This report deals with the possibilities of creating a system for a point-to-point audio- and video communication link, using cheap and simple hardware. The system will be using a local area network based on Ethernet and IP. This work was focused around the Raspberry Pi and its possibilities and limitations, regarding this type of application. The usage of a Raspberry Pi was also compared to using a conventional mini-PC for the same purpose. The overall goal was to achieve a system for point to point audio- and video communication of a very high quality, preferrably HD quality. The users of the system are supposed to get a feeling of live communication. To achieve this a very large monitor was used at each node. The monitor, microphone, camera and speaker are to be integrated into a frame that is hung on a wall in order to resemble a window. When you want to talk to somebody at the other node, you just walk up to this window and call upon the person you want to speak to, since the communications link is always active. This system could be used for distance meetings, distance lectures and in other similar situations. The results indicated that the Raspberry Pi was very capable of handling either transmission or reception of HD quality signals, but for full duplex communication a setup using two separate Raspberry Pis per node is recommended – one for transmission and one for reception. Another solution would be to choose a more powerful hardware platform,for instance a mini-PC, instead of the Raspberry Pi.

In order to handle the increasing costs of healthcare more of the care and monitoring will take place in the patient’s home. It is therefore desirable to develop smaller and portable systems that can record important biosignals such as the electrical activity of the heart in the form of an ECG. This project is a continuation on a previous project that developed a shield that can be connected to the GPIO pins of a Raspberry Pi, a credit-card sized computer. The shield contains an ADAS1000, a low power and compact device that can record the electrical activity of the heart along with respiration. The aim of this project was to develop an application that can run on the Raspberry Pi in order to display the captured data from the shield on a screen along with storing the data for further processing. The project was successful in the way that the requirements for the software have been fulfilled. / För att hantera den ökande kostnaden för hälso- och sjukvård kommer en större del av övervakning samt vård att ske i patientens hem. Det kommer därför att vara önskvärt att utveckla mindre system som är lättare att hantera än de större traditionella apparaterna för att samla in vanliga biosignaler som exempelvis ett EKG. Detta projekt är en fortsättning på ett tidigare projekt vars syfte var att framställa en ”sköld” som kan kopplas ihop med en Raspberry Pi via dess GPIO pinnar. Det föregående projektet var lyckat och en sköld innehållande en ADAS1000 som kan samla in bl.a. ett EKG samt andningen framställdes. Syftet med detta projekt var att utveckla en applikation som kan köras på en Raspberry Pi och på så sätt visa den data som samlas in från skölden på en skärm. Det skulle även vara möjligt att spara insamlad data för senare användning. Projektet resulterade i en applikation som uppfyllde dessa krav.

Many industries have been transformed to better perform in today’s digital age. In this project a solution for digitalizing printed sheet music as well as automating piano playing is researched, developed and built. The project was divided into three sub-systems, the first focusing on the digitalizing of sheet music, the second on identifying and classifying the notes and the third on playing the piano. These were later combined to form a demonstrator called Mozart2000, or M2k. The result was a robot which could determine the note pitch of an arbitrary note, or note combination, written in common music notation, and furthermore play these on the piano. The algorithm is based of off finding coordinates for stafflines and notes using image processing. Programming was done in Python with some functions extracted from the library OpenCV (Open Source Computer Vision). The piano playing mechanism uses solenoids and lever arms, controlled by electrical signals from a Raspberry Pi. Due to scope in budget and time some restrictions were made. The note range for the robot was limited to one octave, meaning 8 piano keys. Moreover, other musical information such as rhythmical and coloring were overlooked and set to a predetermined value. For the digitalizing part, a camera was used, taking a snapshot of one musical bar. The final solution however can be expanded to include additional keys and music segments by replicating the existing mechanism. / I detta projekt söks en lösning för digitalisering av tryckt notskrift, mot bakgrund av en ökande efterfrågan på digitala lösningar. Parallellt undersöks möjligheterna till att automatisera pianospel. För att underlätta arbetet delades projektet in i tre delsystem; det första fokuserade på digitalisering av notpapper, det andra på att hitta och identifiera noter, och det tredje på pianospelet. Delsystemen kunde därefter integreras och resulterade då i Mozart2000, M2k. Den slutgiltiga lösningen är en robot som kan bestämma tonhöjden från ett notpapper och spela dessa på ett piano. Den framtagna algoritmen bygger på att hitta koordinater för notlinjer och noter, jämföra dessa sinsemellan och tilldela dessa utgångar på en Raspberry Pi. Från dessa skickas elektriska signaler till en krets bestående av bland annat transistorer och frihjulsdioder, som i sin tur är kopplade till solenoider. Dessa solenoider kopplade till egentillverkade fingrar kommer sedan att slå an tangenterna på pianot. Eftersom projektet var begränsat i tid och budget gjordes ett antal förenklingar. Till exempel skulle Mozart2000 hålla sig till en oktav, det vill säga åtta toner. Vidare skulle rytmen vara en konstant och endast en takt skulle analyseras och spelas åt gången. Det bedöms dock möjligt att duplicera systemet för att täcka ett större notomfång och/eller fler takter.

