The development of exoskeletons aimed at enhancing the mobility and autonomy of people with disabilities marks a significant advance toward social and occupational inclusion, fostering greater independence and improved quality of life. However, their implementation poses multidisciplinary challenges, including technical issues, usability, cost, and user acceptance. This article synthesizes the main challenges, recent advancements, and future perspectives identified in scientific literature through a systematic review conducted under the PRISMA^® methodology. Forty-three high-impact publications indexed in SCOPUS, Web of Science, ScienceDirect, Taylor & Francis, IEEE Xplore, and PubMed were analyzed, showing an almost perfect inter-rater agreement (Cohen’s Kappa = 0.8390). The findings underscore the need to optimize control systems, reduce costs, and improve device adaptability. Artificial intelligence emerges as a key enabler to overcome these limitations, offering more efficient, affordable, and personalized solutions. This work provides an up-to-date overview of the field and outlines future directions for exoskeleton research and development, highlighting their transformative potential in the lives of people with disabilities.

Population ageing is a growing global trend. It was estimated that by 2050, people over 60 years of age will represent 35% of the population in industrialised countries. This context demands strategies that incorporate technologies, such as fall detection systems, to facilitate remote monitoring and the automatic activation of risk alarms, thus improving quality of life. This article presents a scoping review of the leading technological solutions developed over the last decade for detecting falls in older adults, describing their principles of operation, effectiveness, advantages, limitations, and future trends in their development. The review was conducted under the PRISMA^® methodology, including articles indexed in SCOPUS, ScienceDirect, Web of Science, PubMed, IEEE Xplore and Taylor & Francis. There is a predominance in the use of inertial systems that use accelerometers and gyroscopes, valued for their low cost and wide availability. However, those approaches that combine image analysis with artificial intelligence and machine learning algorithms show superiority in terms of accuracy and robustness. Similarly, progress has been made in the development of multisensory solutions based on IoT technologies, capable of integrating information from various sources, which optimises decision-making in real time.

The advancement of digital technologies such as photogrammetry, 3D scanning, Geographic Information Systems (GISs), and artificial intelligence has profoundly transformed archaeology by enabling more accurate documentation, analysis, and visualization of cultural heritage. These tools facilitate evidence preservation, enhance research processes, and broaden the possibilities for interpreting and disseminating archaeological knowledge. This scoping review synthesizes recent progress in the application of digital technologies for the reconstruction of archaeological evidence, emphasizing their main impacts on archaeological research while addressing existing challenges, limitations, and future perspectives, particularly focusing on the integration of artificial intelligence. A systematic review of the scientific literature was conducted using the PRISMA^® methodology, analyzing documents retrieved from databases such as Scopus, PubMed, IEEE Xplore, and ScienceDirect. One hundred and sixteen papers were selected, with a Cohen’s Kappa coefficient of 0.463 ensuring the reliability of the selection process. The findings reveal that the integration of digital technologies is redefining archaeological reconstruction methods and expanding the horizons of historical and heritage knowledge, requiring collaborative, ethical, and interdisciplinary approaches to achieve a more accurate, accessible, and sustainable archaeology in the future.

