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A digital learning-teaching environment is introduced in which undergraduate students are challenged to connect the basic physical concepts of oscillation, buoyancy and data analysis via an authentic experiment. The damped oscillation of a cylindrical body swimming upright in water is measured via the MEMS acceleration sensor of a wireless MCU SensorTag. The data are recorded with the app phyphox on a smartphone or tablet. The theoretical oscillation period and the experimentally determined periods obtained via different data analysis roots are found to agree showing an excellent theory-experiment interplay. The proposed experiment is suited for the physics home lab e.g. under the current pandemic situation or for open university courses as well as for physics lab courses.

Belastningsskador är idag ett allt större problem i samhället som leder till flera sociala och ekonomiska problem. Tillsammans med en ökande ålder på befolkningen kan belastningsbesvär skapa ännu mer utmaningar i framtiden. Att utöka kunskapen om ergonomi är ett bra sätt att minska risken för att drabbas av belastningsskador. Idag används primärt en visuell bedömning av ergonomi, men varje bedömning är individuella och inte konsistenta. Tillgängligheten av små och billiga Inertial Measurement Unit (IMU) har ökat möjligheten att mäta objektivt istället för subjektivt. I detta exjobb har Texas Instruments SensorTag CC2650 använts som sensor, då den är billig och har många inbyggda sensorer där den 9-axliga rörelsesensorn var den eftersökta. En webbaserad utvecklingsmiljö kallad Node-RED användes för utveckling av en prototyp och sensorn kopplades till en smarttelefon tillsammans med Texas Instruments egna applikation. Data från sensorn skickades från smarttelefonen till webbapplikationen. Mätningar utfördes på en arm för att mäta belastningen på en axel, när handens position passerade axelns höjd finns det risk för belastningsskador efter en längre tid. För att beräkna vinkel av armen användes accelerometer samt gyroskop tillsammans med ett komplementärt filter. Prototypen testades i flera tester, där ena testet undersökte en högre risk t.ex. rita på en tavla samt lägre risk t.ex. papperssortering. Det visade sig att sensorn är kapabel att utföra bedömningar av belastningsriskerna. Men det finns kända begränsningar i form av låg samplingshastighet på 5 Hz (begränsningar i Texas Instruments applikation). Nästa steg för vidare arbete är att lägga till en magnetometer till prototypens sensor fusion och undersöka dess tillförlitlighet. / Musculoskeletal disorders (MSD) is a rising problem in society leading to several socio-economic problems. In combination of the trend of an aging population, MSD can cause even more challenges in the future. Expanding the knowledge of ergonomics is a good way to reduce the risk of stress injury. Today, a visual assessment of ergonomics is primarily used. These observations are individual and not consistent. Availability of cheaper and smaller Inertial Measurement Unit (IMU) has increased the possibility of using objective measurements instead of subjective observations. In this thesis work, the Texas Instruments SensorTag CC2650 was used as a sensor, because it is cheap and has many built-in sensors where the 9-axis motion sensor was the most sought one. A web-based development environment called Node-RED was used to develop a prototype and the sensor was connected to a smartphone along with Texas Instruments own application. The data from the sensor was sent from the smartphone to the web application. Measurements were performed on an arm to measure the load on a shoulder, when the hand's position passed the height of the shoulder it indicates that there is a risk of musculoskeletal disorders after an amount of time. To calculate the angle of the arm, sensor fusion of an accelerometer and a gyroscope were used together with a complementary filter. Developed system was evaluated by series of tasks exposing the shoulder to a higher risk e.g., painting compare to lower risk tasks e.g., paper sorting. It turned out that measurement are useful for assessment of the risk. However, there are known limitations like low sampling rate of 5Hz (due to limitation in the android app from Texas Instruments). Adding magnetometer to the sensor fusion and evaluation of reliability of calculations are the next natural steps for future work.

Internet of Things is the latest phenomenon in the computing industry. Even if it has not been completely defined yet, we are already surrounded by various devices connected to the Internet. This thesis project focuses on low cost and low-power wireless solutions and on the on-line backend behind the architecture. At the same time the present work also deals with Cloud Computing which can provide a highly scalable runtime environment for this backend without building an infrastructure. To handle the huge amount of data collected by billions of devices, BigData services could be used in the same cloud space. The project is a collection of the theoretical background of the Internet of Things; so as a result, it provides the reader with an overview of the concept. It also provides a walktrough of the design, implementation and testing process of a complex agricultural Internet of Things solution.