Volume 2, Issue 2


New Publisher’s Prefix and Title: ICCK Transactions on Sensing, Communication, and Control

Volume 2, Issue 2 (June, 2025) – 6 articles
Citations: Crossref logo 44,   46   |   Viewed: 27944, Download: 4693

Table of Contents

Free Access | Research Article | 30 June 2025 | Cited: Crossref logo  9 , Scopus 11
IoT-Enabled Food Freshness Detection Using Multi-Sensor Data Fusion and Mobile Sensing Interface
ICCK Transactions on Sensing, Communication, and Control | Volume 2, Issue 2: 122-131, 2025 | DOI: 10.62762/TSCC.2025.401245
Abstract
Ensuring the freshness of food products is essential for both acute and chronic health outcomes. However, significant health risks can be triggered by dietary resources subjected to improper storage protocols. Current methods are often unreliable and infeasible for detecting food freshness. This research proposes an IoT-based food freshness detection system that integrates a suite of electrochemical and gas sensors-including pH, moisture, and ethanol sensors-to assess food freshness and reduce health risks associated with spoilage in perishable items like meat, produce, and dairy. The system is integrated with a mobile application that allows users to analyze food quality in real-time, bas... More >

Graphical Abstract
IoT-Enabled Food Freshness Detection Using Multi-Sensor Data Fusion and Mobile Sensing Interface
Free Access | Research Article | 19 May 2025 | Cited: Crossref logo  16 , Scopus 18
Optimizing Cloud Security with a Hybrid BiLSTM-BiGRU Model for Efficient Intrusion Detection
ICCK Transactions on Sensing, Communication, and Control | Volume 2, Issue 2: 106-121, 2025 | DOI: 10.62762/TSCC.2024.433246
Abstract
To address evolving security challenges in cloud computing, this study proposes a hybrid deep learning architecture integrating Bidirectional Long Short-Term Memory (BiLSTM) and Bidirectional Gated Recurrent Units (BiGRU) for cloud intrusion detection. The BiLSTM-BiGRU model synergizes BiLSTM's long-term dependency modeling with BiGRU's efficient gating mechanisms, achieving a detection accuracy of 96.7% on the CIC-IDS 2018 dataset. It outperforms CNN-LSTM baselines by 2.2% accuracy, 3.3% precision, 3.6% recall, and 3.6% F1-score, demonstrating consistently superior performance across all evaluation metrics. The architecture demonstrates operational efficiency through 20% reduced computation... More >

Graphical Abstract
Optimizing Cloud Security with a Hybrid BiLSTM-BiGRU Model for Efficient Intrusion Detection
Free Access | Research Article | 18 May 2025 | Cited: Crossref logo  2 , Scopus 1
Computational Experimental Test on PID Controlled Fixed Wing Aircraft Systems
ICCK Transactions on Sensing, Communication, and Control | Volume 2, Issue 2: 95-105, 2025 | DOI: 10.62762/TSCC.2025.731885
Abstract
This paper focuses on the implementation of a control framework for a fixed wing aircraft system and the simulation demonstrations. The aim is to develop several Proportional Integral Derivative (PID) controllers to stabilise the altitude and attitude in a 2D environment by regulating the engine power, the pitch angle, and height in flight operation. In technique, a dynamic mathematical model is established by considering the degrees of freedom and the dynamics of motion of a fixed wing aircraft, which provide a foundation for design and simulation. A simplified aircraft dynamic model is tailored for testing the formed control systems, which can be flexibly modified with different aircraft c... More >

Graphical Abstract
Computational Experimental Test on PID Controlled Fixed Wing Aircraft Systems
Free Access | Research Article | 08 May 2025 | Cited: Crossref logo  2 , Scopus 2
3D Holography Advertisement On Vehicle Using IoT
ICCK Transactions on Sensing, Communication, and Control | Volume 2, Issue 2: 85-94, 2025 | DOI: 10.62762/TSCC.2024.554721
Abstract
3D holographic displays on vehicles are a new out-of-home (OOH) advertisement technology offering an interactive and dynamic means of engaging consumers. They enhance advertisement visibility and viewer interaction through the projection of colorful, three-dimensional images in public areas. An Internet of Things (IoT) based holographic advertisement system is presented, integrating remote content management and personalized advertising control. The system includes an Android application that allows users to select and schedule ads displayed on moving vehicles. A GPS module provides real-time vehicle tracking, supporting security and targeted advertisements. Cloud-based storage ensures remot... More >

Graphical Abstract
3D Holography Advertisement On Vehicle Using IoT
Free Access | Research Article | 30 April 2025 | Cited: Crossref logo  3 , Scopus 3
Parameter Estimation for the Tuned Liquid Damper Model Based on Robust Extended Kalman Filter
ICCK Transactions on Sensing, Communication, and Control | Volume 2, Issue 2: 75-84, 2025 | DOI: 10.62762/TSCC.2025.663633
Abstract
The Tuned Liquid Damper (TLD) method offers a practical and cost-effective solution for seismic design. Accurate modeling of the TLD system’s dynamic behavior is crucial for optimizing its performance. In this study, the nonlinear dynamics of the TLD system are characterized using the Housner model, with parameters estimated via a nonlinear state estimation approach. To address challenges associated with model discretization and unknown noise processes, we introduce a Robust Extended Kalman Filter (REKF) that incrementally incorporates uncertainties to more accurately capture system dynamics. The proposed method is evaluated through real-time hybrid simulation, employing seismic input sign... More >

Graphical Abstract
Parameter Estimation for the Tuned Liquid Damper Model Based on Robust Extended Kalman Filter
Free Access | Research Article | 15 April 2025 | Cited: Crossref logo  12 , Scopus 11
Smart Ground Robot for Real-Time Detection of Tomato Diseases Using Deep Learning and IoT Technologies
ICCK Transactions on Sensing, Communication, and Control | Volume 2, Issue 2: 66-74, 2025 | DOI: 10.62762/TSCC.2024.593301
Abstract
This study presents an intelligent automated system for real-time detection and classification of tomato diseases using a Convolutional Neural Network (CNN) integrated within an Internet of Things (IoT) based unmanned ground vehicle (UGV). The CNN was trained and evaluated using a dataset comprising over 20,000 images of tomato leaves categorized into ten distinct diseases—Late Blight, Early Blight, Septoria Leaf Spot, Tomato Yellow Leaf Curl Virus, Bacterial Spot, Target Spot, Tomato Mosaic Virus, Leaf Mold, Spider Mites Two-Spotted Spider Mite, Powdery Mildew—and healthy leaves. The developed CNN architecture, optimized for lightweight deployment on edge devices like Raspberry Pi 4, ac... More >

Graphical Abstract
Smart Ground Robot for Real-Time Detection of Tomato Diseases Using Deep Learning and IoT Technologies