This document explains the criteria, considerations and formulations used for the design of the main components of a mobile platform with a robotic arm. This type of robot is one of the most used in the educational field, it facilitates learning and allows the incorporation of control strategies for navigation. Aspects of resistance of materials useful for branches of engineering that lack bases on mechanics are raised. Keywords: Design; robot; platform; educational. References [1]O. Flor, W. Hernandez, O. Vargas, A. Mendez, O. Sergiyenko and V. Tyrsa, "Construction of a Robotic Platform of Differential Type for First-Year Students of Electronic Engineering", International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), Sorrento, Italy, 2020, pp. 538-543, doi: 10.1109/SPEEDAM48782.2020.9161870. [2]O. Flor, “Building a mobile robot”, Education for the future, 2020 [Online] Available: https://omarflor2014. wixsite.com/misitio. [Last Access: February 10, 2020]. [3]A. Ollero, “ROBÓTICA: Manipuladores y robots móviles, Marcombo Boixareu Editores, 2001, Chapters 1-2 (pp. 1-37), Chapter 4 (pp. 85-87), Chapter 9 (pp. 258-267), and Chapter 10 (pp. 303-327). [4]K. Pitti, L. Muñoz, I. Moreno, J. Serracín, “La robótica educativa, una herramienta para la enseñanza-aprendizaje de las ciencias y tecnologías”, Researchgate, pp. 74-90, 2012. [5]E. Ruiz, R. Acuña, N. Certad, A. Terrones and M. E. Cabrera, "Development of a Control Platform for the Mobile Robot Roomba Using ROS and a Kinect Sensor", 2013 Latin American Robotics Symposium and Competition, Arequipa, 2013, pp. 55-60. doi: 10.1109/LARS.2013.57J. [6]J. Wu, C. Lv, L. Zhao, R. Li and G. Wang, "Design and implementation of an omnidirectional mobile robot platform with unified I/O interfaces," 2017 IEEE International Conference on Mechatronics and Automation (ICMA), Takamatsu, 2017, pp. 410-415. doi: 10.1109/ICMA.2017.8015852. [7]M. Ali, W. Yusoff, Z. Hamedon, M. Yussof and M. Mailah, Mechatronic design and development of an autonomous mobile robotics system for road marks painting, IEEE Industrial Electronics and Applications Conference, 2016, pp. 336-341, doi: 10.1109/IEACON.2016.8067401. [8]H. Guo , K. Su , K. Hsia , and J. Wang , Development of the mobile robot with a robot arm, Proceedings IEEE International Conference on Industrial Technology (ICIT), Taipei, Taiwan, 2016, pp. 1648-1653. [9]R. A. Orozco-Velázquez et al., Ackerman Mobile Robot with Arm,International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE), Cuernavaca, 2016, pp. 55-60, doi: 10.1109/ICMEAE. 2016.019. [10]A. Razak et al., Mobile robot structure design, modeling and simulation for confined space application, 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA), 2016 Ipoh, 2016, pp. 1-5. doi: 10.1109/ROMA.2016.7847808.

