{"id":48,"date":"2026-05-28T08:29:44","date_gmt":"2026-05-28T08:29:44","guid":{"rendered":"https:\/\/journals.utgjiu.ro\/JFD\/?post_type=articol&#038;p=48"},"modified":"2026-05-28T08:29:44","modified_gmt":"2026-05-28T08:29:44","slug":"the-evolution-of-intelligent-incident-prevention-systems-in-fuel-transportation-and-storage-a-literature-review","status":"publish","type":"articol","link":"https:\/\/journals.utgjiu.ro\/JFD\/articol\/the-evolution-of-intelligent-incident-prevention-systems-in-fuel-transportation-and-storage-a-literature-review\/","title":{"rendered":"The Evolution of Intelligent Incident-Prevention Systems in Fuel Transportation and Storage: A Literature Review"},"content":{"rendered":"<p>The transport and storage of fuels represent critical components of the energy supply chain, characterized by a high level of operational complexity and an inherent risk of major accidents, including fires, explosions, and environmental contamination. In this context, the development of intelligent systems for incident prevention has become a key research direction over the past decades. This paper presents a comprehensive literature review on the evolution of technological solutions designed to reduce the probability of hazardous events in fuel transport and storage infrastructures. The study analyzes the transition from traditional supervisory control systems, such as SCADA-based architectures, to modern approaches integrating Industrial Internet of Things (IIoT), artificial intelligence (AI), and Digital Twin technologies. A systematic selection of relevant scientific publications from major databases was conducted, focusing on recent advances in real-time monitoring, anomaly detection, predictive maintenance, and decision-support systems. The review highlights the strengths and limitations of each technological stage, emphasizing the shift from reactive safety management to proactive and predictive risk mitigation strategies. Special attention is given to emerging trends, including the integration of multi-source data, the use of machine learning algorithms for anomaly detection, and the implementation of virtual replicas for scenario simulation and optimization. In addition, the paper identifies current research gaps, particularly regarding the integration of human factors, system interoperability, and the scalability of intelligent safety platforms. The findings underline that future developments in this field will rely on hybrid architectures combining sensing technologies, advanced analytics, and real-time simulation capabilities, contributing to safer, more resilient, and sustainable fuel logistics systems.<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}}},"class_list":["post-48","articol","type-articol","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/journals.utgjiu.ro\/JFD\/wp-json\/wp\/v2\/articol\/48","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/journals.utgjiu.ro\/JFD\/wp-json\/wp\/v2\/articol"}],"about":[{"href":"https:\/\/journals.utgjiu.ro\/JFD\/wp-json\/wp\/v2\/types\/articol"}],"wp:attachment":[{"href":"https:\/\/journals.utgjiu.ro\/JFD\/wp-json\/wp\/v2\/media?parent=48"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}