Xudong Wang^1,2, Xueshuai Qin¹, Huiyan Zhang^2,*, Luis Ismael Minchala³

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 385-400, 2023, DOI:10.32604/iasc.2023.036633

Abstract Unmanned vehicles are currently facing many difficulties and challenges in improving safety performance when running in complex urban road traffic environments, such as low intelligence and poor comfort performance in the driving process. The real-time performance of vehicles and the comfort requirements of passengers in path planning and tracking control of unmanned vehicles have attracted more and more attentions. In this paper, in order to improve the real-time performance of the autonomous vehicle planning module and the comfort requirements of passengers that a local granular-based path planning method and tracking control based on multi-segment Bezier curve splicing and model predictive… More >

Ashvini Kulkarni^1,2, P. Augusta Sophy Beulet^1,*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 127-146, 2023, DOI:10.32604/iasc.2023.035144

Abstract It is widely acknowledged that navigation is a significant source of between sites. The Global Positioning System (GPS) has numerous navigational advancements, and hence it is used widely. GPS navigation can be compromised at any level between position, location, and estimation, to the detriment of the user. Consequently, a navigation system requires the precise location and underpinning tracking of an object without signal loss. The objective of a hybrid environment prediction system is to foresee the location of the user and their territory by employing a variety of sensors for position estimation and monitoring navigation. This article presents a state… More >

Jinping Sun^*, Dan Li, Honglin Cheng

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 655-675, 2023, DOI:10.32604/iasc.2023.038016

Abstract Aiming at the problem that a single correlation filter model is sensitive to complex scenes such as background interference and occlusion, a tracking algorithm based on multi-time-space perception and instancespecific proposals is proposed to optimize the mathematical model of the correlation filter (CF). Firstly, according to the consistency of the changes between the object frames and the filter frames, the mask matrix is introduced into the objective function of the filter, so as to extract the spatio-temporal information of the object with background awareness. Secondly, the object function of multi-feature fusion is constructed for the object location, which is optimized… More >

Sophea Horng, Pisal Yenradee^*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6119-6143, 2023, DOI:10.32604/cmc.2023.038764

Abstract This paper proposes a Delivery Service Management (DSM) system for Small and Medium Enterprises (SMEs) that own a delivery fleet of pickup trucks to manage Business-to-Business (B2B) delivery services. The proposed DSM system integrates four systems: Delivery Location Positioning (DLP), Delivery Route Planning (DRP), Arrival Time Prediction (ATP), and Communication and Data Sharing (CDS) systems. These systems are used to pinpoint the delivery locations of customers, plan the delivery route of each truck, predict arrival time (with an interval) at each delivery location, and communicate and share information among stakeholders, respectively. The DSM system deploys Google applications, a GPS tracking… More >

Latifah Almuqren¹, Manar Ahmed Hamza^2,*, Abdullah Mohamed³, Amgad Atta Abdelmageed²

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4917-4933, 2023, DOI:10.32604/cmc.2023.037738

Abstract Face recognition technology automatically identifies an individual from image or video sources. The detection process can be done by attaining facial characteristics from the image of a subject face. Recent developments in deep learning (DL) and computer vision (CV) techniques enable the design of automated face recognition and tracking methods. This study presents a novel Harris Hawks Optimization with deep learning-empowered automated face detection and tracking (HHODL-AFDT) method. The proposed HHODL-AFDT model involves a Faster region based convolution neural network (RCNN)-based face detection model and HHO-based hyperparameter optimization process. The presented optimal Faster RCNN model precisely recognizes the face and… More >

Khalil Chebil^1,2, Skander Htiouech³, Mahdi Khemakhem^1,2,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 233-263, 2023, DOI:10.32604/cmes.2023.026476

Abstract Crowd management and analysis (CMA) systems have gained a lot of interest in the vulgarization of unmanned aerial vehicles (UAVs) use. Crowd tracking using UAVs is among the most important services provided by a CMA. In this paper, we studied the periodic crowd-tracking (PCT) problem. It consists in using UAVs to follow-up crowds, during the life-cycle of an open crowded area (OCA). Two criteria were considered for this purpose. The first is related to the CMA initial investment, while the second is to guarantee the quality of service (QoS). The existing works focus on very specified assumptions that are highly… More >

B. Subashini^*, D. Hemavathi

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3339-3358, 2023, DOI:10.32604/cmc.2023.035074

Abstract Due to an increase in agricultural mislabeling and carelesshandling of non-perishable foods in recent years, consumers have been calling for the food sector to be more transparent. Due to information dispersion between divisions and the propensity to record inaccurate data, current traceability solutions typically fail to provide reliable farm-to-fork histories ofproducts. The three most enticing characteristics of blockchain technology areopenness, integrity, and traceability, which make it a potentially crucial tool for guaranteeing the integrity and correctness of data. In this paper, we suggest a permissioned blockchain system run by organizations, such as regulatory bodies, to promote the origin-tracking of shelf-stable… More >

Ali Raza¹, Samia Allaoua Chelloug^2,*, Mohammed Hamad Alatiyyah³, Ahmad Jalal¹, Jeongmin Park⁴

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3275-3289, 2023, DOI:10.32604/cmc.2023.029719

Abstract Pedestrian detection and tracking are vital elements of today’s surveillance systems, which make daily life safe for humans. Thus, human detection and visualization have become essential inventions in the field of computer vision. Hence, developing a surveillance system with multiple object recognition and tracking, especially in low light and night-time, is still challenging. Therefore, we propose a novel system based on machine learning and image processing to provide an efficient surveillance system for pedestrian detection and tracking at night. In particular, we propose a system that tackles a two-fold problem by detecting multiple pedestrians in infrared (IR) images using machine… More >

Amarjit Singh^*

Journal on Internet of Things, Vol.4, No.2, pp. 69-73, 2022, DOI:10.32604/jiot.2022.026170

Abstract Wireless sensor networks (WSNs) are created and affect our daily lives. You can find applications in various fields such as health, accident, life, manufacturing, production management, network management and many other fields. WSN now connects to the Internet of Things, connects the sensor to the Internet, and then uses it for collaboration and collaboration. However, when WSN is part of the internet we need to be able to study and analyze related terms. In this article, we’re going to look at different ways to get WSN online and identify the challenges that address in future as well. More >

B. Sophia^1,*, D. Chitra²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2491-2504, 2023, DOI:10.32604/iasc.2023.029799

Abstract Presently, video surveillance is commonly employed to ensure security in public places such as traffic signals, malls, railway stations, etc. A major challenge in video surveillance is the identification of anomalies that exist in it such as crimes, thefts, and so on. Besides, the anomaly detection in pedestrian walkways has gained significant attention among the computer vision communities to enhance pedestrian safety. The recent advances of Deep Learning (DL) models have received considerable attention in different processes such as object detection, image classification, etc. In this aspect, this article designs a new Panoptic Feature Pyramid Network based Anomaly Detection and… More >