Application of Artificial Intelligence and Machine Learning in Libraries: A Systematic Review

As the concept and implementation of cutting-edge technologies like artificial intelligence and machine learning has become relevant, academics, researchers and information professionals involve research in this area. The objective of this systematic literature review is to provide a synthesis of empirical studies exploring application of artificial intelligence and machine learning in libraries. To achieve the objectives of the study, a systematic literature review was conducted based on the original guidelines proposed by Kitchenham et al. (2009). Data was collected from Web of Science, Scopus, LISA and LISTA databases. Following the rigorous/ established selection process, a total of thirty-two articles were finally selected, reviewed and analyzed to summarize on the application of AI and ML domain and techniques which are most often used in libraries. Findings show that the current state of the AI and ML research that is relevant with the LIS domain mainly focuses on theoretical works. However, some researchers also emphasized on implementation projects or case studies. This study will provide a panoramic view of AI and ML in libraries for researchers, practitioners and educators for furthering the more technology-oriented approaches, and anticipating future innovation pathways

RFID en el servicio bibliotecario de la UTM

The central library of the Technical University of Manabí (UTM), offers the service of electronic equipment loans (laptops and tablets), in which theft has been presented. In the present article the integration of identification technologies through a web application is exposed. To do this, the requirements were raised, systems analysis and identification technologies were analyzed. Based on the study of art, the development methodology, programming languages, tools and technologies applied in the solution were described, the system architecture was designed with visual / audible alarm, the integrating system was developed and implemented and finally functional tests were carried out. As a result, it was evidenced that using bar code and RFID technology in the library service, there is better control of the entry and exit of electronic equipment, preventing any attempt at theft, and the university and general community receive a quality and speedy service.La biblioteca central de la Universidad Técnica de Manabí (Ecuador)brinda el servicio de préstamos de equipos electrónicos (portátiles y tabletas), en el que se han presentado hurtos de los mismos. En este artículo se expone la integración de RFID a través de una aplicación web. Para ello, se realizó el levantamiento de requerimientos, análisis de sistemas y de tecnologías de identificación, tomando como base el estudio del arte se describió la metodología de desarrollo, lenguajes de programación, herramientas y tecnologías aplicadas en la solución, se diseñó la arquitectura del sistema con alarma visual/sonora, se desarrolló e implantó el sistema integrador y, finalmente, se ejecutaron pruebas de funcionamiento. Como resultado se evidenció que al utilizar tecnología de código de barras y RFID en el servicio bibliotecario existe un mejor control de entrada y salida de los equipos electrónicos, previniendo de cualquier intento de hurto; a su vez, la comunidad universitaria y general recibe un servicio de calidad y rapidez

Physiological and behavior monitoring systems for smart healthcare environments: a review

Healthcare optimization has become increasingly important in the current era, where numerous challenges are posed by population ageing phenomena and the demand for higher quality of the healthcare services. The implementation of Internet of Things (IoT) in the healthcare ecosystem has been one of the best solutions to address these challenges and therefore to prevent and diagnose possible health impairments in people. The remote monitoring of environmental parameters and how they can cause or mediate any disease, and the monitoring of human daily activities and physiological parameters are among the vast applications of IoT in healthcare, which has brought extensive attention of academia and industry. Assisted and smart tailored environments are possible with the implementation of such technologies that bring personal healthcare to any individual, while living in their preferred environments. In this paper we address several requirements for the development of such environments, namely the deployment of physiological signs monitoring systems, daily activity recognition techniques, as well as indoor air quality monitoring solutions. The machine learning methods that are most used in the literature for activity recognition and body motion analysis are also referred. Furthermore, the importance of physical and cognitive training of the elderly population through the implementation of exergames and immersive environments is also addressedinfo:eu-repo/semantics/publishedVersio