Remote ID for separation provision and multi-agent navigation

In this paper, we investigate the integration of drone identification data (Remote ID) with collision avoidance mechanisms to improve the safety and efficiency of multi-drone operations. We introduce an improved Near Mid-Air Collision (NMAC) definition, termed as UAV NMAC (uNMAC), which accounts for uncertainties in the drone's location due to self-localization errors and possible displacements between two location reports. Our proposed uNMAC-based Reciprocal Velocity Obstacle (RVO) model integrates Remote ID messages with RVO to enable enhanced collision-free navigation. We propose modifications to the Remote ID format to include data on localization accuracy and drone airframe size, facilitating more efficient collision avoidance decisions. Through extensive simulations, we demonstrate that our approach halves mission execution times compared to a conservative standard Remote ID-based RVO. Importantly, it ensures collision-free operations even under localization uncertainties. By integrating the improved Remote ID messages and uNMAC-based RVO, we offer a solution to significantly increase airspace capacity while adhering to strict safety standards. Our study emphasizes the potential to augment the safety and efficiency of future drone operations, thereby benefiting industries reliant on drone technologies.Comment: 10 pages, 8 figures, 2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC

Constructing Dynamic Ad-hoc Emergency Networks using Software-Defined Wireless Mesh Networks

Natural disasters and other emergency situations have the potential to destroy a whole network infrastructure needed for communication critical to emergency rescue, evacuation, and initial rehabilitation. Hence, the research community has begun to focus attention on rapid network reconstruction in such emergencies; however, research has tried to create or improve emergency response systems using traditional radio and satellite communications, which face high operation costs and frequent disruptions. This thesis proposes a centralized monitoring and control system to reconstruct ad-hoc networks in emergencies by using software-defined wireless mesh networks (SDWMN). The proposed framework utilizes wireless mesh networks and software-defined networking to provide real-time network monitoring services to restore Internet access in a targeted disaster zone. It dispatches mobile devices including unmanned aerial vehicles and self-driving cars to the most efficient location aggregation to recover impaired network connections by using a new GPS position finder (GPS-PF) algorithm. The algorithm is based on density-based spatial clustering that calculates the best position to deploy one of the mobile devices. The proposed system is evaluated using the common open research emulator to demonstrate its efficiency and high accessibility in emergency situations. The results obtained from the evaluation show that the performance of the emergency communication system is improved considerably with the incorporation of the framework

Passive Radiolocation of IEEE 802.11 Emitters using Directional Antennae

Low-cost commodity hardware and cheaper, more capable consumer-grade drones make the threat of home-made, inexpensive drone-mounted wireless attack platforms (DWAPs) greater than ever. Fences and physical security do little to impede a drone from approaching private, commercial, or government wireless access points (WAPs) and conducting wireless attacks. At the same time, unmanned aerial vehicles (UAVs) present a valuable tool for network defenders conducting site surveys and emulating threats. These platforms present near-term dangers and opportunities for corporations and governments. Despite the vast leaps in technology these capabilities represent, UAVs are noisy and consequently difficult to conceal as they approach a potential target; stealth is a valuable asset to an attacker. Using a directional antenna instead of the typical omnidirectional antenna would significantly increase the distance from which a DWAP may conduct attacks and would improve their stealthiness and overall effectiveness. This research seeks to investigate the possibility of using directional antennae on DWAPs by resolving issues inhibiting directional antennae use on consumer and hobbyist drone platforms. This research presents the hypothesis that a DWAP equipped with a directional antenna can predict bearings and locations of WAPs within an acceptable margin of error

Improving a wireless localization system via machine learning techniques and security protocols

The recent advancements made in Internet of Things (IoT) devices have brought forth new opportunities for technologies and systems to be integrated into our everyday life. In this work, we investigate how edge nodes can effectively utilize 802.11 wireless beacon frames being broadcast from pre-existing access points in a building to achieve room-level localization. We explain the needed hardware and software for this system and demonstrate a proof of concept with experimental data analysis. Improvements to localization accuracy are shown via machine learning by implementing the random forest algorithm. Using this algorithm, historical data can train the model and make more informed decisions while tracking other nodes in the future. We also include multiple security protocols that can be taken to reduce the threat of both physical and digital attacks on the system. These threats include access point spoofing, side channel analysis, and packet sniffing, all of which are often overlooked in IoT devices that are rushed to market. Our research demonstrates the comprehensive combination of affordability, accuracy, and security possible in an IoT beacon frame-based localization system that has not been fully explored by the localization research community

