Smart cities: Fusion-based intelligent traffic congestion control system for vehicular networks using machine learning techniques

Egyptian Informatics Journal, Год журнала: 2022, Номер 23(3), С. 417 - 426

Опубликована: Апрель 13, 2022

Smart cities have been developed over the past decade, and reducing traffic congestion has top concern in smart city development. Short delays communication between vehicles Roadside Units (RSUs), smooth flow, road safety are key challenges of Intelligent Transportation Systems (ITSs). The rapid upsurge number increased accidents. To fix this issue, Vehicular Networks (VNs) many new ideas, including vehicular communications, navigation, control. Machine Learning (ML) is an efficient approach to finding hidden insights into ITS without being programmed explicitly by learning from data. This research proposed a fusion-based intelligent control system for VNs (FITCCS-VN) using ML techniques that collect data route on available routes alleviate cities. provides innovative services drivers enable view flow volume remotely, intending avoid jams. model improves decreases congestion. accuracy 95% miss rate 5%, which better than previous approaches.

Язык: Английский

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Fusion-Based Supply Chain Collaboration Using Machine Learning Techniques

Intelligent Automation & Soft Computing, Год журнала: 2021, Номер 31(3), С. 1671 - 1687

Опубликована: Окт. 10, 2021

Supply Chain Collaboration is the network of various entities that work cohesively to make up entire process. The supply chain organizations’ success dependent on integration, teamwork, and communication information. Every day, business players in a dynamic setting. They must balance competing goals such as process robustness, risk reduction, vulnerability real financial risks, resilience against just-in-time cost-efficiency. Decision-making based shared information constitutes recital competitiveness collective has prompted companies implement perfect data analytics functions (e.g., science, predictive analytics, big data) improve operations and, eventually, efficiency. Simulation modeling are powerful methods for analyzing, investigating, examining, observing evaluating real-world industrial logistic processes this scenario. Fusion-based Machine learning provides platform may address issues/limitations Collaboration. Compared Classical probable fusion techniques, fused method offer strong computing ability prediction. In scenario, machine learning-based model been proposed evaluate propensity decision-making increase efficiency

Язык: Английский

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MapReduce based intelligent model for intrusion detection using machine learning technique

Journal of King Saud University - Computer and Information Sciences, Год журнала: 2021, Номер 34(10), С. 9723 - 9731

Опубликована: Дек. 16, 2021

With the emergence of Internet Things (IoT), computer networks' phenomenal expansion, and enormous relevant applications, data is continuously increasing. In this way, cybersecurity has gained significant importance in protecting networks from different cyber-attacks like Intrusions, Denial-of-Service (DoS), Eavesdropping, Rushing Attack, etc. A traditional Intrusion Detection System (IDS) tangled with clustering technique plays a vital role modern security. Still, it limitations to analyze vast volumes identify an anomaly intelligently. Machine learning that may be MapReduce-Based Intelligent Model for (MR-IMID) automate intrusion detection MR-IMID proposed detect intrusions on network multiple classification tasks research work. The processes big sets reliably using commodity hardware. work, sources are being utilized Real-time detection. research, detects by predicting unknown test scenarios stores database minimize future inconsistencies. accuracy model during training validation phases 97.7% 95.7%, respectively, which better than previously published approaches.

Язык: Английский

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5G Campus Networks: A First Measurement Study

IEEE Access, Год журнала: 2021, Номер 9, С. 121786 - 121803

Опубликована: Янв. 1, 2021

A 5G campus network is a for the users affiliated with organization, e.g., an industrial campus, covering prescribed geographical area. can operate as so-called non-stand-alone (NSA) (which requires 4G Long-Term Evolution (LTE) spectrum access) or standalone (SA) (without LTE access). networks are envisioned to enable new use cases, which require cyclic delay-sensitive communication, such robot control. We design rigorous testbed measuring one-way packet delays between end device via radio access (RAN) core sub-microsecond precision well delay nanosecond precision. With our design, we conduct detailed measurements of download (downstream, i.e., device) upload (upstream, core) and losses both non-standalone hardware operation.We also measure corresponding SA NSA processing upload. find that typically 95% in range from 4–10 ms, indicating fairly wide spread delays. Also, existing implementations regularly incur latencies up 0.4 outliers above one millisecond. Our measurement results inform further development refinement cases. make data traces publicly available IEEE DataPort Campus Networks: Measurement Traces dataset (DOI 10.21227/xe3c-e968).

