Essays about: "edge devices"
Showing result 16 - 20 of 133 essays containing the words edge devices.
-
16. Measuring the responsiveness of WebAssembly in edge network applications
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Edge computing facilitates applications of cyber-physical systems that require low latencies by moving compute and storage resources closer to the end application. Whilst the edge network benefits such systems in terms of responsiveness, it increases the systems’ complexity due to edge devices’ often heterogeneous and resource-constrained nature. READ MORE
-
17. Edge Machine Learning for Wildlife Conservation : A part of the Ngulia project
University essay from Linköpings universitet/ReglerteknikAbstract : The prominence of Edge Machine Learning is increasing swiftly as the performance of microcontrollers continues to improve. By deploying object detection and classification models on edge devices with camera sensors, it becomes possible to locate and identify objects in their vicinity. READ MORE
-
18. Integration of Attribute-Based Encryption and IoT: An IoT Security Architecture
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Services relying on internet of things (IoTs) are increasing day by day. IoT makes use of internet services like network connectivity and computing capability to transform everyday objects into smart things that can interact with users, and the environment to achieve a purpose they are designed for. READ MORE
-
19. Low-power Acceleration of Convolutional Neural Networks using Near Memory Computing on a RISC-V SoC
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : The recent peak in interest for artificial intelligence, partly fueled by language models such as ChatGPT, is pushing the demand for machine learning and data processing in everyday applications, such as self-driving cars, where low latency is crucial and typically achieved through edge computing. The vast amount of data processing required intensifies the existing performance bottleneck of the data movement. READ MORE
-
20. Efficient Memory Encryption for Neural Network Accelerators
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : The widespread integration of machine learning (ML) in edge and mobile devices, particularly in critical contexts like autonomous vehicles, highlights the need for robust security. However, ensuring data confidentiality and preserving inference integrity is costly due to the mismatch between traditional security methods and ML demands. READ MORE