En este trabajo se presenta el diseño de una mano robótica de 7 grados de libertad que permite mayor flexibilidad, logrando las acciones habituales realizadas por una mano normal. El trabajo consta de un prototipo diseñado con actuares lineales y sensor mioeléctrico, siguiendo el mecanismo de la Universidad de Toronto para el manejo de falanges funcionales. Se presenta el diseño, descripción constructiva, componentes y recomendaciones para la elaboración de unamano robótica flexible y útil para pacientes amputados con miembro residual para el encaje. Palabras Clave: Mano robótica, grado de libertad, Mecanismo de Toronto, actuador lineal. Referencias [1]W. Diane, J. Braza and M. Yacub, Essentials of Physical Medicine and Rehabilitation, 4th ed. Philadelphia: Walter R. Frontera and Julie K. Silver and Thomas D. Rizzo, 2020, pp. 651 - 657. [2]A. Heerschop, C. Van Der Sluis, E. Otten, & R.M. Bongers, Looking beyond proportional control: The relevance of mode switching in learning to operate multi-articulating myoelectric upper-limb prostheses, . Biomedical Signal Processing and Control, 2020, doi:10.1016/j.bspc.2019.101647. [3]L. Heisnam, B. Suthar, 20 DOF robotic hand for tele-operation: — Design, simulation, control and accuracy test with leap motion. 2016 International Conference on Robotics and Automation for Humanitarian Applications (RAHA), 2016, doi:10.1109/raha.2016.7931886. [4]Y. Mishima, R. Ozawa, Design of a robotic finger using series gear chain mechanisms. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014, doi:10.1109/iros.2014.6942961. [5]N. Dechev, W. Cleghorn, S. Naumann, Multi-segmented finger design of an experimental prosthetic hand,Proceedings of the Sixth National Applied Mechanisms & Robotics Conference, december 1999. [6]O. Flor, “Building a mobile robot,” Education for the future. Accessed on: December 29, 2019. [Online] Available: https://omarflor2014.wixsite.com/misitio. [7]Vargas, O., Flor,O., Suarez, F., Design of a robotic prototype of the hand and right forearm for prostheses, Universidad, Ciencia y Tecnología, 2019. [8]O. Vargas, O. Flor, F. Suarez, C. Chimbo, Construction and functional tests of a robotic prototype for human prostheses, Revista espirales, 2020. [9]P. PonPriya, E. Priya, Design and control of prosthetic hand using myoelectric signal. International Conference on Computing and Communications Technologies (ICCCT), 2017, doi:10.1109/iccct2.2017.7972314. [10]N. Bajaj, A. Spiers, A. Dollar, State of the Art in Artificial Wrists: A Review of Prosthetic and Robotic Wrist Design. IEEE Transactions on Robotics, 2019, doi:10.1109/tro.2018.2865890. In this work, the design of a robotic hand with 7 degrees of freedom is presented that allows greater flexibility, achieving the usual actions performed by a normal hand. The work consists of a prototype designed with linear actuators and myoelectric sensor, following the mechanism of the University of Toronto for the management of functional phalanges. The design, construction description, components and recommendations for the elaboration of a flexible and useful robotic hand for amputee patients with a residual limb for the socket are presented. Keywords: Robotic hand, Degree of freedom, Toronto´s Mechanism, lineal actuator. References [1]W. Diane, J. Braza and M. Yacub, Essentials of Physical Medicine and Rehabilitation, 4th ed. Philadelphia: Walter R. Frontera and Julie K. Silver and Thomas D. Rizzo, 2020, pp. 651 - 657. [2]A. Heerschop, C. Van Der Sluis, E. Otten, & R.M. Bongers, Looking beyond proportional control: The relevance of mode switching in learning to operate multi-articulating myoelectric upper-limb prostheses, . Biomedical Signal Processing and Control, 2020, doi:10.1016/j.bspc.2019.101647. [3]L. Heisnam, B. Suthar, 20 DOF robotic hand for tele-operation: — Design, simulation, control and accuracy test with leap motion. 2016 International Conference on Robotics and Automation for Humanitarian Applications (RAHA), 2016, doi:10.1109/raha.2016.7931886. [4]Y. Mishima, R. Ozawa, Design of a robotic finger using series gear chain mechanisms. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014, doi:10.1109/iros.2014.6942961. [5]N. Dechev, W. Cleghorn, S. Naumann, Multi-segmented finger design of an experimental prosthetic hand,Proceedings of the Sixth National Applied Mechanisms & Robotics Conference, december 1999. [6]O. Flor, “Building a mobile robot,” Education for the future. Accessed on: December 29, 2019. [Online] Available: https://omarflor2014.wixsite.com/misitio. [7]Vargas, O., Flor,O., Suarez, F., Design of a robotic prototype of the hand and right forearm for prostheses, Universidad, Ciencia y Tecnología, 2019. [8]O. Vargas, O. Flor, F. Suarez, C. Chimbo, Construction and functional tests of a robotic prototype for human prostheses, Revista espirales, 2020. [9]P. PonPriya, E. Priya, Design and control of prosthetic hand using myoelectric signal. International Conference on Computing and Communications Technologies (ICCCT), 2017, doi:10.1109/iccct2.2017.7972314. [10]N. Bajaj, A. Spiers, A. Dollar, State of the Art in Artificial Wrists: A Review of Prosthetic and Robotic Wrist Design. IEEE Transactions on Robotics, 2019, doi:10.1109/tro.2018.2865890.

Security infrastructure has evolved from the use of reactive models toward the adoption of predictive technologies, transforming and enhancing threat anticipation, improving monitoring capabilities, and strengthening strategic decision-making driven by the integration of emerging technologies and artificial intelligence. This review study synthesizes the changes occurring across spatial, maritime, aerial, border, and cybersecurity infrastructure, evidencing the impact of the transition toward predictive technologies; it addresses the challenges and limitations these technologies introduce as a consequence of their operational deployment, and concludes by examining future lines of development in this domain. The review was conducted following the PRISMA^® methodology, analyzing the scientific literature retrieved from seven indexed databases—SCOPUS, ScienceDirect, Web of Science, IEEE Xplore, Taylor & Francis, ProQuest, and PubMed—consistent with the full search scope. Articles were independently assessed by two reviewers, yielding an initial Cohen’s Kappa coefficient of 0.458; following structured discussion and consensus resolution, the final inter-rater reliability reached κ = 0.71, meeting the accepted threshold for scoping review methodology. The findings demonstrate a global transition toward intelligent security infrastructures, with measurable improvements in performance, accuracy, and response times in the generation of actionable intelligence to support strategic decision-making.