Exploring the Next Frontier in Wireless Communication: 5G and Beyond for Enhanced Reliability and Low Latency in IoT and Autonomous Technologies DOI Open Access
Deepak Kumar Sharma, K. Lakshmi Narayana,

P Shyamala

et al.

Nanotechnology Perceptions, Journal Year: 2024, Volume and Issue: unknown, P. 676 - 689

Published: Dec. 1, 2024

This research focuses on how 5G and beyond technologies might be the game changers in reliability, low latency, efficiency, improvement of IoT autonomous systems, such as electric vehicles. It addresses advancements 6G-based communication networks integrated with machine learning edge computing to enhance vehicle performance, energy management, vehicle-to-infrastructure (V2I) communication. Extensive experimentation conducted greatly led discovery important improvements response time. Latency was reduced by much 45 per cent when compared 4G networks, this meant that 6G enabled potential increases up 60 over data throughput reliability high-density environments. In addition that, AI application towards predictive maintenance battery optimization an increase 30 for applications intelligence a more sustainable EV system. The results further reveal promise AI-based security ML-based 25% reduction network vulnerabilities traditional protocols. inform transformative capability next generations fulfil their scope remodelling future vehicles systems. Future will focus overcoming present infrastructure deficiencies improving algorithms behind real-time decision-making processes support scalable, energy-efficient, secure ecosystems.

Language: Английский

Recent Advancements in Morphing Applications: Architecture, Artificial Intelligence Integration, Challenges, and Future Trends- A Comprehensive Survey DOI Creative Commons
Md. Najmul Mowla, Davood Asadi,

Tahir Durhasan

et al.

Aerospace Science and Technology, Journal Year: 2025, Volume and Issue: 161, P. 110102 - 110102

Published: Feb. 26, 2025

Language: Английский

Citations

1
Machine Learning-Based and AI Powered Satellite Imagery Processing for Global Air Traffic Surveillance Systems DOI
Fredrick Kayusi, Petros Chavula,

Linety Juma

et al.

LatIA, Journal Year: 2025, Volume and Issue: 3, P. 82 - 82

Published: Feb. 19, 2025

The unprecedented growth of global air traffic has put immense pressure on the management systems. In light that, situational awareness and surveillance are indispensable, especially for satellite-based aircraft tracking There been some crucial development in field; however, every major player this arena relies a single proprietary, non-transparent data feed. This is where chapter differentiates itself. AIS gaining traction recently same purpose matured considerably over past decade; communication service providers have failed to instrument significant portions world’s oceans. study proposes multimodal artificial intelligence-powered algorithm boost estimates using Global Air Traffic Visualization dataset. Two intelligence agents categorically detect streaks huge collection satellite images notify geospatial temporal statistical agent whenever both modalities concordance. A user can fine-tune threshold hyperparameter based installed detection rate datasets get best satellite-derived estimates.

Language: Английский

Citations

0
Digital Twin Framework for Aircraft Lifecycle Management Based on Data-Driven Models DOI Creative Commons
Igor Kabashkin

Mathematics, Journal Year: 2024, Volume and Issue: 12(19), P. 2979 - 2979

Published: Sept. 25, 2024

This paper presents a comprehensive framework for implementing digital twins in aircraft lifecycle management, with focus on using data-driven models to enhance decision-making and operational efficiency. The proposed integrates cutting-edge technologies such as IoT sensors, big data analytics, machine learning, 6G communication, cloud computing create robust twin ecosystem. explores the key components of framework, including phases, new technologies, twins. It discusses challenges creating accurate during operation maintenance proposes solutions emerging technologies. incorporates physics-based, data-driven, hybrid simulate predict behavior. Supporting like federated analytics tools enable seamless integration operation. also examines models, knowledge-driven approach, limitations current implementations, future research directions. holistic aims transform fragmented into comprehensive, real-time representations that can safety, efficiency, sustainability throughout lifecycle.

Language: Английский

Citations

3
Managing Operational Efficiency and Reducing Aircraft Downtime by Optimization of Aircraft On-Ground (AOG) Processes for Air Operator DOI Creative Commons
Iyad Alomar,

D Mukhlynin Nikita

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(9), P. 5129 - 5129

Published: May 5, 2025

This research aims to identify patterns and root causes of aircraft downtimes by comparing various forecasting models used in the aviation industry prevent AOG events effectively. At its heart, this study explores innovative using time series analysis, modeling binary classification predict spare part usage, reduce downtime, tackle complexities managing inventory for diverse fleets. By analyzing both data insights shared experts, offers a practical roadmap enhancing supply chain efficiency reducing Mean Time Between Failures (MTBF). The thesis emphasizes how real-time integration hybrid approaches can transform operations, helping airlines keep parts available when where they are needed most. It also shows precise is not just about saving costs, it boosting customer satisfaction staying competitive an ever-demanding industry. In addition data-driven insights, provides actionable recommendations, such as embracing predictive maintenance strategies streamlining logistics. These steps aim ensure smoother fewer disruptions, more reliable service passengers operators alike.