Язык: Английский

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Survey on Device to Device (D2D) Communication for 5GB/6G Networks: Concept, Applications, Challenges, and Future Directions

IEEE Access, Год журнала: 2022, Номер 10, С. 30792 - 30821

Опубликована: Янв. 1, 2022

Device-to-device (D2D) communication is one of the most promising technologies in wireless cellular networks that can be employed to improve spectral and energy efficiency, increase data rates, reduce links latency. This paper investigates fifth generation beyond (5GB) networks, basics D2D communication, applications, classification. Herein, in-band (IBD) out-band (OBD) modes are discussed. also presents integration with other prominent demonstrates importance possible solutions improving network performance. We further investigate challenges opportunities, future research directions 5GB networks. In addition, 6G open areas introduced.

Язык: Английский

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Smart cities: the role of Internet of Things and machine learning in realizing a data-centric smart environment

Complex & Intelligent Systems, Год журнала: 2023, Номер 10(1), С. 1607 - 1637

Опубликована: Июль 27, 2023

Abstract This paper explores the concept of smart cities and role Internet Things (IoT) machine learning (ML) in realizing a data-centric environment. Smart leverage technology data to improve quality life for citizens enhance efficiency urban services. IoT have emerged as key technologies enabling city solutions that rely on large-scale collection, analysis, decision-making. presents an overview cities’ various applications discusses challenges associated with implementing environments. The also compares different case studies successful implementations utilizing technologies. findings suggest these potential transform environments enable creation more livable, sustainable, efficient cities. However, significant remain regarding privacy, security, ethical considerations, which must be addressed realize full

Язык: Английский

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A survey of mobility-aware Multi-access Edge Computing: Challenges, use cases and future directions

Ad Hoc Networks, Год журнала: 2022, Номер 140, С. 103044 - 103044

Опубликована: Ноя. 18, 2022

Язык: Английский

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A comprehensive survey on 6G and beyond: Enabling technologies, opportunities of machine learning and challenges

Computer Networks, Год журнала: 2023, Номер 237, С. 110085 - 110085

Опубликована: Ноя. 6, 2023

Язык: Английский

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Enhancing patient healthcare with mobile edge computing and 5G: challenges and solutions for secure online health tools

Journal of Cloud Computing Advances Systems and Applications, Год журнала: 2024, Номер 13(1)

Опубликована: Май 2, 2024

Abstract Patient-focused healthcare applications are important to patients because they offer a range of advantages that add value and improve the overall experience. The 5G networks, along with Mobile Edge Computing (MEC), can greatly transform applications, which in turn improves patient care. MEC plays an role by bringing computing resources edge network. It becomes part IoT system within brings data closer core, speeds up decision-making, lowers latency, quality While usage networks is beneficial for purposes, there some issues difficulties should be solved efficient introduction this technological pair into healthcare. One critical blockchain technology help overcome challenge faced realizing most potential involving medical devices. This article presents comprehensive literature review on IoT-based devices, provide real-time solutions patients, discusses major contributions made industry. paper also limitations have devices area, especially field decentralized solutions. For reason, readership intended not only researchers but graduate students.

Язык: Английский

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Ultra-Wideband Radar-Based Indoor Activity Monitoring for Elderly Care

Sensors, Год журнала: 2021, Номер 21(9), С. 3158 - 3158

Опубликована: Май 2, 2021

In this paper, we propose an unobtrusive method and architecture for monitoring a person’s presence collecting his/her health-related parameters simultaneously in home environment. The system is based on using single ultra-wideband (UWB) impulse-radar as sensing device. Using UWB radars, aim to recognize person some preselected movements without camera-type monitoring. Via the experimental work, have also demonstrated that, by signal, it possible detect small chest remotely coughing, example. addition, statistical data analysis, posture room can be recognized steady situation. implemented machine learning technique (k-nearest neighbour) automatically classify static radar data. Skewness, kurtosis received power are used classification during postprocessing. accuracy achieved more than 99%. present reliability fault tolerance analyses three kinds of network architectures point out weakest item installation. This information highly important system’s implementation.

Язык: Английский

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