Managing Visibility and Validity of Distress Calls with an Ad-Hoc SOS System

The availability of ICT services can be severely disrupted in the aftermath of disasters. Ad-hoc assemblages of communication technology have the potential to bridge such breakdowns. This article investigates the use of an ad-hoc system for sending SOS signals in a large-scale exercise that simulated a terrorist attack. In this context, we found that the sensitivity that was introduced by the adversarial nature of the situation posed unexpected challenges for our approach, as giving away one's location in the immediate danger of a terrorist attack became an issue both for first responders and the affected people in the area. We show how practices of calling for help and reacting to help calls can be affected by such a system and affect the management of the visibility and validity of SOS calls, implying a need for further negotiation in situations where communication is sensitive and technically restrained

Multimodal Interaction for Enhancing Team Coordination on the Battlefield

Team coordination is vital to the success of team missions. On the battlefield and in other hazardous environments, mission outcomes are often very unpredictable because of unforeseen circumstances and complications encountered that adversely affect team coordination. In addition, the battlefield is constantly evolving as new technology, such as context-aware systems and unmanned drones, becomes available to assist teams in coordinating team efforts. As a result, we must re-evaluate the dynamics of teams that operate in high-stress, hazardous environments in order to learn how to use technology to enhance team coordination within this new context. In dangerous environments where multi-tasking is critical for the safety and success of the team operation, it is important to know what forms of interaction are most conducive to team tasks. We have explored interaction methods, including various types of user input and data feedback mediums that can assist teams in performing unified tasks on the battlefield. We’ve conducted an ethnographic analysis of Soldiers and researched technologies such as sketch recognition, physiological data classification, augmented reality, and haptics to come up with a set of core principles to be used when de- signing technological tools for these teams. This dissertation provides support for these principles and addresses outstanding problems of team connectivity, mobility, cognitive load, team awareness, and hands-free interaction in mobile military applications. This research has resulted in the development of a multimodal solution that enhances team coordination by allowing users to synchronize their tasks while keeping an overall awareness of team status and their environment. The set of solutions we’ve developed utilizes optimal interaction techniques implemented and evaluated in related projects; the ultimate goal of this research is to learn how to use technology to provide total situational awareness and team connectivity on the battlefield. This information can be used to aid the research and development of technological solutions for teams that operate in hazardous environments as more advanced resources become available

Infrastructure Wi-Fi for connected autonomous vehicle positioning : a review of the state-of-the-art

In order to realize intelligent vehicular transport networks and self driving cars, connected autonomous vehicles (CAVs) are required to be able to estimate their position to the nearest centimeter. Traditional positioning in CAVs is realized by using a global navigation satellite system (GNSS) such as global positioning system (GPS) or by fusing weighted location parameters from a GNSS with an inertial navigation systems (INSs). In urban environments where Wi-Fi coverage is ubiquitous and GNSS signals experience signal blockage, multipath or non line-of-sight (NLOS) propagation, enterprise or carrier-grade Wi-Fi networks can be opportunistically used for localization or “fused” with GNSS to improve the localization accuracy and precision. While GNSS-free localization systems are in the literature, a survey of vehicle localization from the perspective of a Wi-Fi anchor/infrastructure is limited. Consequently, this review seeks to investigate recent technological advances relating to positioning techniques between an ego vehicle and a vehicular network infrastructure. Also discussed in this paper is an analysis of the location accuracy, complexity and applicability of surveyed literature with respect to intelligent transportation system requirements for CAVs. It is envisaged that hybrid vehicular localization systems will enable pervasive localization services for CAVs as they travel through urban canyons, dense foliage or multi-story car parks

Control Of 3d Printer Using Drone With Autopilot And Raspberry Pi Microcontroller

Rapid prototyping or 3D printing technology is the advanced manufacturing process and it is getting popular to many sectors of field. However, there are some limitation of this technology which is limited to the printer size. This study focuses on combining of drone technology and rapid prototyping technology. Therefore, control the 3D printer using drone that paired with autopilot and microcontroller can build an object without considering the size of printer. The conversion of tool path to the flight path is done. Two flight paths for printing a rectangular sheet with size of 2m×8m and 20m×80m are generated. The simulation results show the flight path with size of 2m×8m is better than flight path with size of 20m×80m. However, this is concern to the resolution of global positioning system. This paper has made a big step toward the idea of combining the 2 technologies