Next Article in Journal
Deep-Learning-Based Frame Format Detection for IEEE 802.11 Wireless Local Area Networks
Previous Article in Journal
Measuring the Impact of Accurate Feature Selection on the Performance of RBM in Comparison to State of the Art Machine Learning Algorithms
Previous Article in Special Issue
Exploiting Recurring Patterns to Improve Scalability of Parking Availability Prediction Systems

Intellino: Processor for Embedded Artificial Intelligence

Department of Electronic Engineering, Seoul National University of Science and Technology, Seoul 01811, Korea
Author to whom correspondence should be addressed.
Electronics 2020, 9(7), 1169;
Received: 8 June 2020 / Revised: 16 July 2020 / Accepted: 16 July 2020 / Published: 18 July 2020
(This article belongs to the Special Issue Recent Machine Learning Applications to Internet of Things (IoT))
The development of computation technology and artificial intelligence (AI) field brings about AI to be applied to various system. In addition, the research on hardware-based AI processors leads to the minimization of AI devices. By adapting the AI device to the edge of internet of things (IoT), the system can perform AI operation promptly on the edge and reduce the workload of the system core. As the edge is influenced by the characteristics of the embedded system, implementing hardware which operates with low power in restricted resources on a processor is necessary. In this paper, we propose the intellino, a processor for embedded artificial intelligence. Intellino ensures low power operation based on optimized AI algorithms and reduces the workload of the system core through the hardware implementation of a neural network. In addition, intellino’s dedicated protocol helps the embedded system to enhance the performance. We measure intellino performance, achieving over 95% accuracy, and verify our proposal with an field programmable gate array (FPGA) prototyping. View Full-Text
Keywords: AI processor; internet of things; machine learning; embedded system; low power AI processor; internet of things; machine learning; embedded system; low power
Show Figures

Figure 1

MDPI and ACS Style

Yoon, Y.H.; Hwang, D.H.; Yang, J.H.; Lee, S.E. Intellino: Processor for Embedded Artificial Intelligence. Electronics 2020, 9, 1169.

AMA Style

Yoon YH, Hwang DH, Yang JH, Lee SE. Intellino: Processor for Embedded Artificial Intelligence. Electronics. 2020; 9(7):1169.

Chicago/Turabian Style

Yoon, Young Hyun, Dong Hyun Hwang, Jun Hyeok Yang, and Seung Eun Lee. 2020. "Intellino: Processor for Embedded Artificial Intelligence" Electronics 9, no. 7: 1169.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop