Unlocking the Future: Fostering Human–Machine Collaboration and Driving Intelligent Automation through Industry 5.0 in Smart Cities

Smart Cities, Journal Year: 2023, Volume and Issue: 6(5), P. 2742 - 2782

Published: Oct. 10, 2023

In the quest to meet escalating demands of citizens, future smart cities emerge as crucial entities. Their role becomes even more vital given current challenges posed by rapid urbanization and need for sustainable inclusive living spaces. At heart these are advancements in information communication technologies, with Industry 5.0 playing an increasingly significant role. This paper endeavors conduct exhaustive survey analyze including potential their implications cities. The crux is exploration technological across various domains that set shape urban environments. discussion spans diverse areas but not limited cyber–physical systems, fog computing, unmanned aerial vehicles, renewable energy, machine learning, deep cybersecurity, digital forensics. Additionally, sheds light on specific city context, illuminating its impact enabling advanced cybersecurity measures, fostering human–machine collaboration, driving intelligent automation services, refining data management decision making. also offers in-depth review existing frameworks shaping applications, evaluating how technologies could augment frameworks. particular, delves into face, bringing 5.0-enabled solutions fore.

Language: Английский

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Impact of Weather Factors on Unmanned Aerial Vehicles’ Wireless Communications

Future Internet, Journal Year: 2025, Volume and Issue: 17(1), P. 27 - 27

Published: Jan. 8, 2025

As the applications of unmanned aerial vehicles (UAV) expand, reliable communication between UAVs and ground control stations is crucial for successful missions. However, adverse weather conditions caused by atmospheric gases, clouds, fog, rain, turbulence pose challenges degrading signals. Although, some recent studies have explored nature signal attenuation variations, that compare from various analyze effect on available bandwidth are missing. This work aimed to address this research gap thoroughly investigating impact UAV communications. Quantitative qualitative performance analyses were performed using metrics such as bit error rate received signals associated with different modulation schemes frequencies, a linearly segmented model. The results indicate gases clouds/fog affect wireless propagation; however, rain propagation distances operating frequencies considered in study was most severe. Based influence power transmission, frequency, schemes, distance, suboptimization, we propose an algorithm select maximum frequency link operation.

Language: Английский

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Unmanned Aircraft Systems (UASs): Current State, Emerging Technologies, and Future Trends

Drones, Journal Year: 2025, Volume and Issue: 9(1), P. 59 - 59

Published: Jan. 15, 2025

Unmanned aircraft, commonly referred to as drones, represent a valuable alternative for various operational tasks due their versatility, flexibility, cost-effectiveness, and reusability. These features make them particularly advantageous in environments that are hazardous or inaccessible humans. Recent developments have highlighted significant increase the use of unmanned aircraft within metropolitan areas. This growth has necessitated implementation new regulations guidelines ensure safe integration UAS into urban environments. Consequently, concept UAM emerged. refers an innovative air transportation paradigm designed both passengers cargo settings, leveraging capabilities drones. review manuscript explores latest advancements UAS, focusing on updated regulations, definitions, enabling technologies, airspace classifications relevant operations. Additionally, it provides comprehensive overview systems, including classifications, key features, primary applications.

Language: Английский

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Target Detection and Recognition for Traffic Congestion in Smart Cities Using Deep Learning-Enabled UAVs: A Review and Analysis

Applied Sciences, Journal Year: 2023, Volume and Issue: 13(6), P. 3995 - 3995

Published: March 21, 2023

In smart cities, target detection is one of the major issues in order to avoid traffic congestion. It also key topics for military, traffic, civilian, sports, and numerous other applications. daily life, challenging serious tasks congestion due various factors such as background motion, small recipient size, unclear object characteristics, drastic occlusion. For examination, unmanned aerial vehicles (UAVs) are becoming an engaging solution their mobility, low cost, wide field view, accessibility trained manipulators, a threat people’s lives, ease use. Because these benefits along with good tracking effectiveness resolution, UAVs have received much attention transportation technology analyzing targets. However, objects UAV images usually small, so after neural estimation, large quantity detailed knowledge about may be missed, which results deficient performance actual recognition models. To tackle issues, many deep learning (DL)-based approaches been proposed. this review paper, we study end-to-end paradigm based on different DL approaches, includes one-stage two-stage detectors from observe under complex circumstances. Moreover, analyze evaluation work enhance accuracy, reduce computational optimize design. Furthermore, provided comparison differences technologies followed by future research trends.

