UAV Management System for the Smart City

Sul'aj, Peter; Haluška, Renát; Ovsenik, L'ubes; Marchevsky, S.; Pulli, Petri; Kramar, Vadim

doi:10.1109/disa.2018.8490535

Cited by 3 publications

(3 citation statements)

References 6 publications

(5 reference statements)

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“…The proposed framework allowed to automatically learn the airspace structure, assess the use of the airspace and identify patterns of airspace usage. For this, it included three modules: (1) clustering flight trajectories at the spatial scale to identify trajectory patterns, (2) trajectory classification by using Random Forests algorithm to assess flight trajectory conformance against the learned airspace structure and identify air traffic flows, (3) clustering air traffic flows at the temporal scale to identify traffic flow patterns. This framework was used to obtain a detailed characterization of air traffic flows in the terminal areas of multi-airport systems including New York, Hong Kong and Sao Paulo.…”

Section: B Flight Data Analysis and Traffic Pattern Identificationmentioning

confidence: 99%

“…If the precipitation is heavy, the amount of rain falling on the UAV's wings per 𝑐𝑚 2 area causes an imbalance in the weights of left and right wings. Equation (1) gives the imbalance of weight expressed as:…”

Section: ) Precipitationmentioning

confidence: 99%

“…In recent times, the civilian applications of UAVs have risen across diverse fields due to their versatile functionality, automation capabilities and low cost. The application areas of UAVs for both consumer and industry include business and marketing, surveying and monitoring, emergency services and healthcare, delivery services, gaming and sports telecasting, news reporting, the education sector, military, security, and many other fields [1], [2].…”

Section: Introductionmentioning

confidence: 99%

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Modeling and Characterization of Traffic Flow Patterns and Identification of Airspace Density for UTM Application

2022

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Current airspace has limited resources, and the widespread use of unmanned aerial vehicles (UAVs) increases airspace density, which is already crowded with manned aircraft. This demands the improvement of airspace safety and capacity while considering all parametric uncertainties that may hinder aircraft and UAV mobility such as dynamic airspace structures and weather conditions. This paper proposes a data analytics framework to characterize traffic flow patterns of unmanned traffic management (UTM) airspace by analyzing simulated historical data. Mission patterns are characterized and identified by considering multiple UAV missions and scenarios with different priority levels to highlight UAVs' trajectories and deviations from the actual path due to these constraints. The pertinent data analysis supports risk analysis and improves trajectory planning in different airspace regions considering all dynamic parameters such as extreme weather, emergency services, and dynamic airspace structures. The data processing framework, which is density-based spatial clustering of applications with noise (DBSCAN), identified significant deviations in mission patterns with almost 82% confidence level. The UTM traffic flow characterization is conducted by three key characterization parameters mainly Distance from Centroid (DFC), Distance to Complete Mission (DTCM) and Time to Complete Mission (TTCM). This work also analyzed the airspace congestion using the Kernel density estimation (KDE). This analysis identified some regions of interference as potential congested areas representing safety concerns. The proposed framework is envisioned to assist UTM authority by characterizing air traffic behavior, managing its flow, improving airspace design, and providing the basis for developing predictive capabilities that support traffic flow management.

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Section: B Flight Data Analysis and Traffic Pattern Identificationmentioning

confidence: 99%

Section: ) Precipitationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modeling and Characterization of Traffic Flow Patterns and Identification of Airspace Density for UTM Application

2022

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Parallel Image Signal Processing in a Distributed Car Plate Recognition System

Handrik

Handriková

Vaško

2020

2020 New Trends in Signal Processing (NTSP)

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Automated system for dispatching the movement of unmanned aerial vehicles with a distributed survey of flight tasks

Gura

Rukhlinskiy²,

Шаров

et al. 2021

Journal of Intelligent Systems

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Over the past decade, unmanned aerial vehicles (UAVs) have received increasing attention and are being used in the areas of harvesting, videotaping, and the military industry. In this article, the consideration is focused on areas where video recording is required for ground inspections. This paper describes modern communication technologies and systems that enable interaction and data exchange between UAVs and a ground control station (GCS). This article focuses on different architectures of communication systems, establishing the characteristics of each to identify the preferred architecture that does not require a significant consumption of resources and whose data transmission is reliable. A coherent architecture that includes multiple UAVs, wireless sensor networks, cellular networks, GCSs, and satellite network to duplicate communications for enhanced system security has been offered. Some reliability problems have been discussed, the solution of which was suggested to be a backup connection via satellite, i.e., a second connection. This study focused not only on the communication channels but also on the data exchanged between system components, indicating the purpose of their application. Some of the communication problems and shortcomings of various systems, as well as further focus areas and improvement recommendations were discussed.

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UAV Management System for the Smart City

Cited by 3 publications

References 6 publications

Modeling and Characterization of Traffic Flow Patterns and Identification of Airspace Density for UTM Application

Modeling and Characterization of Traffic Flow Patterns and Identification of Airspace Density for UTM Application

Parallel Image Signal Processing in a Distributed Car Plate Recognition System

Automated system for dispatching the movement of unmanned aerial vehicles with a distributed survey of flight tasks

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