Emerging Hyper Automation + Human AI Technologies including Selected Papers from ICGHIT 2023

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 3383

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Department of Software and Communications Energy, Hongik University, Sejongro 2639, Republic of Korea
Interests: wireless networks and communications; WSN; wireless ICN; edge computing
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Special Issue Information

Dear Colleagues,

The 11th International Conference on Green and Human Information Technology (ICGHIT 2023) will be held 31~02 February, 2023, in Bangkok, Thailand (http://icghit.org/ ).

The 11th International Conference on Green and Human Information Technology is a unique global conference for researchers, industry professionals, and academics who are interested in the latest development of green and human information technology. The main theme of ICGHIT in this year is “Emerging Hyper Automation + Human AI technology” which means the emerging automation or AI technologies applied to any applied science area such as network, signal processing, circuit, telecommunications, etc. The latest technologies of Human AI are already pervading our daily personal life regardless of our recognition. They give us big challenges and great opportunities at the same time.

Centering on the main theme, ICGHIT will provide an exciting program: hands-on experience-based tutorial sessions and special sessions covering research issues & directions with applications from both theoretical and practical viewpoints. The conference will also include plenary sessions, technical sessions, and workshops with special sessions.

Highly qualified papers selected from ICGHIT 2023 will be invited to submit to this Special Issue for publication. However, the Special Issue also welcomes to accept submissions from general researchers which fit into the scope of the SI as shown below. 

The topics of this Special Issue include, but are not limited to:

Green Information Technology

  • Green Technology & Energy Saving
  • Green Computing & Green IT Convergence and Applications
  • Energy Harvest-based Communications & Networking
  • Technologies for Network Sustainability

Communications & Networks for IoT and 5G & Beyond.

  • Communications & Networks for Massive IoT & 5G
  • Optical & Visual Light Communication
  • Ad hoc & Sensor Networks
  • M2M/IoT & Ubiquitous Computing
  • NFV, SDN, ICN, Network Slicing
  • AI and ML-based Technologies

Computer and Network Security

  • Block-Chain-based Networking & Applications
  • Distributed PKI
  • Applied Cryptography
  • Security in Big Data and Cloud Computing
  • Security for Future Internet Architecture (SDN, ICN, etc.)

Control and Intelligent System

  • Automatic Control & Neural Network and Fuzzy
  • Artificial Intelligence & HCI
  • Intelligent Robotics and Transportation & HRI
  • Brain Science and Bioengineering

Network SW/HW Design, Architecture & Applications

  • Architecture & Protocols
  • Sustainable Sensor Networks
  • Information-centric Sensor Networks
  • Blockchain-based Secure Sensor Networks
  • AI-based Self-evolving Sensor networks
  • Sensor/RFID Circuit Design
  • System on Chip (SoC)
  • IC System for Communication

Dr. Byung-Seo Kim
Guest Editor

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Published Papers (1 paper)

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23 pages, 28478 KiB  
Article
Blind Spot Detection Radar System Design for Safe Driving of Smart Vehicles
by Wantae Kim, Heejin Yang and Jinhong Kim
Appl. Sci. 2023, 13(10), 6147; https://doi.org/10.3390/app13106147 - 17 May 2023
Cited by 2 | Viewed by 2781
Abstract
Recently, there has been extensive research and development in the field of smart cars, including technologies related to autonomous driving. Various industries are actively working towards creating efficient and safe self-driving cars. Sensor technologies are emerging to prevent traffic accidents and support safe [...] Read more.
Recently, there has been extensive research and development in the field of smart cars, including technologies related to autonomous driving. Various industries are actively working towards creating efficient and safe self-driving cars. Sensor technologies are emerging to prevent traffic accidents and support safe driving in complex environments where human perception may be limited. One of the representative technologies being researched is the use of Frequency Modulated Continuous Wave (FMCW) radar. Automobile manufacturers are improving driving safety by equipping cars with Blind Spot Detection (BSD) radar systems that use FMCW technology. As the complexity of driving environments continues to grow, ongoing research is aimed at enhancing the accuracy and reliability of BSD radar technology for detecting blind spots in vehicles. This paper presents the signal processing and tracking algorithms that are the core technologies of the BSD radar, and the design for a BSD radar system. The designed radar system was installed on a vehicle to verify its performance in real-world road environments. The ultimate objective of this research is to design a BSD radar system with high accuracy and reliability in BSD detection using AI technology. In pursuit of this goal, this paper presents the hardware design of the BSD radar system, including antenna and modem designs. Full article
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