JST — Smart Systems and Devices is an Open Access, peer-reviewed, English-language scholarly journal published three times annually — in January, May, and September. The journal highlights recent advances and original research in intelligent automation, sensor technologies, and interconnected smart systems.

Key topics of interest include smart cities, smart grids, and the Internet of Things (IoT); unmanned aerial vehicle (UAV) robotics and control; advanced materials for sensor applications; artificial intelligence (AI) and computational optimization techniques; as well as smart healthcare devices and systems.

The journal places particular emphasis on the integration of hardware, software, and communication technologies to enable intelligent decision-making and automation across diverse domains.

JST — Smart Systems and Devices aims to provide a focused platform for academic researchers, engineers, and practitioners to share innovative solutions, theoretical insights, and practical implementations that advance the state of the art in smart, interconnected technologies.

The journal is published by Hanoi University of Science and Technology, Bach Khoa Publishing House for the printed version, with editorial leadership provided by an international board of experts. All manuscripts submitted to the journal undergo a rigorous peer-review process to ensure high standards of scholarly quality, technical accuracy, and scientific contribution.

View full Aims and scope

Publishing timeline

1.45 days
Time to first decision
4.14 authors
Average number of authors per article
78.23 days
Submission to acceptance
4.00 days
Acceptance to publication

Vol. 36 No. 1 (2026): Journal of Science and Technology - Smart Systems and Devices (01/2026)

Date Published: 15/01/2026

Table of Contents

Research article

An IoT System to Measure and Detect Foreign Object Debris (FOD)on Airport Runways Using AI and Computer Vision
Hiep Nguyen-Hoang, Quyen Nguyen-Van, Vinh Tran-Quang
PDF Cite
Page: 001-008
UAV-to-Satellite Communication for 6G IoV Networks Using Beamforming Orthogonal Time Frequency Space: A Deep Q-Learning Approach
Nguyen Huu Trung
PDF Cite
Page: 009-017
Static Hand Gesture Recognition Using a Low-Cost Data Glove and Bayesian Neural Network
Son T. Nguyen, Tu M. Pham, Anh Hoang, Trung T. Cao, Quang M. Tran
PDF Cite
Page: 018-024
View All