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Electronic Communications, IOT and Big Data, 2nd Volume
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Department of Electronic Engineering, National Formosa University, Yunlin City 632, Taiwan
Laboratoire des Usages en Technologies d’Information Numériques, Lutin, France
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan
Department of Recreation and Health Care Management, Chia Nan University of Pharmacy & Science, Tainan City 71710, Taiwan
Department of Electrical Engineering, Lunghwa University of Science and Technology, Taoyuan 333, Taiwan
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Electronic Communications, IOT and Big Data, 2nd Volume

Abstract submission deadline
31 December 2025
Manuscript submission deadline
31 March 2026
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Topic Information

Dear Colleagues,

The 2025 IEEE 4th International Conference on Electronic Communications, Internet of Things and Big Data will be held at Tamkang University, Taipei, Taiwan from April 25 to 27, 2025. It will provide a platform for high-tech personnel and researchers in the topics of Electronic Communications, Internet of Things and Big Data to discuss their research and recent developments in the field The booming economic development in Asia, especially the advanced technology in the fields of Electronic Communications, Internet of Things and Big Data, has attracted significant attention from many universities, research institutions and companies. The focus of this conference will be on research that presents innovative ideas or results and practical applications. The topics of interest are as follows:

I. Big Data and Cloud Computing

  1. Models and Algorithms of Big Data
  2. Architecture of Big Data
  3. Big Data Management
  4. Big Data Analysis and Processing
  5. Security and Privacy of Big Data
  6. Big Data in Smart Cities
  7. Search, Mining and Visualization of Big Data
  8. Technologies, Services and Application of Big Data
  9. Edge Computing
  10. Architectures and Systems of Cloud Computing
  11. Models, Simulations, Designs, and Paradigms of Cloud Computing
  12. Management and Operations of Cloud Computing
  13. Technologies, Services and Applications of Cloud Computing
  14. Dynamic Resource Supply and Consumption
  15. Management and Analysis of Geospatial Big Data
  16. UAV Oblique Photography and Ground 3D Real-scene Modeling
  17. Aerial Photography of UAV loaded with Multispectral Sensors
  18. Medical Informatics and Healthcare Engineering

II. Technologies and Application of Artificial Intelligence

  1. Basic Theory and Application of Artificial Intelligence
  2. Knowledge Science and Knowledge Engineering
  3. Machine Learning and Data Mining
  4. Machine Perception and Virtual Reality
  5. Natural Language Processing and Understanding
  6. Neural Network and Deep Learning
  7. Pattern Recognition Theory and Application
  8. Rough Set and Soft Computing
  9. Biometric Identification
  10. Computer Vision and Image Processing
  11. Evolutionary Calculation
  12. Information Retrieval and Web Search
  13. Intelligent Planning and Scheduling
  14. Intelligent Control
  15. Classification and Change Detection of Remote Sensing Images or Aerial Images
  16. Computer and Software Application

III. Robotics Science and Engineering

  1. Robot control
  2. Mobile robotics
  3. Intelligent pension robots
  4. Mobile sensor networks
  5. Perception systems
  6. Micro robots and micro-manipulation
  7. Visual serving
  8. Search, rescue and field robotics
  9. Robot sensing and data fusion
  10. Indoor localization and navigation
  11. Dexterous manipulation
  12. Medical robots and bio-robotics
  13. Human-centered systems
  14. Space and underwater robots
  15. Tele-robotics

IV. Internet of Things and Sensor Technology

  1. Technology architecture of Internet of Things
  2. Sensors in Internet of Things
  3. Perception technology of Internet of Things information
  4. Multi-terminal cooperative control and Internet of Things intelligent terminal
  5. Multi-network resource sharing in the environment of Internet of Things
  6. Heterogeneous fusion and multi-domain collaboration in the Internet of Things environment 
  7. SDN and intelligent service network
  8. Technology and its application in the Internet of Things
  9. Cloud computing and big data in the Internet of Things
  10. Information analysis and processing of Internet of Things
  11. CPS technology and intelligent information system
  12. Internet of Things technology standard
  13. Internet of Things information security
  14. Narrow Band Internet of Things (NB-IoT)
  15. Smart cities
  16. Smart farming
  17. Smart grids
  18. Digital health/telehealth/telemedicine

