Rashid Jahangir^1,*, Nazik Alturki², Muhammad Asif Nauman³, Faiqa Hanif¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.071574 - 09 December 2025

Abstract Human activity recognition (HAR) is a method to predict human activities from sensor signals using machine learning (ML) techniques. HAR systems have several applications in various domains, including medicine, surveillance, behavioral monitoring, and posture analysis. Extraction of suitable information from sensor data is an important part of the HAR process to recognize activities accurately. Several research studies on HAR have utilized Mel frequency cepstral coefficients (MFCCs) because of their effectiveness in capturing the periodic pattern of sensor signals. However, existing MFCC-based approaches often fail to capture sufficient temporal variability, which limits their ability to distinguish… More >

Fatima Khan¹, Amna Khan¹, Tariq Ali², Tariq Shahzad³, Tehseen Mazhar^4,*, Sunawar Khan⁵, Muhammad Adnan Khan^6,*, Habib Hamam^7,8,9,10

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-27, 2026, DOI:10.32604/cmc.2025.068228 - 09 December 2025

Abstract The rise in noise and air pollution poses severe risks to human health and the environment. Industrial and vehicular emissions release harmful pollutants such as CO₂, SO₂, CO, CH₄, and noise, leading to significant environmental degradation. Monitoring and analyzing pollutant concentrations in real-time is crucial for mitigating these risks. However, existing systems often lack the capacity to monitor both indoor and outdoor environments effectively.This study presents a low-cost, IoT-based pollution detection system that integrates gas sensors (MQ-135 and MQ-4), a noise sensor (LM393), and a humidity sensor (DHT-22), all connected to a Node MCU (ESP8266) microcontroller. The… More >

Moneerah Alotaibi^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.069195 - 10 November 2025

Abstract Advanced traffic monitoring systems encounter substantial challenges in vehicle detection and classification due to the limitations of conventional methods, which often demand extensive computational resources and struggle with diverse data acquisition techniques. This research presents a novel approach for vehicle classification and recognition in aerial image sequences, integrating multiple advanced techniques to enhance detection accuracy. The proposed model begins with preprocessing using Multiscale Retinex (MSR) to enhance image quality, followed by Expectation-Maximization (EM) Segmentation for precise foreground object identification. Vehicle detection is performed using the state-of-the-art YOLOv10 framework, while feature extraction incorporates Maximally Stable Extremal… More >

Fatima Al-Quayed^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-16, 2026, DOI:10.32604/cmc.2025.069102 - 10 November 2025

Abstract Due to the growth of smart cities, many real-time systems have been developed to support smart cities using Internet of Things (IoT) and emerging technologies. They are formulated to collect the data for environment monitoring and automate the communication process. In recent decades, researchers have made many efforts to propose autonomous systems for manipulating network data and providing on-time responses in critical operations. However, the widespread use of IoT devices in resource-constrained applications and mobile sensor networks introduces significant research challenges for cybersecurity. These systems are vulnerable to a variety of cyberattacks, including unauthorized access,… More >

Mirza Murad Baig¹, Muhammad Rehan Faheem^2,*, Lal Khan^3,*, Hannan Adeel², Syed Asim Ali Shah⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 2895-2935, 2025, DOI:10.32604/cmes.2025.073172 - 23 December 2025

Abstract With growing urban areas, the climate continues to change as a result of growing populations, and hence, the demand for better emergency response systems has become more important than ever. Human Behaviour Classification (HBC) systems have started to play a vital role by analysing data from different sources to detect signs of emergencies. These systems are being used in many critical areas like healthcare, public safety, and disaster management to improve response time and to prepare ahead of time. But detecting human behaviour in such stressful conditions is not simple; it often comes with noisy… More > Graphic Abstract

Rıdvan Yayla, Hakan Üçgün^*, Onur Ali Korkmaz

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4055-4087, 2025, DOI:10.32604/cmes.2025.072703 - 23 December 2025

