moveable diesel tanks. Enormous amounts of diesel in Sweden are stolen every year and the tank that is most vulnerable is the moveable tank in other words tanks that can be moved around with diesel inside.</p><p>The report proposes methods how to measure fluid amount in a tank and how to measure if diesel is disappearing from the tank.</p><p>The report also describes a tank monitoring system prototype.</p>

This paper discusses the design of an autonomous remote-controlled racecar to play a one-on-one match of capture the flag. A competition was held, and the results are presented and conclusions are made.

This rapport describes how a security and control system has been developed for moveable diesel tanks. Enormous amounts of diesel in Sweden are stolen every year and the tank that is most vulnerable is the moveable tank in other words tanks that can be moved around with diesel inside. The report proposes methods how to measure fluid amount in a tank and how to measure if diesel is disappearing from the tank. The report also describes a tank monitoring system prototype.

With the advent of energy harvesters, supporting fast and efficient computation on energy harvesting devices has become a key challenge in the field of energy harvesting on ubiquitous devices. Computation on energy harvesting devices is equivalent to spreading the execution time of a lasting application over short, frequent cycles of power. However, we must ensure that results obtained from intermittently executing an application do produce results that are congruent to those produced by executing the application on a device with a continuous source of power. The current state-of-the-art systems that enable intermittent computation on energy harvesters make use of novel compiler analysis techniques as well as on-board hardware on devices to measure the energy remaining for useful computation. However, currently available programming models, which mostly target devices with FRAM as the NVM, would cause failure on devices that employ the Flash as primary NVM, thereby resulting in a non-universal solution that is restricted by the choice of NVM. This is primarily the result of the Flash's limited read/write endurance. This research aims to contribute to the world of energy harvesting devices by providing solutions that would enable intermittent computation regardless of the choice of NVM on a device by utilizing only the SRAM to save state and perform computation. Utilizing the SRAM further reduces run-time overhead as SRAM reads/writes are less costlier than NVM reads/writes. Our proposed solutions rely on programmer-guidance and compiler analysis to correct and efficient intermittent computation. We then extend our system to provide a complete compiler-based solution without programmer intervention. Our system is able to run applications that would otherwise render any device with Flash as NVM useless in a matter of hours. / Master of Science / As batteries continue to take up space and make small-scale sensors hefty, battery-less devices have grown increasingly popular for non-resource intensive computations. From tracking air pressure in vehicle tires to monitoring room temperature, battery-less devices have countless applications in various walks of life. These devices function by periodically harvesting energy from the environment and its surroundings to power short bursts of computation. When device energy levels reach a lower-bound threshold these devices must power off to scavenge useful energy from the environment to further perform short bursts of computation. Usually, energy harvesting devices draw power from solar, thermal or RF energy. This vastly depends on the build of the device, also known as a microprocessor (a processing unit built to perform small-scale computations). Due to these devices constantly powering on and off, performing continuous computation on such devices is rather more difficult when compared to systems with a continuous source of power. Since applications can require more time to complete than one power cycle of such devices, by default, applications running on these devices will restart execution from the beginning at the start of every power cycle. Therefore, it is necessary for such devices to have mechanisms to remember where the were before the device lost power. The past decade has seen many solutions proposed to aid an application in restarting execution rather than recomputing everything from the beginning. Solutions utilize different categories of devices with different storage technologies as well different software and hardware utilities available to programmers in this domain. In this research, we propose two different low-overhead, long-life computation models to support intermittent computation on a subset of energy harvesting devices which use Flash-based memory to store persistent data. Our approaches are heavily dependent on programmer guidance and different program analysis techniques to sustain computation across power cycles.