Today orienteering competitions use digital sensors to collect the punches from each runner. This is done by a chip that the runner carries and punches at each control where a sensor is placed. This data is then collected and processed by a computer program to calculate the results. Since the orienteering competitions often occur in areas without common infrastructures, it requires the organisers to build their own for power and network. This thesis set out to investigate if it is possible to build a system where the data could be read, processed and presented without these locally built infrastructures. Furthermore, it investigates how much power the system would require. To test this a Raspberry Pi computer is used, where an orienteering sensor alongside a 4G modem is connected. On the Raspberry Pi a program is built for reading the data via an API communicating with the sensor. Then through mobile network the reserved data is sent to a result calculation server. These results are then presented on a website in order of best time. The energy consumption is measured through the amount of current the device uses. It was discovered that the device’s peak current was 798 mA which leads to that for a standard competition time of 8 hours a battery with the capacity of 6384 mA·h would be required. / Idag använder orienteringstävlingar digitala sensorer för att registrera stämplingar för de tävlande. Det görs med ett chip som löparen har med sig och stämplar i sensorer vid varje kontroll. Detta data läses sedan av och processas av ett datorprogram för att kalkylera ett resultat. Eftersom orienteringstävlingar ofta sker i områden utan allmän infrastruktur, krävs det att arrangören bygger upp egen infrastruktur för elektricitet och nätverk. Den här avhandlingen avser att undersöka om det är möjligt att bygga ett system där datat inhämtas, processas och presenteras utan att behöva bygga upp denna lokala infrastruktur. Vidare är syftet att undersöka hur mycket energi ett sådant system kräver. För att göra detta används en Raspberry Pi dator med en orienteringssensor och ett 4G modem. På Raspberry Pi:en skapas ett program vilket läser ut orienteringschipets data via ett API som kommunicerar med sensorn, och skickar via mobilt nätverk datat till en resultatberäkningsserver. Dessa resultat presenteras sedan på en webbsida. Den krävda batterikapaciteten beräknas utifrån hur mycket ström Raspberry Pi:en använder. Undersökningen visade att datorns maximala strömförbrukning var 798 mA vilket leder till att den krävda batterikapaciteten för att klara en tävlingsdag på 8 timmar är 6384 mA·h.

During the last couple of years there has been a shift in technology within the Swedish elderly care where the analog personal security alarm is being replaced with personal security alarm that uses internet to communicate. This transition happens due to the ever increasing access to the internet among the elderly and the decreasing availability of analog personal security alarms. This paper describes the work whose purpose is to develop a system that will act as a prototype of a personal security alarm that uses Voice Over IP and the protocol Session Initiation Protocol. The final system is to be comprised by a Raspberry Pi that uses the SIP protocol, a keypad and a soundcard that is built around PCM3060 chip. / De senaste åren pågår det ett teknikskifte inom den svenska äldreomsorgen där de analoga trygghetslarmen ersätts av larm som använder internet för att kommunicera. Denna övergång sker på grund av att tillgång till internet ökar hos äldre personer samt att hushåll med analoga anslutningarna blir allt färre. Denna rapport beskriver arbetet med att ta fram ett system som ska fungera som en prototyp för ett trygghetslarm. Detta system använder sig av Voice Over IP och protokollet Session Initiation Protocol. Det slutliga systemet består av en Raspberry Pi som använder sig av SIP protokollet, en knappsats samt ett ljudkort som är byggt runt ett PCM3060 chip.

