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  • 1.
    Jiang, Yiliang
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    Quantitative comparison of SensibleThings and Microsoft Azure IoT Hub2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    With the development of the Internet-of-Things, more and more IoT platforms come up with different structures and characteristics. Making balance of their advantages and disadvantages, we should choose the suitable platform in differ- ent scenarios. For this project, I make comparison of a cloud-based centralized platform, Microsoft Azure IoT hub and a fully distributed platform, Sensi- bleThings. Quantitative comparison is made for performance by 2 scenarios, messages sending speed adds up, devices lie in different location. General com- parison is made for security, utilization and the storage. Finally I draw the con- clusion that SensibleThings performs more stable when a lot of messages push- es to the platform. Microsoft Azure has better geographic expansion. For gener- al comparison, Microsoft Azure IoT hub has better security. The requirement of local device for Microsoft Azure IoT hub is lower than SensibleThings. The SensibleThings are open source and free while Microsoft Azure follow the con- cept “pay as you go” with many throttling limitations for different editions. Microsoft is more user-friendly.

  • 2.
    Li, Yimeng
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Self-Tuning NFC Circuits2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Contactless automatic identification procedures which are called RFID systems (Radio-frequency Identification) have become very popular in recent years for transferring power and data. With the development of RFID technology, the demand of easy transmitting of short data packages has made NFC (Near-field Communication) technology wildly used especially in mobile applications. The communication between a mobile and a tag is achieved through a magnetic field generated by the mobile’s NFC interface. In order to get a maximal power transmission, the tag circuit is designed to operate at the resonance frequency of 13.56 MHz, which is equal to the operation frequency of the mobile’s NFC interface. As mutual inductances provided by different kinds of mobiles exist divergence, optimal power transfer cannot be reached every time. This thesis focuses on the optimization of power transfer during the communications between tags and mobiles with uncertain NFC coils. By incorporating a self-tuning parallel variable capacitance compensation circuitry the resonance frequency of an NFC tag circuit can be self-tuned to 13.56 MHz to ensure an optimal power transmission. This thesis presents both theoretical and experimental analysis of this improved self-tuning NFC circuitry in detail and demonstrates that by digitally tuning a parallel capacitor circuit, the energy transferred to an NFC tag can be optimized when facing different kinds of NFC-enabled mobile phones.

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