Oscar Peña-Cáceres^1,2,*, Elvis Garay-Silupu³, Darwin Aguilar-Chuquizuta⁴, Henry Silva-Marchan⁴

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2151-2188, 2025, DOI:10.32604/cmc.2025.065149 - 03 July 2025

Abstract Self-Explaining Autonomous Systems (SEAS) have emerged as a strategic frontier within Artificial Intelligence (AI), responding to growing demands for transparency and interpretability in autonomous decision-making. This study presents a comprehensive bibliometric analysis of SEAS research published between 2020 and February 2025, drawing upon 1380 documents indexed in Scopus. The analysis applies co-citation mapping, keyword co-occurrence, and author collaboration networks using VOSviewer, MASHA, and Python to examine scientific production, intellectual structure, and global collaboration patterns. The results indicate a sustained annual growth rate of 41.38%, with an h-index of 57 and an average of 21.97 citations… More >

Mofadal Alymani¹, Mohamed Esmail Karar^2,*, Hazem Ibrahim Shehata^1,3

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2181-2197, 2024, DOI:10.32604/cmc.2024.052406 - 15 August 2024

Abstract Object tracking is one of the major tasks for mobile robots in many real-world applications. Also, artificial intelligence and automatic control techniques play an important role in enhancing the performance of mobile robot navigation. In contrast to previous simulation studies, this paper presents a new intelligent mobile robot for accomplishing multi-tasks by tracking red-green-blue (RGB) colored objects in a real experimental field. Moreover, a practical smart controller is developed based on adaptive fuzzy logic and custom proportional-integral-derivative (PID) schemes to achieve accurate tracking results, considering robot command delay and tolerance errors. The design of developed… More >

Abdulrahman M. Abdulghani, Wilbur L. Walters, Khalid H. Abed^*

Journal of Blockchain and Intelligent Computing, Vol.1, pp. 1-13, 2023, DOI:10.32604/jbic.2023.041340 - 29 September 2023

Abstract Blockchain technology is increasingly used to design trustworthy and reliable platforms for sharing information in a plethora of industries. It is a decentralized system that acts as an immutable record for storing data. It has the potential to disrupt a range of fields that rely on data, including autonomous systems like Unmanned Aerial Vehicles (UAVs). In this paper, we propose a framework based on blockchain and distributed ledger technology to improve transmission time and provide a secured and trusted method for UAVs to transfer data to the consumer efficiently while maintaining data reliability. The results More >

Ashit Kumar Dutta^1,*, Yasser Albagory², Abdul Rahaman Wahab Sait³, Ismail Mohamed Keshta¹

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 899-915, 2022, DOI:10.32604/cmc.2022.026783 - 18 May 2022

Abstract Recently, autonomous systems become a hot research topic among industrialists and academicians due to their applicability in different domains such as healthcare, agriculture, industrial automation, etc. Among the interesting applications of autonomous systems, their applicability in agricultural sector becomes significant. Autonomous unmanned aerial vehicles (UAVs) can be used for suitable site-specific weed management (SSWM) to improve crop productivity. In spite of substantial advancements in UAV based data collection systems, automated weed detection still remains a tedious task owing to the high resemblance of weeds to the crops. The recently developed deep learning (DL) models have… More >