The purpose of this bachelor’s thesis was to create a robot that could play chess through voice recognition and robotics. The two areas to be investigated were the robot’s precision and speed. The reason for building a robot arm of the SCARA type was that it can easily pick up and place pieces with reach over the entire chessboard. The robot arm is controlled from a Raspberry Pi 4 and is moved by two Dynamixel AX-12a servomotors. To pick up chess pieces, a continuous 360-degree servomotor was used to lift an electromagnet which was mounted on a gear rack. AUSB microphone was used to collect what move the player indicated. The Stockfish chess engine was used to generate moves for the robot. The parts of the robot that had the greatest impacton precision were the stability of the aluminum profiles, the gear ratio between the gears that transmit torque to the arm, the gear mesh contact ratio and the size of the electromagnet. The time it took to complete a move could be reduced by increasing the speed of the motors whena chess piece was not attached to the electromagnet, andusing a larger gear in the RC servo that raises and lowers the electromagnet. / Syftet med det här kandidatexamensarbetet var att skapa en robot som genom röstigenkänning och robotik kunde spela schack. De två områden som skulle undersöka svar robotens precision och hastighet. Anledningen till att bygga en robotarm av SCARA typ var att den enkelt kanplocka upp och ställa ner pjäser med räckvidd över hela schackbrädet. Robotarmen styrs från en Raspberry Pi 4och drivs av två stycken Dynamixel AX-12a servomotorer. För att plocka upp schackpjäser användes en kontinuerlig 360-graders servomotor som lyfte en elektromagnet monterad på iniumprofilerna, utväxlingenmellan kugghjulen som överför moment till armen, anliggningsytan vid kuggingreppen och storlek av elektromagnet. Tiden det tog att genomföra ett drag gick att minska genomatt öka hastigheten på motorerna då en schackpjäs inte sattfast på elektromagneten, samt använda ett större kugghjulhos RC servot som höjer och sänker elektromagneten.

The Department of Applied Physics and Electronics at Umeå University offers education and conducts research in the field of automation and robotics. To raise the competence in automation in the CODESYS development environment it’s proposed to build a remote controlled self-balancing robot as a testing platform which is then programmed using CODESYS for Raspberry Pi.   The chassis of the robot consists of laser-cut plexiglass plates, stacked on top of each other and fixed using threaded rods, nuts and washers. On these plates the robots’ electrical components, wheels and motors are attached.   The control system is designed as a feedback loop where the robots’ angle relative to the gravity vector is the controlled variable. A PID-controller is used as the system controller and a Kalman Filter is used to filter the input signals from the IMU board using input from both the accelerometer and the gyro.   The control system is implemented in CODESYS as a Function Block Diagram (FBD) using both pre-made, standard function blocks and customized function blocks. By using the in-built web-visualization tool the robot can be remote controlled via Wi-Fi.   After tuning the Kalman Filter through plot-analysis and the PID-controller through Ziegler-Nichols method the robot can stay balanced on a flat surface.   The robots’ performance is tested through a series of test scenarios of which it only completes one out of four. The project ran out of time before further testing could be done.   For future work one could improve the performance of the PID-controller through more sophisticated tuning methods. One can also add a steering-function or test different type of controllers.

Context: Smart farming, agritech, is growing in popularity and is starting to develop rapidly with some already existing technology that is implemented in agriculture for both industrial and private use. Objectives: The goal of this thesis is to investigate the benefits and issues with implementing technology in agriculture, agritech. In this thesis the investigation and research is performed by conduction a literature study and an experiment. Realization: A prototype was created to monitor the soil moisture level and calculating the average soil moisture value, then water the plants when needed. This was then compared to a manually watered pot to investigate if agritech could reduce the water usage when maintaining plants. Results: The result of the experiment indicates that it is possible to improve the use of resources such as human labor, time spent on maintaining the plants and water usage. Conclusions: The conclusion of this thesis is with the help of agritech, human workers can spend more time on other tasks and maintain the technology implemented. Instead of observing the plants to see if they need watering and watering them manually. Water usage may also be minimized with the help of sensors that make sure the plants only get watered when needed by constantly checking the soil moisture level.

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With the recent advancement of deep learning, the performance of object detection techniques has greatly increased in both speed and accuracy. This has made it possible to run highly accurate object detection with real time speed on modern desktop computer systems. Recently, there has been a growing interest in developing smaller and faster deep neural network architectures suited for embedded devices. This thesis explores the suitability of running object detection on the Raspberry Pi 3, a popular embedded computer board. Two controlled experiments are conducted where two state of the art object detection models SSD and YOLO are tested in how they perform in accuracy and speed. The results show that the SSD model slightly outperforms YOLO in both speed and accuracy, but with the low processing power that the current generation of Raspberry Pi has to offer, none of the two performs well enough to be viable in applications where high speed is necessary.