Current Issue : April - June Volume : 2021 Issue Number : 2 Articles : 5 Articles
The fault detection and diagnosis (FDD) along with condition monitoring (CM) and of rotating machinery (RM) have critical\nimportance for early diagnosis to prevent severe damage of infrastructure in industrial environments. Importantly, valuable\nindustrial equipment needs continuous monitoring to enhance the safety, reliability, and availability and to decrease the cost of\nmaintenance of modern industrial systems and applications. However, induction motor (IM) has been extensively used in several\nindustrial processes because it is cheap, reliable, and robust. Rolling bearings are considered to be the main component of IM.\nUndoubtedly, any failure of this basic component can lead to a serious breakdown of IM and for whole industrial system. )us,\nmany current methods based on different techniques are employed as a fault prognosis and diagnosis of rolling elements bearing\nof IM. Moreover, these techniques include signal/image processing, intelligent diagnostics, data fusion, data mining, and expert\nsystems for time and frequency as well as time-frequency domains. Artificial intelligence (AI) techniques have proven their\nsignificance in every field of digital technology. Industrial machines, automation, and processes are the net frontiers of AI\nadaptation. )ere are quite developed literatures that have been approaching the issues using signals and data processing\ntechniques. However, the key contribution of this work is to present an extensive review of CM and FDD of the IM, especially for\nrolling elements bearings, based on artificial intelligent (AI) methods. )is study highlights the advantages and performance\nlimitations of each method. Finally, challenges and future trends are also highlighted....
The influential stage of Internet of Things (IoT) has reformed all fields of life in general but specifically with the emergence of artificial intelligence (AI) has drawn the attention of researchers into a new paradigm of life standard. This revolution has been accepted around the globe for making life easier with the use of intelligent devices such as smart sensors, actuators, and many other devices. AI-enabled devices are more intelligent and capable of doing a specific task which saves a lot of resources and time. Different approaches are available in the existing literature to tackle diverse issues of real life based on AI and IoTsystems. The role of decision-making has its own importance in the AI-enabled and IoTsystems. In-depth knowledge of the existing literature is dire need of the research community to summarize the literature in effective way by which practitioners and researchers can benefit from the prevailing proofs and suggest new solutions for solving a particular problem of AI-enabled sensing and decision-making for the IoT system. To facilitate research community, the proposed study presents a systematic literature review of the existing literature, organizes the evidences in a systematic way, and then analyzes it for future research. The study reported the literature of the last 5 years based on the research questions, inclusion and exclusion criteria, and quality assessment of the selected study. Finally, derivations are drawn from the included paper for future research....
Banks daily interact with a vast number of customers and are still depending on a legacy system. With today’s advances in technology, regarding lifting almost all processes to automation, from start of production to finish, there is a need for revolution in archaic monetary management institutes. By not being in tune with the contemporary trends and times, banks are losing on an opportunity to transform some of their business models and relieve humans of repetitive work, prevent frauds, make better decisions and consequently gain losses. Banks can engage in implementation of new Virtual Assistants and Artificial Intelligence (A.I.) machine learning technologies, just as the other industries have engaged in modernizing i.e. medical checks, medical reports and evaluations, and this research paper will elaborate and emphasize the impact of artificial intelligence implementation on the banking sector processes. This research is based on both quantitative and model-based proofs of system performance by using several analytical tools, such as SPSS. The automation process helps institutions to enhance profitability, performance and to reduce human dependency. In a nutshell, Virtual Assistants powered with Artificial Intelligence improve the business process performance in every sector of business, especially the banking sector making it fast, reliable and not human dependent....
Understanding video files is a challenging task. While the current video understanding techniques rely on deep learning, the obtained results suffer from a lack of real trustful meaning. Deep learning recognizes patterns from big data, leading to deep feature abstraction, not deep understanding. Deep learning tries to understand multimedia production by analyzing its content. We cannot understand the semantics of a multimedia file by analyzing its content only. Events occurring in a scene earn their meanings from the context containing them. A screaming kid could be scared of a threat or surprised by a lovely gift or just playing in the backyard. Artificial intelligence is a heterogeneous process that goes beyond learning. In this article, we discuss the heterogeneity of AI as a process that includes innate knowledge, approximations, and context awareness. We present a contextaware video understanding technique that makes the machine intelligent enough to understand the message behind the video stream. The main purpose is to understand the video stream by extracting real meaningful concepts, emotions, temporal data, and spatial data from the video context.Thediffusion of heterogeneous data patterns from the video context leads to accurate decisionmaking about the video message and outperforms systems that rely on deep learning. Objective and subjective comparisons prove the accuracy of the concepts extracted by the proposed context-aware technique in comparison with the current deep learning video understanding techniques. Both systems are compared in terms of retrieval time, computing time, data size consumption, and complexity analysis. Comparisons show a significant efficient resource usage of the proposed context-aware system, which makes it a suitable solution for real-time scenarios. Moreover, we discuss the pros and cons of deep learning architectures....
The current e-commerce operation model has network defects such as network chaos and uneven network distribution, which affect economic development and progress. In response to the above problems, this article introduces the artificial intelligence system, optimizes and analyzes the structure of e-commerce websites, and combines the Internet economy with online website theory through independent screening and analysis of the artificial intelligence system. The concept of blockchain technology is introduced, and the characteristics of blockchain are analyzed through theory and data using quantitative analysis methods, and the problem of cross-border electronic payment is solved based on blockchain. Based on the analysis of artificial intelligence, an optimized online website innovation plan was obtained. Finally, the online website resource allocation variables are simulated, and the simulation method is used to test the scheme. The simulation test simulates the process of resource allocation, optimizes the use of innovative models, and hires professional financial personnel to observe records. The test verifies the effectiveness of the structure optimization of the e-commerce platform realized in this paper....
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