Drone Compliance Standards

User interface for creating and modifying airspace restrictions for drones using non-digitized information. The interface allows human operators to quickly and easily convert analog information like phone calls and radio transmissions into digital airspace restrictions for drones. It provides fields for selecting restriction types, durations, locations, descriptions, and a task list to manage and access the restrictions. This enables efficient ingestion of non-digitized information into the drone fleet management system for creating or modifying airspace restrictions.

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Introduction. With the growing popularity of unmanned aircraft, many challenges anWith possibilities aviation use, there are and threats to state security. Effective introduction new technologies should be accompanied by creation an appropriate legal framework unified terminological apparatus. Currently, is a problem diversity in area question, affecting efficiency regulation. Methods. The research was based on general scientific methods such as analysis, categorisation, classification, typology statistical method, well private formal-legal, comparative-legal historical-legal methods. Results. As result research, author provides classification aerial vehicles (hereinafter referred UAVs) using characteristics aircraft systems UASs). These results can applied law enforcement practice qualification offences related use UASs, development normative acts effective measures counteract coming from unlawful UAVs. theoretical significance article consists methodologically verified functionally substantiated UAVs, eliminating uncertainty this area.

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Detect and Avoid (DAA) mechanisms for unmanned aerial systems (UAS) to enable safe beyond visual line of sight (BVLOS) operation. The DAA mechanism involves direct communication between UAS and network assistance for collision detection and conflict resolution. UAS register their DAA capabilities with a server. When requested by a serving airspace management unit (AMU), the UAS configures its DAA policy. If collision is detected, the UAS dynamically changes its flight path based on the policy. This enables network-assisted DAA beyond onboard sensors' range.

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ABSTRACT The European Union (EU) is making regulatory efforts to allow for the safe integration of drones into civilian airspace through automated means. Commission Implementing Regulation 2021/664 concerning unmanned traffic management (a system referred as USpace) furthers that commitment. Accordingly, drone operators must avail themselves automatic trafficrelated USpace services flight authorization, geo awareness, information, and network identification before entering USpace airspace. Using infrastructural analysis, proposed within Science Technology Studies (STS), this article shows while automation meant ensure traffic, it could also challenge safety in at least three ways: by inviting reliability concerns infrastructure; because transition from humancentric automationcentric systems; being subject irregularities EU's framework. An therefore, helps unveiling important factors which influence technologies critically discussing role law their regulation.

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A system for securely managing and verifying the identities of unmanned aerial systems (UAS) to enable safe integration of drones into airspace. The system provides a dynamic secure identification network that allows aircraft to share identification information through a permissioned blockchain-like network. It provides services like identity provisioning and verification to securely ingest private registration data, UAS identity verification requests, and returns validated identity and flight information. The system enables a standards-compliant utility service that functions with the Remote ID standard.

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Monitoring unmanned aerial systems (UAS) in a communication network to enable law enforcement to track and intercept UAS communications and locate UAS devices. It involves a network function requesting info about UAS devices from the mobility management, subscription management, and payload management devices. This provides data like UAS device IDs, subscriber info, flying rules, location, and intercepted comms. A central function collects and sends this to law enforcement.

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Enabling safe unmanned aerial vehicle (UAV) operations beyond visual line of sight by using ground-based and UAV-mounted observer devices to provide visual monitoring of the airspace and UAVs. The observer devices can be deployed around a designated area to cover it and provide a visual line of sight. UAVs with observer devices can fly to positions, land, hover, or autonomously to monitor other UAVs and conditions. This replaces human visual observers when not practical for BVLOS, high altitude, or unattended UAV flights.

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Enabling unmanned aerial vehicles (UAVs) to integrate safely into civilian airspace by leveraging wireless networks for detect and avoid (DAA) functionality. UAVs discover network-based DAA services, register to participate, and then use the network infrastructure for supplemental collision avoidance assistance beyond onboard sensors. This involves the UAV indicating association, the network confirming DAA availability, and the UAV registering to leverage network resources like localized DAA servers.

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Optimizing power control for unmanned aerial vehicles (UAVs) using orientation-based open loop power control (OLPC) for SL transmission of remote ID. The OLPC takes into account the UAV's orientation relative to a reference location to determine the optimal transmission power. This allows balancing between ensuring ground receipt and avoiding interference while UAVs fly at different heights and angles. The reference location could be a nearest base station or a predefined location.

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Ensuring safe operation of industrial machines like drones or agricultural equipment before starting the operation by checking if the operation area is registered. The system involves an industrial machine, an area acquisition device, and a control unit. The control unit has storage to store registered areas. When the machine requests to operate in a new area, the control unit checks if that area matches any registered areas. If not, it prevents the operation to avoid issues like drones spreading chemicals outside registered fields or collisions due to unidentified obstacles. This provides a safeguard against misuse and errors by confirming the operation area against known data.