Language: Английский

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AERIAL: A Meta Review and Discussion of Challenges Toward Unmanned Aerial Vehicle Operations in Logistics, Mobility, and Monitoring

IEEE Transactions on Intelligent Transportation Systems, Journal Year: 2023, Volume and Issue: 25(7), P. 6276 - 6289

Published: Dec. 28, 2023

There exists a tremendous number of research surveys on various aspects UAV logistics, mobility and monitoring tasks in the literature. These have been published distinct venues, often having significant overlap goals key findings. In this study, we provide meta review across nearly 100 extant overview papers, extract their messages, investigate extent being complementary. We develop AERIAL framework, which aggregates major challenges way to successful application UAVs for mobility, monitoring. believe that framework contribute towards clearer understanding scientific landscape identification potential directions future studies.

Language: Английский

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High-Resolution Feature Pyramid Network for Small Object Detection on Drone View

IEEE Transactions on Circuits and Systems for Video Technology, Journal Year: 2023, Volume and Issue: 34(1), P. 475 - 489

Published: June 16, 2023

Object detection has developed rapidly with the help of deep learning technologies recent years. However, object on drone view remains challenging due to two main reasons: (1) It is difficult detect small-scale objects lacking detailed information. (2) The diversity camera angles drones brings dramatic differences in scale. Although feature pyramid network (FPN) alleviates problem caused by scale difference some extent, it also retains worthless features, which wastes resources and slows down speed. In this work, we propose a novel High-Resolution Feature Pyramid Network (HR-FPN) improve accuracy avoid redundancy. key components HR-FPN include high-resolution alignment module (HRFA), fusion (HRFF) multi-scale decoupled head (MSDH). HRFA feeds features from backbone into parallel resampling channels obtain at same HRFF establishes bottom-up path distribute context-rich low-level semantic information all layers that are then aggregated classification localization feature. MSDH cope predicting categories locations corresponding different scales separately. Moreover, train model scale-weighted loss focus more objects. Extensive experiments comprehensive evaluations demonstrate effectiveness advancement our approach.

Language: Английский

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Strategies for Optimized UAV Surveillance in Various Tasks and Scenarios: A Review

Drones, Journal Year: 2024, Volume and Issue: 8(5), P. 193 - 193

Published: May 12, 2024

This review paper provides insights into optimization strategies for Unmanned Aerial Vehicles (UAVs) in a variety of surveillance tasks and scenarios. From basic path planning to complex mission execution, we comprehensively evaluate the multifaceted role UAVs critical areas such as infrastructure inspection, security surveillance, environmental monitoring, archaeological research, mining applications, etc. The analyzes detail effectiveness specific tasks, including power line bridge inspections, search rescue operations, police activities, monitoring. focus is on integration advanced navigation algorithms artificial intelligence technologies with UAV challenges operating environments. Looking ahead, this predicts trends cooperative networks explores potential more challenging not only researchers comprehensive analysis current state art, but also highlights future research directions, aiming engage inspire readers further explore missions.

Language: Английский

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Vehicle trajectory dataset from drone videos including off-ramp and congested traffic – Analysis of data quality, traffic flow, and accident risk

Communications in Transportation Research, Journal Year: 2024, Volume and Issue: 4, P. 100133 - 100133

Published: June 22, 2024

Language: Английский

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An Improved Artificial Potential Field UAV Path Planning Algorithm Guided by RRT Under Environment-aware Modeling: Theory and Simulation

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 12080 - 12097

Published: Jan. 1, 2024

Unmanned Aerial Vehicles (UAVs) have been extensively researched and used in civil military applications due to their effectiveness flexibility. However, when identifying obstacles avoiding them, most of the existing path planning methods fail accurately perceive environment, such as without considering differences between obstacles, which leads low timeliness easy fall into a local minimum. In this work, an improved artificial potential field UAV algorithm (G-APF) guided by rapidly-exploring random tree (RRT) based on environment-aware model is designed overcome limitations traditional methods. The can different objects environment through addition supervised modeling unsupervised planning. Specifically, YOLOv8 establish flight model, adaptive optimal threat distance calculation module construct repulsive field. Secondly, improve global awareness we first use G-APF plan rough environment. Then, initially generated trajectory replanned building attractive combining it with Finally, problems minimum target unreachability oscillation (APF) are solved G-APF. Experiments regions performed demonstrate efficiency proposed approach.

Language: Английский

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Advanced Aerial Monitoring and Vehicle Classification for Intelligent Transportation Systems with YOLOv8 Variants

Journal of Network and Computer Applications, Journal Year: 2025, Volume and Issue: unknown, P. 104134 - 104134

Published: Feb. 1, 2025

Language: Английский

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