V. Electronic and Electrical Engineering

  1. Bioengineering
  2. Communication, Networking and Broadcasting
  3. Components, Circuits, Devices and Systems
  4. Computing and Processing
  5. Engineered Materials, Dielectrics and Plasmas
  6. Engineering Profession
  7. Fields, Waves and Electromagnetics
  8. General Topics for Engineers (Math, Science and Engineering)
  9. Geoscience
  10. Photonics and Electro-Optics
  11. Power, Energy and Industry Applications
  12. Signal Processing and Analysis

VI. Big Data and AI Technologies on Civil and Architecture Engineering

  1. Green Architecture
  2. Ecological Architecture
  3. Building Energy Management
  4. Building Information Modeling
  5. Architectural Environment and Equipment Engineering
  6. Green Building Materials
  7. IOT/Smart Buildings
  8. Digital Architecture
  9. Civil Engineering and Engineering Management
  10. Advanced Construction Technology
  11. Innovative Construction and Development
  12. Digital Construction

VII. Big Data and AI Technologies on Environmental Engineering and Geographic Information 

  1. Environmental Monitoring and Control
  2. Environmental Planning and Assessment
  3. Environmental Protection
  4. Environmental Sustainability
  5. Environmental Safety and Health
  6. Biomedical Engineering
  7. Geographic Information and Remote Sensing Science
  8. Geographic Information System Application

Prof. Dr. Teen-­Hang Meen
Prof. Dr. Charles Tijus
Prof. Dr. Cheng-Chien Kuo
Prof. Dr. Kuei-Shu Hsu
Prof. Dr. Jih-Fu Tu
Topic Editors

Keywords

  • electronic communications
  • big data and cloud computing
  • technologies and application of artificial intelligence
  • robotics science and engineering
  • internet of things and sensor technology

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci 		2.5 5.3 2011 18.4 Days CHF 2400 Submit
Computers
computers 		2.6 5.4 2012 15.5 Days CHF 1800 Submit
Journal of Sensor and Actuator Networks
jsan 		3.3 7.9 2012 19 Days CHF 2000 Submit
Technologies
technologies 		4.2 6.7 2013 21.1 Days CHF 1600 Submit
Big Data and Cognitive Computing
BDCC 		3.7 7.1 2017 25.3 Days CHF 1800 Submit
Sensors
sensors 		3.4 7.3 2001 18.6 Days CHF 2600 Submit
Telecom
telecom 		2.1 4.8 2020 20.5 Days CHF 1200 Submit
Electronics
electronics 		2.6 5.3 2012 16.4 Days CHF 2400 Submit

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Published Papers (4 papers)