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An acoustic-based detection and avoidance system for unmanned aircraft that uses a array of audio sensors to detect and locate nearby aircraft without radar. The system analyzes audio signals received by the sensors to estimate the position of intruding aircraft relative to the UAV. By detecting audio signals from other aircraft and analyzing their characteristics like frequency and timing, the system can determine the direction, range, and altitude of nearby aircraft without relying on heavy radar equipment. This allows UAVs to meet regulatory requirements for 360-degree detection and avoidance in a more cost-effective and lightweight manner compared to radar.

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Processing method to detect and prevent abnormal unmanned aerial vehicle (UAV) behavior like transmitting non-command and control (non-C2) data. The method involves a session management function (SMF) network element providing detection rules to user plane function (UPF) network elements. UPFs then detect non-C2 data in UAV transmissions and report back to SMF. SMF sends abnormal traffic reports to a network element with supervision capabilities to process and prevent transmission of non-C2 data. This allows detecting and stopping abnormal UAV behavior without disconnecting or switching controllers.

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Introducing drones in the Indian airspace is helping to improve tasks like security, movement of goods, rescue operations, and agricultural monitoring. This research looks into what happening now, UAVs are being used for, regulatory guidelines, limitations faced when using aviation sector India. Through use secondary data sources, policy documents, comments from experts, paper details how recent release Drone Rules 2021 has driven innovation at same time exposed shortcomings infrastructure, privacy protections, skilled employees. It clear study that although drone India developing fast, it will need support everyone become both sustainable scalable. text aimed outlining ways India, as well giving ideas for ensuring better management safety airspace. Keywords- drones, UAVs, aviation, DGCA, regulations, logistics, surveillance, integration

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The economic and social implications of the expanding drone ecosystem push need to extend Air Traffic Management implement Unmanned aircraft system Management. U-space, an European initiative launched in 2016, aims design a for managing integrating drones airspace, as well set services procedures guarantee airspace access large number drones. However, entry new users operations brings concerns, increasing risks cyberattacks are major factor U-space concerns. Indeed, standalone inherently introduce cyber threats that similar ones carried over by autonomous vehicles. Furthermore, involves many highly-exposed Cyber-Physical Systems, with growing vulnerabilities potentially conducting several threat scenarios security incidents affecting public spaces, critical facilities, citizens right privacy. These considerations lead necessity establish primary challenge proper security-by-design approaches. From research perspective, these result adoption automated risk assessment addressing complexity cost-efficiency engineering secure systems. Following this direction, work proposes preliminar... Read More

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Aerial traffic management system for unmanned aerial vehicles (UAVs) that enables efficient navigation through complex airspace. The system employs a centralized control server to generate navigation plans for multiple UAVs, with each plan specifying waypoints. When a UAV encounters an unoccupied waypoint, it is instructed to hover until clearance is obtained. Once cleared, the UAV proceeds to its destination. The system ensures safe separation between UAVs by dynamically locking occupied waypoints, enabling coordinated navigation through shared airspace.

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Automated flight response for unmanned aerial vehicles (UAVs) to comply with airspace restrictions around airports and other no-fly zones. The UAV calculates its distance from restricted areas using its own location and the location of the restrictions. If the distance is below a threshold, it takes immediate action like landing or preventing takeoff. If the distance is greater, it allows normal flight. This allows automated compliance with airspace rules while providing flexibility for safe operations when farther away.

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The aim of this article is to discuss the legal changes introduced in Poland response growing threat critical infrastructure facilities from unmanned aerial vehicles (UAVs) and present a recommended method for assessing effectiveness UAV detection neutralisation systems developed by Government Centre Security (RCB). authors amendment Act 3 July 2002 Aviation Law, which includes provisions relevant safety platform flights, ensuring that operators have right defend protected facility against attacks using aircraft, 24 May 2013 on direct coercive measures firearms, expanded catalogue include destruction or immobilisation seizure control over its flight, indicated means neutralisation.

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Detecting drones approaching restricted areas and preventing them from entering using 5G network technology. When drones are detected near restricted areas like airports, military bases, or government buildings, the network reduces the power of beams that could steer the drones into those areas. This is done by having the base stations near the restricted area disable certain beams and reduce the power of others. This forces the drones to use alternative beams that avoid the restricted area. This creates a virtual geofence around the restricted area using 5G network capabilities. The network also enables beamforming on the base stations near restricted areas to steer drones away. This involves detecting drones approaching, estimating which beams they will use, and disabling or powering down those beams to force them to use different beams.

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Detecting and responding to flight-restricted regions for unmanned aerial vehicles (UAVs) to permit automated flight control in response to detected proximity to restricted areas. The method involves calculating distances between the UAV and flight-restricted regions using location data. If the distance falls within certain thresholds, flight response measures like landing or preventing takeoff are initiated. This provides automated response to restricted areas with graded actions based on proximity. It also uses location systems to accurately detect restricted areas.

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Automating drone waiver requests in emergency situations to expedite approval and reduce delays. The system uses AI to identify and describe incidents, communicate instantly with requesters, and validate data. It aims to provide faster, more efficient waiver processing for emergency drone operations compared to manual methods.

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