International Journal of Sensor Networks
- Editor in Chief
- Prof. Yang Xiao
- ISSN online
- ISSN print
- 12 issues per year
- Impact factor (Clarivate Analytics) 2023 1.1 (5 Year Impact Factor 0.9)
- CiteScore 2.3 (2022)
IJSNet proposes and fosters discussion on and dissemination of issues related to research and applications of distributed and wireless/wired sensor and actuator networks. Sensor networks is an interdisciplinary field including many fields such as wireless networks and communications, protocols, distributed algorithms, signal processing, embedded systems, and information management.
Topics covered include
- Energy efficiency, energy efficient protocols
- Location techniques, routing, medium access control
- Coverage, connectivity, longevity, scheduling, synchronisation
- Network resource management, network protocols, lightweight protocols
- Fault tolerance/diagnostics
- Data storage, query processing, system architectures, operating systems
- In-network processing and aggregation
- Learning of models from data
- Performance analysis
- Sensor tasking and control
- Security, privacy, data integrity
- Modelling of systems/physical environments, simulation tools/environments
The objectives of IJSNet are to establish an effective channel of communication between industry, government agencies, academic and research institutions and persons concerned with related problems in sensor networks. It also aims to promote and coordinate developments in the field of sensor networks.
IJSNet provides a vehicle to help professionals, academics, researchers, developers, working in the field of sensor networks to disseminate information and to learn from each other's work.
IJSNet publishes original papers, short papers, and review papers. Special Issues devoted to important topics in sensor networks will also be published.
IJSNET is indexed in:
- Journal Citation Reports (Clarivate Analytics)
- Scopus (Elsevier)
- Compendex [formerly Ei] (Elsevier)
- Science Citation Index Expanded (Clarivate Analytics)
- Academic OneFile (Gale)
- ACM Digital Library
- cnpLINKer (CNPIEC)
- DBLP Computer Science Bibliography
- Google Scholar
- Info Trac (Gale)
- Inspec (Institution of Engineering and Technology)
- io-port (FIZ Karlsruhe)
IJSNET is listed in:More journal lists/directories...
Editor in Chief
- Xiao, Yang, University of Alabama, USA
- Hossain, Ekram, University of Manitoba, Canada
- Tseng, Yu-Chee, National Chiao Tung University, Taiwan, Province of China
Editorial Board Members
- Abawajy, Jemal, Deakin University, Australia
- Cai, Zhipeng, Georgia State University, USA
- Chen, Hsiao-Hwa, National Cheng Kung University, Taiwan, Province of China
- Chen, Hui, Virginia State University , USA
- Chen, Zesheng, Purdue University Fort Wayne, USA
- Cheng, Maggie, New Jersey Institute of Technology, USA
- Cheng, Xiuzhen (Susan), The George Washington University, USA
- Coll-Perales, Baldomero, Universidad Miguel Hernández de Elche, Spain
- Douligeris, Christos, University of Piraeus, Greece
- Du, Ding-zhu, University of Texas at Dallas, USA
- Duan, Qiang, Pennsylvania State University, USA
- Elmallah, Ehab S., University of Alberta, Canada
- Erbad, Aiman, Hamad Bin Khalifa University, Qatar
- Fei, Zongming, University of Kentucky, USA
- Guizani, Mohsen, University of Idaho, USA
- Guizani, Sghaier, Alfaisal University, Saudi Arabia
- Gupta, Nitin, National Institute of Technology, Hamirpur, India
- Jian, Mao, Beihang University, China
- Leung, Kin K., Imperial College, UK
- Leung, Victor C. M., The University of British Columbia, Canada
- Li, Wei, Texas Southern University, USA
- Lin, Jason Yi-Bing, National Chiao Tung University, Taiwan, Province of China
- Lloret Mauri, Jaime, Polytechnic University of Valencia, Spain
- Lv, Zhihan, Qingdao University, China
- Malekian, Reza, University of Pretoria, South Africa
- Misic, Jelena, Ryerson University, Canada
- Mohamed, Amr M., Qatar University, Qatar
- Nayyar, Anand, Duy Tan University, Vietnam
- Nijim, Mais W., Texas A&M University-Kingsville, USA
- Pathan, Al-Sakib Khan, United International University, Bangladesh
- Raptis, Theofanis, National Research Council, Italy
- Shen, Xuemin, University of Waterloo, Canada
- Shi, Weisong, Wayne State University, USA
- Sun, Bo, Lamar University , USA
- Sun, Wei, Hefei University of Technology, China
- Wang, Shengling, Beijing Normal University , China
- Wang, Xiaoyan, Ibaraki University, Japan
- Wu, Jie, Temple University, USA
- Xia, Xiaofang, Xidian University, China
- Xu, Shengjie, San Diego State University, USA
- Xue, Guoliang, Arizona State University, USA
- Yang, Jie, Florida State University, USA
- Yu, Jiguo, Qufu Normal University, China
- Yuan, Xiaojing, University of Houston, USA
- Zhang, Jingyuan (Alex), University of Alabama, USA
- Znati, Taieb, University of Pittsburgh, USA
- Zonta, Daniele, University of Trento, Italy
- Zorzi, Michele, Universita' di Ferrara, Italy
A few essentials for publishing in this journal
- Submitted articles should not have been previously published or be currently under consideration for publication elsewhere.
- Conference papers may only be submitted if the paper has been completely re-written (more details available here) and the author has cleared any necessary permissions with the copyright owner if it has been previously copyrighted.
- Briefs and research notes are not published in this journal.
- All our articles go through a double-blind review process.
- All authors must declare they have read and agreed to the content of the submitted article. A full statement of our Ethical Guidelines for Authors (PDF) is available.
- There are no charges for publishing with Inderscience, unless you require your article to be Open Access (OA). You can find more information on OA here.
- All articles for this journal must be submitted using our online submissions system.
- View Author guidelines.
AI unmasks PPE failures
4 April, 2023
Writing in the International Journal of Sensor Networks, a team from China has developed a system based on machine learning that can detect whether personnel are wearing the requisite PPE. The approach uses deep neural networks (DNNs) to carry out object detection in real scenarios. Jianlou Lou, Xiangyu Li, Guang Huo, Feng Liang, Zhaoyang Qu, and Ndagijimana Kwihangano Soleil of the Northeast Electric Power University in Jilin and Tianrui Lou of Guangzhou University have used two novel modules, the Deformable and Attention Residual with 50 layers (DAR50) feature extraction module, and the Criss-Cross Feature Pyramid Network (CCFPN) feature fusion module, in order to address the two key problems that have so far limited performance in PPE detection. They have thus overcome the issues of interference from background information and detection target scales that vary in size [...]More details...