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26 pages, 5688 KiB  
Article
Image-Based Nutritional Advisory System: Employing Multimodal Deep Learning for Food Classification and Nutritional Analysis
by Sheng-Tzong Cheng, Ya-Jin Lyu and Ching Teng
Appl. Sci. 2025, 15(9), 4911; https://doi.org/10.3390/app15094911 - 28 Apr 2025
Viewed by 65
Abstract
Accurate dietary assessment is essential for effective health management and disease prevention. However, conventional methods that rely on manual food logging and nutritional lookup are often time consuming and error prone. This study proposes an image-based nutritional advisory system that integrates multimodal deep [...] Read more.
Accurate dietary assessment is essential for effective health management and disease prevention. However, conventional methods that rely on manual food logging and nutritional lookup are often time consuming and error prone. This study proposes an image-based nutritional advisory system that integrates multimodal deep learning to automate food classification, volume estimation, and dietary recommendation to address these limitations. The system employs a fine-tuned CLIP model for zero-shot food recognition, achieving high accuracy across diverse food categories, including unseen items. For volume measurement, a learning-based multi-view stereo (MVS) approach eliminates the need for specialized hardware, yielding reliable estimations with a mean absolute percentage error (MAPE) of 23.5% across standard food categories. Nutritional values are then calculated by referencing verified food composition databases. Furthermore, the system leverages a large language model (Llama 3) to generate personalized dietary advice tailored to individual health goals. The experimental results show that the system attains a top 1 classification accuracy of 91% on CNFOOD-241 and 80% on Food 101 and delivers high-quality recommendation texts with a BLEU-4 score of 45.13. These findings demonstrate the system’s potential as a practical and scalable tool for automated dietary management, offering improved precision, convenience, and user experience. Full article
(This article belongs to the Topic Electronic Communications, IOT and Big Data, 2nd Volume)
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17 pages, 428 KiB  
Article
Dynamic UAV Task Allocation and Path Planning with Energy Management Using Adaptive PSO in Rolling Horizon Framework
by Zhen Han and Weian Guo
Appl. Sci. 2025, 15(8), 4220; https://doi.org/10.3390/app15084220 - 11 Apr 2025
Viewed by 250
Abstract
Unmanned aerial vehicles (UAVs) are increasingly deployed in dynamic environments for applications such as surveillance, delivery, and data collection, where efficient task allocation and path planning are critical to minimizing mission completion time while managing limited energy resources. This paper proposes a novel [...] Read more.
Unmanned aerial vehicles (UAVs) are increasingly deployed in dynamic environments for applications such as surveillance, delivery, and data collection, where efficient task allocation and path planning are critical to minimizing mission completion time while managing limited energy resources. This paper proposes a novel approach that integrates energy management into a rolling horizon framework for dynamic UAV task allocation and path planning. We introduce an enhanced Particle Swarm Optimization (PSO) algorithm, incorporating adaptive perturbation strategies and a local search mechanism based on simulated annealing, to optimize UAV task assignments and routes. The rolling horizon framework enables the system to adapt to evolving task demands over time. Energy consumption is explicitly modeled, accounting for flight, computation, and recharging at designated stations, ensuring practical applicability. Extensive simulations demonstrate that the proposed method reduces the mission makespan significantly compared to conventional static planning approaches, while effectively balancing energy usage and recharging requirements. These results highlight the potential of our approach for real-world UAV operations in dynamic settings. Full article
(This article belongs to the Topic Electronic Communications, IOT and Big Data, 2nd Volume)
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21 pages, 5795 KiB  
Article
Design and Implementation of a Tripod Robot Control System Using Hand Kinematics and a Sensory Glove
by Jakub Krzus, Tomasz Trawiński, Paweł Kielan and Marcin Szczygieł
Electronics 2025, 14(6), 1150; https://doi.org/10.3390/electronics14061150 - 14 Mar 2025
Viewed by 385
Abstract
Current technological progress in automation and robotics allows human kinematics to be used to control any device. As part of this study, a sensory glove was developed that allows for a delta robot to be controlled using hand movements. The process of controlling [...] Read more.
Current technological progress in automation and robotics allows human kinematics to be used to control any device. As part of this study, a sensory glove was developed that allows for a delta robot to be controlled using hand movements. The process of controlling an actuator can often be problematic due to its complexity. The proposed system solves this problem using human–machine interactions. The sensory glove allows for easy control of the robot by detecting the rotation of the hand and pressing the control buttons. Conventional buttons have been replaced with SMART materials such as conductive thread and conductive fabric. The ESP32 microcontroller placed on the control glove collects data read from the MPU6050 sensor. It also facilitates wireless communication with the Raspberry Pi microcontroller supporting the Modbus TCP/IP protocol, which controls the robot’s movement. Due to the noise of the data read from the gyroscope, the signals were subjected to a filtering process using basic recursive filters and an advanced algorithm with Kalman filters. Full article
(This article belongs to the Topic Electronic Communications, IOT and Big Data, 2nd Volume)
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28 pages, 2405 KiB  
Article
Global Optimal Automatic Generation Control of a Multimachine Power System Using Hybrid NLMPC and Data-Driven Methods
by Ahmed Khamees and Hüseyin Altınkaya
Appl. Sci. 2025, 15(4), 1956; https://doi.org/10.3390/app15041956 - 13 Feb 2025
Viewed by 498
Abstract
Real-world power systems face challenges from demand fluctuations, system constraints, communication delays, and unmeasurable disturbances. This paper presents a real-time hybrid approach integrating Nonlinear Model Predictive Control (NLMPC) and data-driven methods for automatic generation control (AGC) of synchronous generators, particularly under cyber-physical attacks. [...] Read more.
Real-world power systems face challenges from demand fluctuations, system constraints, communication delays, and unmeasurable disturbances. This paper presents a real-time hybrid approach integrating Nonlinear Model Predictive Control (NLMPC) and data-driven methods for automatic generation control (AGC) of synchronous generators, particularly under cyber-physical attacks. Unlike previous studies, this work considers both technical and economic aspects of power system management. A key innovation is the incorporation of a detailed thermo-mechanical model of turbine and governor dynamics, enabling optimized control and effective management of power oscillations. The proposed NLMPC-based AGC strategy addresses governor saturation and generation rate constraints, ensuring stability. Extensive simulations in MATLAB/Simulink, including IEEE 11-bus and 9-bus test systems, validate the controller’s effectiveness in enhancing power system performance under various challenging conditions. Full article
(This article belongs to the Topic Electronic Communications, IOT and Big Data, 2nd Volume)
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