sensors-logo

Journal Browser

Journal Browser

Advanced Sensor Technologies for Multimodal Decision-Making

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 741

Special Issue Editor


E-Mail Website
Guest Editor
Department of Artificial Intelligence, Chung-Ang University, Seoul 06974, Republic of Korea
Interests: multi-modal AI; visual-language reasoning; medical AI; computer vision
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The evolution of sensor technologies has created unprecedented opportunities for intelligent systems that can process and integrate information from multiple sensing modalities to enable sophisticated decision-making processes. Modern applications across healthcare, manufacturing, autonomous systems, smart cities, and industrial automation increasingly rely on the fusion of diverse sensor data streams to achieve robust, accurate, and context-aware decisions that surpass the capabilities of single-modal approaches.

This Special Issue explores cutting-edge developments in advanced sensor technologies specifically designed for multimodal decision-making systems. We seek contributions that address the integration of heterogeneous sensor data, real-time processing architectures, and intelligent fusion algorithms that enable autonomous and semi-autonomous systems to make informed decisions in complex environments.

We welcome original research and review articles on topics including, but not limited to, the following:

  • Multimodal sensor fusion algorithms and architectures;
  • Advanced sensing technologies for autonomous systems and robotics;
  • Advanced sensing technologies for healthcare systems;
  • Advanced sensing technologies for smart city systems;
  • AI-driven sensor data interpretation and pattern recognition;
  • Adaptive and self-calibrating sensor systems.

We invite researchers and practitioners to contribute innovative solutions that advance the field of sensor-based intelligent systems and their practical deployment in real-world applications.

Dr. Junyeong Kim
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multimodal sensor fusion
  • multimodal decision making
  • multimodal information interpretation
  • autonomous systems
  • healthcare systems

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

16 pages, 1433 KB  
Article
Intelligent Algorithms for the Detection of Suspicious Transactions in Payment Data Management Systems Based on LSTM Neural Networks
by Abdinabi Mukhamadiyev, Fayzullo Nazarov, Sherzod Yarmatov and Jinsoo Cho
Sensors 2025, 25(21), 6683; https://doi.org/10.3390/s25216683 - 1 Nov 2025
Viewed by 583
Abstract
Today, a number of works are being carried out all over the world to develop data processing and management systems, as well as to apply artificial intelligence and information technologies in the fields of production, science, education, and healthcare. The optimization of the [...] Read more.
Today, a number of works are being carried out all over the world to develop data processing and management systems, as well as to apply artificial intelligence and information technologies in the fields of production, science, education, and healthcare. The optimization of the management of socio-economic process systems, and the management and reliability of databases of the digital payment information-based information systems of enterprises and organizations are relevant. This research work investigates the issue of increasing the reliability of information in information systems working with payment information. The characteristics of ambiguous suspicious transactions in payment systems are analyzed, and based on the analysis, preliminary data preparation stages are carried out for the intelligent detection of ambiguous suspicious transactions. Traditional and neural network models of machine learning for the detection of suspicious transactions in payment information management systems are developed, and a comparative analysis is carried out. Furthermore, to enhance the performance of the core LSTM model, an Artificial Bee Colony (ABC) optimization algorithm was integrated for automated hyperparameter tuning, which improved the model’s accuracy and efficiency in identifying complex fraudulent patterns. Full article
(This article belongs to the Special Issue Advanced Sensor Technologies for Multimodal Decision-Making)
Show Figures

Figure 1

Back to TopTop