Language: Английский

Citations

0
AIoT in Healthcare and Remote Monitoring DOI

Anuska Dutta,

Diya Biswas,

Piyal Roy

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 269 - 298

Published: May 8, 2025

Integration of AI and IoT has contributed a lot to improve healthcare real-time patient monitoring predictive analysis patients' health. This chapter focuses on IoT-based telehealth devices that assess essential health parameters from distance thus improving quality the care minimizing risks spreading diseases. These systems are intelligently implemented by cloud computing machine learning they foresee anomalies help in treatment plans. One innovations reported is CNN for screening arrhythmias wearable while athletes action offer results with high level precision. The also explores transition conventional methods aircraft towards AIoT employ data maintenance as well safety enhancements. prospect use revealed focus its utilization identification hazardous compounds consideration environment.

Language: Английский

Citations

0
Unified Aviation Maintenance Ecosystem on the Basis of 6G Technology DOI Open Access
Igor Kabashkin

Electronics, Journal Year: 2024, Volume and Issue: 13(19), P. 3824 - 3824

Published: Sept. 27, 2024

The advent of 6G technology will transforms aviation, particularly in the realm aircraft health monitoring systems (AHMSs). This paper explores transformative potential enhancing real-time data exchange, predictive maintenance, and overall communication efficiency within aviation sector. By using ultra-fast transmission, low latency, advanced AI integration, enables development a unified AHMS architecture that significantly improves safety, operational efficiency, reliability. proposed eight-layer model, incorporating digital twins, federated learning, edge computing, showcases how can revolutionize maintenance by providing continuous, decision-making capabilities.

Language: Английский

Citations

2
NFT-Based Framework for Digital Twin Management in Aviation Component Lifecycle Tracking DOI Creative Commons
Igor Kabashkin

Algorithms, Journal Year: 2024, Volume and Issue: 17(11), P. 494 - 494

Published: Nov. 2, 2024

The paper presents a novel framework for implementing decentralized algorithms based on non-fungible tokens (NFTs) digital twin management in aviation, with focus component lifecycle tracking. proposed approach uses NFTs to create unique, immutable representations of physical aviation components capturing real-time records component’s entire lifecycle, from manufacture retirement. This outlines detailed workflows key processes, including part tracking, maintenance records, certification and compliance, supply chain management, flight logs, ownership leasing, technical documentation, quality assurance. introduces class designed manage the complex relationships between components, their twins, associated NFTs. A unified model is presented demonstrate how are created updated across various stages ensuring data integrity, regulatory operational efficiency. also discusses architecture system, exploring sources, blockchain, NFTs, other critical components. It further examines main challenges NFT-based future research directions.

Language: Английский

Citations

1
Exploring the Next Frontier in Wireless Communication: 5G and Beyond for Enhanced Reliability and Low Latency in IoT and Autonomous Technologies DOI Open Access
Deepak Kumar Sharma, K. Lakshmi Narayana,

P Shyamala

et al.

Nanotechnology Perceptions, Journal Year: 2024, Volume and Issue: unknown, P. 676 - 689

Published: Dec. 1, 2024

This research focuses on how 5G and beyond technologies might be the game changers in reliability, low latency, efficiency, improvement of IoT autonomous systems, such as electric vehicles. It addresses advancements 6G-based communication networks integrated with machine learning edge computing to enhance vehicle performance, energy management, vehicle-to-infrastructure (V2I) communication. Extensive experimentation conducted greatly led discovery important improvements response time. Latency was reduced by much 45 per cent when compared 4G networks, this meant that 6G enabled potential increases up 60 over data throughput reliability high-density environments. In addition that, AI application towards predictive maintenance battery optimization an increase 30 for applications intelligence a more sustainable EV system. The results further reveal promise AI-based security ML-based 25% reduction network vulnerabilities traditional protocols. inform transformative capability next generations fulfil their scope remodelling future vehicles systems. Future will focus overcoming present infrastructure deficiencies improving algorithms behind real-time decision-making processes support scalable, energy-efficient, secure ecosystems.

Language: Английский

Citations

0