Recent Advances in Embedded Computing, Intelligence and Applications
The latest proliferation of Internet of Things deployments and edge computing combined with artificial intelligence has led to new exciting application scenarios, where embedded digital devices are essential enablers. Moreover, new powerful and efficient devices are appearing to cope with workloads...
محفوظ في:
| التنسيق: | Online |
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| اللغة: | الإنجليزية |
| منشور في: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| الموضوعات: | |
| الوصول للمادة أونلاين: | ONIX_20220621_9783036542461_82 |
| الوسوم: |
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| _version_ | 1869517890858778624 |
|---|---|
| collection | Directory of Open Access Books |
| description | The latest proliferation of Internet of Things deployments and edge computing combined with artificial intelligence has led to new exciting application scenarios, where embedded digital devices are essential enablers. Moreover, new powerful and efficient devices are appearing to cope with workloads formerly reserved for the cloud, such as deep learning. These devices allow processing close to where data are generated, avoiding bottlenecks due to communication limitations. The efficient integration of hardware, software and artificial intelligence capabilities deployed in real sensing contexts empowers the edge intelligence paradigm, which will ultimately contribute to the fostering of the offloading processing functionalities to the edge. In this Special Issue, researchers have contributed nine peer-reviewed papers covering a wide range of topics in the area of edge intelligence. Among them are hardware-accelerated implementations of deep neural networks, IoT platforms for extreme edge computing, neuro-evolvable and neuromorphic machine learning, and embedded recommender systems. |
| format | Online |
| id | doab-20.500.12854ir-84504 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-845042024-03-30T12:51:04Z Recent Advances in Embedded Computing, Intelligence and Applications Portilla, Jorge Otero, Andres Mujica, Gabriel high-level synthesis HLS SDSoC support vector machines SVM code refactoring Zynq ZedBoard extreme edge embedded edge computing internet of things deployment hardware design IoT security Contiki-NG trustability embedded systems collaborative filtering recommender systems parallelism reconfigurable hardware neuroevolution block-based neural network dynamic and partial reconfiguration scalability reinforcement learning embedded system artificial intelligence hardware acceleration neuromorphic processor power consumption harsh environment fog computing edge computing cloud computing IoT gateway LoRa WiFi low power consumption low latency flexible smart port quantisation evolutionary algorithm neural network FPGA Movidius VPU 2D graphics accelerator line-drawing Bresenham’s algorithm alpha-blending anti-aliasing field-programmable gate array deep learning performance estimation Gaussian process thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries The latest proliferation of Internet of Things deployments and edge computing combined with artificial intelligence has led to new exciting application scenarios, where embedded digital devices are essential enablers. Moreover, new powerful and efficient devices are appearing to cope with workloads formerly reserved for the cloud, such as deep learning. These devices allow processing close to where data are generated, avoiding bottlenecks due to communication limitations. The efficient integration of hardware, software and artificial intelligence capabilities deployed in real sensing contexts empowers the edge intelligence paradigm, which will ultimately contribute to the fostering of the offloading processing functionalities to the edge. In this Special Issue, researchers have contributed nine peer-reviewed papers covering a wide range of topics in the area of edge intelligence. Among them are hardware-accelerated implementations of deep neural networks, IoT platforms for extreme edge computing, neuro-evolvable and neuromorphic machine learning, and embedded recommender systems. 2022-06-21T08:39:01Z 2022-06-21T08:39:01Z 2022 book ONIX_20220621_9783036542461_82 9783036542461 9783036542454 https://directory.doabooks.org/handle/20.500.12854/84504 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/5488 https://mdpi.com/books/pdfview/book/5488 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-4245-4 10.3390/books978-3-0365-4245-4 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036542461 9783036542454 188 Basel open access |
| spellingShingle | high-level synthesis HLS SDSoC support vector machines SVM code refactoring Zynq ZedBoard extreme edge embedded edge computing internet of things deployment hardware design IoT security Contiki-NG trustability embedded systems collaborative filtering recommender systems parallelism reconfigurable hardware neuroevolution block-based neural network dynamic and partial reconfiguration scalability reinforcement learning embedded system artificial intelligence hardware acceleration neuromorphic processor power consumption harsh environment fog computing edge computing cloud computing IoT gateway LoRa WiFi low power consumption low latency flexible smart port quantisation evolutionary algorithm neural network FPGA Movidius VPU 2D graphics accelerator line-drawing Bresenham’s algorithm alpha-blending anti-aliasing field-programmable gate array deep learning performance estimation Gaussian process thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Recent Advances in Embedded Computing, Intelligence and Applications |
| title | Recent Advances in Embedded Computing, Intelligence and Applications |
| title_full | Recent Advances in Embedded Computing, Intelligence and Applications |
| title_fullStr | Recent Advances in Embedded Computing, Intelligence and Applications |
| title_full_unstemmed | Recent Advances in Embedded Computing, Intelligence and Applications |
| title_short | Recent Advances in Embedded Computing, Intelligence and Applications |
| title_sort | recent advances in embedded computing intelligence and applications |
| topic | high-level synthesis HLS SDSoC support vector machines SVM code refactoring Zynq ZedBoard extreme edge embedded edge computing internet of things deployment hardware design IoT security Contiki-NG trustability embedded systems collaborative filtering recommender systems parallelism reconfigurable hardware neuroevolution block-based neural network dynamic and partial reconfiguration scalability reinforcement learning embedded system artificial intelligence hardware acceleration neuromorphic processor power consumption harsh environment fog computing edge computing cloud computing IoT gateway LoRa WiFi low power consumption low latency flexible smart port quantisation evolutionary algorithm neural network FPGA Movidius VPU 2D graphics accelerator line-drawing Bresenham’s algorithm alpha-blending anti-aliasing field-programmable gate array deep learning performance estimation Gaussian process thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| topic_facet | high-level synthesis HLS SDSoC support vector machines SVM code refactoring Zynq ZedBoard extreme edge embedded edge computing internet of things deployment hardware design IoT security Contiki-NG trustability embedded systems collaborative filtering recommender systems parallelism reconfigurable hardware neuroevolution block-based neural network dynamic and partial reconfiguration scalability reinforcement learning embedded system artificial intelligence hardware acceleration neuromorphic processor power consumption harsh environment fog computing edge computing cloud computing IoT gateway LoRa WiFi low power consumption low latency flexible smart port quantisation evolutionary algorithm neural network FPGA Movidius VPU 2D graphics accelerator line-drawing Bresenham’s algorithm alpha-blending anti-aliasing field-programmable gate array deep learning performance estimation Gaussian process thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| url | ONIX_20220621_9783036542461_82 |