Ayman Noor^1,2, Hanan Almukhalfi^1,2, Arthur Souza^2,3, Talal H. Noor^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3085-3111, 2025, DOI:10.32604/cmes.2025.068393 - 30 September 2025

Abstract People with visual impairments face substantial navigation difficulties in residential and unfamiliar indoor spaces. Neither canes nor verbal navigation systems possess adequate features to deliver real-time spatial awareness to users. This research work represents a feasibility study for the wearable IoT-based indoor object detection assistant system architecture that employs a real-time indoor object detection approach to help visually impaired users recognize indoor objects. The system architecture includes four main layers: Wearable Internet of Things (IoT), Network, Cloud, and Indoor Object Detection Layers. The wearable hardware prototype is assembled using a Raspberry Pi 4, while the… More >

Anjie Wang^1,2, Haining Jiao^1,2,*, Zhichao Chen^1,2,*, Jie Yang^1,2

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5773-5790, 2025, DOI:10.32604/cmc.2025.066852 - 30 July 2025

Abstract With the rapid development of the Internet of Things (IoT), artificial intelligence, and big data, waste-sorting systems must balance high accuracy, low latency, and resource efficiency. This paper presents an edge-friendly intelligent waste-sorting system that integrates a lightweight visual neural network, a pentagonal-trajectory robotic arm, and IoT connectivity to meet the requirements of real-time response and high accuracy. A lightweight object detection model, YOLO-WasNet (You Only Look Once for Waste Sorting Network), is proposed to optimize performance on edge devices. YOLO-WasNet adopts a lightweight backbone, applies Spatial Pyramid Pooling-Fast (SPPF) and Convolutional Block Attention Module… More >

Doaa Sami Khafaga¹, Sarah M. Alhammad^1,*, Amal Magdi², Osama ElKomy², Nabil A. Lashin², Khalid M. Hosny²

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1967-1986, 2023, DOI:10.32604/csse.2023.040345 - 28 July 2023

Abstract Image authentication techniques have recently received a lot of attention for protecting images against unauthorized access. Due to the wide use of the Internet nowadays, the need to ensure data integrity and authentication increases. Many techniques, such as watermarking and encryption, are used for securing images transmitted via the Internet. The majority of watermarking systems are PC-based, but they are not very portable. Hardware-based watermarking methods need to be developed to accommodate real-time applications and provide portability. This paper presents hybrid data security techniques using a zero watermarking method to provide copyright protection for the… More >

Turki M. Alanazi^*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3343-3354, 2023, DOI:10.32604/iasc.2023.036411 - 15 March 2023

Abstract Detecting and recognizing text from natural scene images presents a challenge because the image quality depends on the conditions in which the image is captured, such as viewing angles, blurring, sensor noise, etc. However, in this paper, a prototype for text detection and recognition from natural scene images is proposed. This prototype is based on the Raspberry Pi 4 and the Universal Serial Bus (USB) camera and embedded our text detection and recognition model, which was developed using the Python language. Our model is based on the deep learning text detector model through the Efficient… More >

G. Arunachalam^1,*, P. SureshKumar²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1279-1294, 2023, DOI:10.32604/csse.2023.031001 - 03 November 2022

Abstract The main components of Cognitive Radio networks are Primary Users (PU) and Secondary Users (SU). The most essential method used in Cognitive networks is Spectrum Sensing, which detects the spectrum band and opportunistically accesses the free white areas for different users. Exploiting the free spaces helps to increase the spectrum efficiency. But the existing spectrum sensing techniques such as energy detectors, cyclo-stationary detectors suffer from various problems such as complexity, non-responsive behaviors under low Signal to Noise Ratio (SNR) and computational overhead, which affects the performance of the sensing accuracy. Many algorithms such as Long-Short… More >

Thien Khai Tran¹, Kha Tu Huynh^2,*, Dac-Nhuong Le³, Muhammad Arif⁴, Hoa Minh Dinh¹

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2479-2491, 2023, DOI:10.32604/iasc.2023.029078 - 19 July 2022

Abstract Environmental pollution has had substantial impacts on human life, and trash is one of the main sources of such pollution in most countries. Trash classification from a collection of trash images can limit the overloading of garbage disposal systems and efficiently promote recycling activities; thus, development of such a classification system is topical and urgent. This paper proposed an effective trash classification system that relies on a classification module embedded in a hard-ware setup to classify trash in real time. An image dataset is first augmented to enhance the images before classifying them as either… More >

Rihem Farkh^*, Khaled Aljaloud

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 901-911, 2023, DOI:10.32604/iasc.2023.027614 - 06 June 2022

Abstract In a controlled indoor environment, line tracking has become the most practical and reliable navigation strategy for autonomous mobile robots. A line tracking robot is a self-mobile machine that can recognize and track a painted line on the floor. In general, the path is set and can be visible, such as a black line on a white surface with high contrasting colors. The robot’s path is marked by a distinct line or track, which the robot follows to move. Several scientific contributions from the disciplines of vision and control have been made to mobile robot More >

N. Penchalaiah¹, Abeer S. Al-Humaimeedy², Mashael Maashi³, J. Chinna Babu^4,*, Osamah Ibrahim Khalaf⁵, Theyazn H. H. Aldhyani⁶

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5349-5365, 2022, DOI:10.32604/cmc.2022.029639 - 28 July 2022

Abstract The expanding amounts of information created by Internet of Things (IoT) devices places a strain on cloud computing, which is often used for data analysis and storage. This paper investigates a different approach based on edge cloud applications, which involves data filtering and processing before being delivered to a backup cloud environment. This Paper suggest designing and implementing a low cost, low power cluster of Single Board Computers (SBC) for this purpose, reducing the amount of data that must be transmitted elsewhere, using Big Data ideas and technology. An Apache Hadoop and Spark Cluster that… More >

Rihem Farkh^1,2, Saad Alhuwaimel^3,*, Sultan Alzahrani³, Khaled Al Jaloud¹, Mohammad Tabrez Quasim⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2811-2824, 2022, DOI:10.32604/cmc.2022.020259 - 29 March 2022

Abstract Several applications of machine learning and artificial intelligence, have acquired importance and come to the fore as a result of recent advances and improvements in these approaches. Autonomous cars are one such application. This is expected to have a significant and revolutionary influence on society. Integration with smart cities, new infrastructure and urban planning with sophisticated cyber-security are some of the current ramifications of self-driving automobiles. The autonomous automobile, often known as self-driving systems or driverless vehicles, is a vehicle that can perceive its surroundings and navigate predetermined routes without human involvement. Cars are on… More >

Abdulfattah Noorwali¹, Ameni Yengui^2,*, Kaiçar Ammous², Anis Ammous¹

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 455-466, 2022, DOI:10.32604/iasc.2022.020574 - 26 October 2021

Abstract Early fetal cardiac diseases and heart abnormalities can be detected and appropriately treated by monitoring fetal health during pregnancy. Advancements in computer sciences and the technology of sensors show that is possible to monitor fetal electrocardiogram (fECG). Both signal processing and experimental aspects are needed to be investigated to monitor fECG. In this study, we aim to design and realize a non invasive fECG monitoring system. In the first part of this work, a remote study process of the electrical activity of the heart is achieved. In fact, our proposed design considers transmitting the detected… More >