Sökning: "EXAMENSARBETE embedded systems"

Visar resultat 1 - 5 av 79 uppsatser innehållade orden EXAMENSARBETE embedded systems.

  1. 1. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

    Master-uppsats, KTH/Mekatronik och inbyggda styrsystem

    Författare :Helgi Hrafn Björnsson; Jón Kaldal; [2023]
    Nyckelord :Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

    Sammanfattning : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. LÄS MER

  3. 2. Design and implementation of an energy harvesting system in a prosthetic limb

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Ódinn K. Rúnarsson; [2023]
    Nyckelord :Energy harvesting; Prosthetic limbs; Supercapacitors; Printed circuit boards; 3D printing; Energiinsamling; Lemmproteser; Superkondensatorer; Tryckta kretskort; 3D Utskrivning; Orkuöflun; Gervilimir; Ofurþéttar; Prentaðar rafrásir; Þrívíddarprentun;

    Sammanfattning : Energy Harvesting, also known as power harvesting or ambient power, is the process of obtaining small amounts of power from secondary sources, such as vibrations, light, temperature variations and even radio-frequency emissions. These systems have been uncommon in personal and wearable electronics in the past, however they are slowly gaining traction. LÄS MER

  4. 3. Multi-Scale Task Dynamics in Transfer and Multi-Task Learning : Towards Efficient Perception for Autonomous Driving

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Simon Ekman von Huth; [2023]
    Nyckelord :Autonomous Driving; Computer Vision; Deep Learning; Machine Learning; Multi-Task Learning; Transfer Learning; Task Relationships; Task Dynamics; Python; Multi-Scale Representation Learning; Fuss-Free Network; Självkörande Fordon; Datorseende; Djupinlärning; Maskininlärning; Multiuppgiftsinlärning; Överföringsinlärning; Uppgiftsrelationer; Uppgiftsdynamik; Python; Flerskalig Representationsinlärning; Fuss-Free Nätverk;

    Sammanfattning : Autonomous driving technology has the potential to revolutionize the way we think about transportation and its impact on society. Perceiving the environment is a key aspect of autonomous driving, which involves multiple computer vision tasks. LÄS MER

  5. 4. Syntax-Based Dependency Discovery : Extracting Dependencies Between Integration Test Cases for Passive Testing

    M1-uppsats, KTH/Hälsoinformatik och logistik

    Författare :David Halldoff; Martin Sten; [2023]
    Nyckelord :Software testing; passive testing; integration testing; test case; dependency discovery; guarded assertion; automotive; safety-critical; Mjukvarutestning; passiv testning; integrationstestning; testfall; beroendeupptäckt; fordon; säkerhetskritisk;

    Sammanfattning : Modern-day vehicles consist of numerous electronic computing devices with accompanying software. Since vehicles are generally classified as safety-critical systems, rigorous testing strategies have to be deployed to ensure correct operation of the embedded software. LÄS MER

  7. 5. Embedded Software Simulation Method for Multi-Core Environments Using Parallelism

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Joachim Larsson; [2023]
    Nyckelord :Embedded software; linux processes; multi-core simulation; parallelism; Inbyggd mjukvara; linux processer; flerkärnig simulering;

    Sammanfattning : As technology advances, embedded systems become increasingly complex, with embedded software implemented on platforms with many processors running in parallel. Testing such software on hardware might not always be possible and, when possible, can be time-consuming and costly. LÄS MER