Abstract:The smart city vision has driven the rapid development and advancement of interconnected technologies using the Internet of Things (IoT) and cyber-physical systems (CPS). In this paper, various aspects of IoT and CPS in recent years (from 2013 to May 2023) are surveyed. It first begins with industry standards which ensure cost-effective solutions and interoperability. With ever-growing big data, tremendous undiscovered knowledge can be mined to be transformed into useful applications. Machine learning algorith… Show more
“…I4.0 is the fourth industrial revolution or technological revolution that integrates different technologies, such as big data, industrial automation (robotics), simulations, integration systems, cyber-physical systems, internet of things, cyber security, computing in the cloud, additive manufacturing, and augmented reality, for the continuous improvement of the industry. I4.0 combines information and communication technologies with digital manufacturing and production processes [10][11][12]. Industry 4.0 enables the integration of physical assets into interdependent physical and digital processes, creating smart factories and manufacturing environments [13].…”
This article presents a critical review of the current and future state of “business architecture” within the enterprise architecture frameworks. The review is conducted in the following four stages. In the first stage of analysis, the research and publication questions are established. In the second stage, the search for information is designed and implemented using the Prisma methodology, and once the selection criteria were applied, 75 article-type documents were selected from Scopus, WoS, and Dimensions databases. In the third stage, the information analysis is conducted, and then it is synthesized. Finally, in fourth stage, the discussion is elaborated. This research contributes in understanding the current and future trends of business architecture in Industry 4.0. Considering the challenges of the changing market, the results show the need to implement architectures and dynamic business models, including their artifacts, in a globalized context immersed in new technologies.
“…I4.0 is the fourth industrial revolution or technological revolution that integrates different technologies, such as big data, industrial automation (robotics), simulations, integration systems, cyber-physical systems, internet of things, cyber security, computing in the cloud, additive manufacturing, and augmented reality, for the continuous improvement of the industry. I4.0 combines information and communication technologies with digital manufacturing and production processes [10][11][12]. Industry 4.0 enables the integration of physical assets into interdependent physical and digital processes, creating smart factories and manufacturing environments [13].…”
This article presents a critical review of the current and future state of “business architecture” within the enterprise architecture frameworks. The review is conducted in the following four stages. In the first stage of analysis, the research and publication questions are established. In the second stage, the search for information is designed and implemented using the Prisma methodology, and once the selection criteria were applied, 75 article-type documents were selected from Scopus, WoS, and Dimensions databases. In the third stage, the information analysis is conducted, and then it is synthesized. Finally, in fourth stage, the discussion is elaborated. This research contributes in understanding the current and future trends of business architecture in Industry 4.0. Considering the challenges of the changing market, the results show the need to implement architectures and dynamic business models, including their artifacts, in a globalized context immersed in new technologies.
“…At its core, ontology is a structured framework that defines the relationships between various entities and concepts within a particular domain. For example, in a forensic context, ontology could define the relationships between a suspect, a crime scene, and different types of evidence, such as DNA samples or digital data [36,51,52]. This structured approach facilitates more than just data storage; it allows for effective data retrieval and the ability to draw meaningful conclusions from complex, interconnected information [51][52][53][54][55][56].…”
Section: Literature Reviewmentioning
confidence: 99%
“…For example, in a forensic context, ontology could define the relationships between a suspect, a crime scene, and different types of evidence, such as DNA samples or digital data [36,51,52]. This structured approach facilitates more than just data storage; it allows for effective data retrieval and the ability to draw meaningful conclusions from complex, interconnected information [51][52][53][54][55][56]. The utility of ontology extends to creating semantic networks, which allow for the representation of complex relationships that are machine-readable and intuitively understandable for human operators [57].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Designing an ontological framework that is comprehensive and flexible enough to adapt to the evolving nature of criminal activities requires a deep understanding of the domain and expertise in ontology design principles. Furthermore, the effectiveness of an ontology-based system is highly dependent on the quality and completeness of the data it contains [51,52]. Incomplete or inaccurate data can lead to misleading or false conclusions, and therefore, the data input process must be rigorously controlled and validated.…”
Nowadays, more and more sciences are involved in strengthening the work of law enforcement authorities. Scientific documentation is evidence highly respected by the courts in administering justice. As the involvement of science in solving crimes increases, so does human subjectivism, which often leads to wrong conclusions and, consequently, to bad judgments. From the above arises the need to create a single information system that will be fed with scientific evidence such as fingerprints, genetic material, digital data, forensic photographs, information from the forensic report, etc., and also investigative data such as information from witnesses’ statements, the apology of the accused, etc., from various crime scenes that will be able, through formal reasoning procedure, to conclude possible perpetrators. The present study examines a proposal for developing an information system that can be a basis for creating a forensic ontology—a semantic representation of the crime scene—through descriptive logic in the owl semantic language. The Interoperability-Enhanced information system to be developed could assist law enforcement authorities in solving crimes. At the same time, it would promote closer cooperation between academia, civil society, and state institutions by fostering a culture of engagement for the common good.
“…Recently, smart firefighting systems have been proposed and developed due to their capability of enhancing the efficiency and effectiveness of firefighting operations. Reinforced by the Internet of Things (IoT) technologies [2,3], smart firefighting systems are able to perform intelligent and automated fire detection and suppression. IoT-based smart devices, such as smoke detectors, heat sensors, water sprinklers, etc., as well as advanced technologies such as wireless networking, smart sensors, machine learning and automation, are applied to provide intelligent monitoring, early detection and a rapid response to fire incidents.…”
Fire pumps are the key components of water supply in a firefighting system. At present, there is a lack of fire water pump testing methods that intelligently detect faulty states. Existing testing approaches require manual operation, which leads to low efficiency and accuracy. To solve the issue, this paper presents an automatic and smart testing approach that acquires measurements of the flow, pressure, shaft power and efficiency from smart sensors via an IoT network, so that performance curves are obtained in the testing processes. An IoT platform is developed for data conversion, transmission and storage. The Discrete Fréchet Distance is applied to evaluate the similarities between the acquired performance curves and metric performance curves, to determine the working condition of the fire pump. The weights of the measurement dimensions for distance computation are optimized by the Genetic Algorithm to improve the distinction between normal and faulty performance curves. Finally, the experimental results show that the proposed method can completely detect faulty states and prove its high practicality for real firefighting systems.
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