Abstract Recent advancements in autonomous vehicle technologies are transforming intelligent transportation systems. Artificial intelligence enables real-time sensing, decision-making, and control on embedded platforms with improved efficiency. This study presents the design and implementation of an autonomous radio-controlled (RC) vehicle prototype capable of lane line detection, obstacle avoidance, and navigation through dynamic path planning. The system integrates image processing and ultrasonic sensing, utilizing Raspberry Pi for vision-based tasks and Arduino Nano for real-time control. Lane line detection is achieved through conventional image processing techniques, providing the basis for local path generation, while traffic sign classification employs a… More > Graphic Abstract

R. Rajeev^a,b,*, C. M. S. Negi^a

Chalcogenide Letters, Vol.22, No.5, pp. 469-480, 2025, DOI:10.15251/CL.2025.225.469

Abstract Cobalt-doped cadmium sulphide nanoparticles of semiconductors (CDs: Co NPs) were synthesised using various cobalt concentrations utilising a microwave-assisted approach. Debye-Scherer equation revealed the nanoparticles' size range to be between 2 and 4 nm. Diffraction from X-rays revealed a zinc mix structure. According to the structure in the optical bandgap energies indicates that, doping has systematically raised the bandgap energy as the doping concentration raises. The composition of the nanoparticles which was verified by EDAX, validated the effective integration of cobalt into the CdS structure. The detection of different functional and vibrational groups was performed at More >

A. X. Yang^a, L. F. Huang^b,*, Y. Y. Liu^c

Chalcogenide Letters, Vol.22, No.7, pp. 649-663, 2025, DOI:10.15251/CL.2025.227.649

Abstract An innovative flexible electronic device was developed by integrating functionalized carbon nanotubes, bismuth sulfide nanostructures, and a polyvinylidene fluoride matrix to create a highly water‐resistant strain detection platform. The fabricated film exhibited a remarkable static water contact angle of 141°, with only a 3–4° reduction after 48 hours of immersion, confirming its excellent hydrophobic performance. Mechanical testing revealed a tensile strength of 43.2 MPa and maintained over 96% of its original strength following 1000 bending cycles, thereby demonstrating outstanding durability under repetitive deformation. Electrical characterization showed an initial conductivity of 12.3 S/m and a baseline resistance near… More >

A. W. Jabbar^a, N. K. Abbas^b,*

Chalcogenide Letters, Vol.22, No.8, pp. 735-752, 2025, DOI:10.15251/CL.2025.228.735

Abstract Nanostructured CdS and CdS: Cu thin films were synthesized by pulsed laser deposition with a Nd: YAG laser of different energies, 0.1, 0.5, and 1 W. The number of pulses was 300, and the frequency was 20 kHz. The CdS nanoparticles were deposited on a glass substrate. The optical, structural, and morphological properties were investigated utilized X-ray diffraction, UV-Vis spectrophotometry, and field emission scanning electron microscopy. From 2.25 to 2.1 eV, the results demonstrate that the band gap energy reduces as laser energy increases. Morphological investigations reveal that the laser energy has a significant impact More >

X. Y. Chen^a,b, Y. H. Cai^a, Y. S. Chen^c, S. J. Huang^b, M. H. Li^d, Y. H. Li^e, C. H. Lin^c, H. Chen^a,*

Chalcogenide Letters, Vol.22, No.9, pp. 777-785, 2025, DOI:10.15251/CL.2025.229.777

Abstract This study focuses on the development of zinc oxide (ZnO)/zinc sulfide (ZnS) core-shell structures on flexible polyethylene terephthalate (PET) substrates for enhanced light sensing. PET offers high elasticity, optical transparency, and chemical resistance, making it ideal for wearable optoelectronics. By optimizing the vulcanization process, a uniform ZnS shell is formed on the exposed regions of ZnO nanorods (NRs), significantly enhancing ZnO-based sensor’s sensitivity to visible light, especially red light (peak wavelength at 630 nm). Structural and spectral analyses confirm the successful formation of the ZnO/ZnS heterostructure, improved charge separation, and broadened light response. To improve More >