Artificial intelligence (AI) bids serious attention among the researchers and academicians to show how evolutions of smart city are taking place at different scales. Smart Cities Intelligence gives a multidisciplinary, joined procedure, using speculative applied bits information, for evaluation savvy situations. The objective this published special issue is focus on all aspects future research directions specific area AI-enabled applications automatic intelligent systems in cities societies....

Abstract Agriculture in rural areas facing critical issues such as irrigation with the increase water crises followed by some other line seed quality, poor fertilizers and many others. The recent advances suggest that IoT Blockchain Technology along artificial intelligence will be most dominant technologies near future. In this article, integration of Internet Things (IoT) technology is implemented for monitoring agricultural fields efficiently. An efficient quality smart management system...

Recently, 6G-enabled Internet of Things (IoT) is gaining attention and addressing various challenges real time application. The artificial intelligence plays a significant role for big data analytics presents accurate analysis in time. However, designing through faces some issues terms security, privacy, training data, centralized architecture. In this article, blockchain-based IoT framework with proposed which the integration blockchain applications. performance architecture evaluated...

Abstract Agriculture encompasses the study, practice, and discipline of plant cultivation. has an extensive history dating back thousands years. Depending on climate terrain, it began independently in various locations planet. In comparison to what could be sustained by foraging gathering, agriculture potential significantly increase human population. Throughout twenty-first century, precision farming (PF) increased agricultural output. (PA) is a technology-enabled method that assesses,...

Planning effective routes and monitoring vehicle traffic are essential for creating sustainable smart cities. Accurate speed prediction is a key component of these efforts, as it aids in alleviating congestion. While their physical proximity important, the interconnection road segments what significantly contributes to increase This interconnectedness poses significant challenge increasing accuracy. To address this, we propose novel approach based on Deep Graph Neural Networks (DGNNs), which...

Breast cancer, a leading cause of female mortality worldwide, poses significant health challenge. Recent advancements in deep learning techniques have revolutionized breast cancer pathology by enabling accurate image classification. Various imaging methods, such as mammography, CT, MRI, ultrasound, and biopsies, aid detection. Computer-assisted pathological classification is paramount importance for diagnosis. This study introduces novel approach to histopathological It leverages modified...

The Internet of Things (IoT) technology allows massive devices to connect the internet for data exchange. It is anticipated that in near future, trillions IoT will be connected internet. To deploy these devices, requirement spectrum increasing day by day. Most transmit over unlicensed frequency bands cause severe interference each other while exchanging as are becoming overcrowded. Therefore, overcome scarcity and problems among a novel communication paradigm called cognitive radio-based...

Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating transmission messages between graph nodes. operate on graph‐structured data, which makes them suitable for a wide variety computer vision problems, such as link prediction, node classification, and classification. The authors explore in depth applications GNNs vision, including their design considerations, architectural challenges, applications, implementation concerns. While conventional...

This paper presents an attributed graph-based approach to intricate data mining problem of revealing affiliated, interdependent entities that might be at risk being tempted into fraudulent transfer pricing. We formalize the notions controlled transactions and parties in terms graph theory. investigate use clustering rule induction techniques identify candidate groups (hot spots) suspect entities. Further, we find require special attention with respect pricing audits using network analysis...

In the current era of emerging technologies such as deep learning, artificial intelligence, multimedia data analysis, Internet Things (IoT), significant role vibration analysis can be seen in biomedical, nonlinear dynamics, and control engineering. Despite numerous applications, lots challenges issues are still needed to address like nonlinearity, fault diagnosis, spectrum biomedical monitoring processing. The aim this Special Issue is cover all aforesaid practical solutions for...

In this paper, we present a method for the assessment of share cardholders most prone to various types bank fraud (i.e. fishing, vishing, skimming). For purpose, forecasting information system has been designed. It is based on clustering module used output certain set cluster indices that depend percentage aggrieved clients in training sample. The k-means clustering. initial coordinates centroids are defined using advanced k-means++ algorithm.

This paper focuses on the design and implementation of a distributed, highly scalable, fault-tolerant anti-fraud service accessible via REST API. Web works in near real-time employs machine learning algorithms for predictive analytics. Our goal is to develop an affordable service, which provides possibility participating parties (i.e. merchants, aggregating agents, payment systems, banks) reduce risks fraudulent payments over their sites. We explore number approaches resulting significant...

In this paper, we present a clique-based method for mining fuzzy graph patterns of money laundering and financing terrorism. The will contribute to new generation intelligent anti-money systems that incorporate comprehensive information from various sources as well human subject matter experts. A degree confidence can therefore be associated each relation between any two actors in transactions. We reduce the problem subgraph isomorphism finding set maximal cliques extension mathematical...

Risks and losses arising from system failure, unauthorized activity, fraud other operational errors are postulated to be one of the primary banking risks.Expert-based scenario analysis aims at describing frequency severity extreme losses.Experts not exact in predicting quantitative estimates for a distant future.The predicted scenarios described by range qualitative storylines.This study introduces applies methodology evaluation risk levels derived experts opinions collected scenarios.The is...

In this paper, we present a new graph-theoretic approach to modeling user activity in wide range of information security monitoring tasks. We introduce notion generalized hypergraph that allows direct and holistic representation complex relationships context-dependent communications between actors groups network.

In this paper, we present a graph-based approach to data mining problem of exploring and revealing domain groups users prone committing financial fraud. Data in applications refers extracting organizing knowledge from large amount legal according certain criteria. order solve problem, information about the companies should be well-defined arranged process model. Here, introduced model formalize amounts as well methodology graph centers interest classification prediction tasks that are vital...

This paper has considered an architecture for building the Industrial Internet of Things (IIoT) using edge computing technology. The levels this and their respective roles are described, as benefits implementing Mobile Edge Computing (MEC) in IIoT, model smart factory, case which application must be migrated from cloud to device. As part explanation selection technologies used coordinating migration a network with computing, concepts designing software based on microservice were considered,...