Over the past decade, there has been a remarkable acceleration in evolution of smart cities and intelligent spaces, driven by breakthroughs technologies such as Internet Things (IoT), edge–fog–cloud computing, machine learning (ML)/artificial intelligence (AI). As society begins to harness full potential these environments, horizon brightens with promise an immersive, interconnected 3D world. The forthcoming paradigm shift how we live, work, interact owes much groundbreaking innovations...

Over the past decade, there has been a remarkable acceleration in evolution of smart cities and intelligent spaces, driven by breakthroughs technologies such as Internet Things (IoT), edge-fog-cloud computing, machine learning (ML)/Artificial Intelligence (AI). As society begins to harness full potential these environments, horizon brightens with promise an immersive, interconnected 3D world. The forthcoming paradigm shift how we live, work, interact owes much groundbreaking innovations...

The proliferation of Unmanned Aerial Vehicle (UAV) networks is increasing, driven by their capacity to deliver automated services tailored the varied demands numerous smart city applications. Trust, security, and privacy remain paramount in public domain. Traditional centralized network designs fall short ensuring device authentication, data integrity, within UAV networks’ highly dynamic adaptable environments. Decentralized reputation systems emerge as a promising solution enhance...

The introduction of Global Positioning System (GPS) has greatly transformed navigation services; however, GPS remains vulnerable to threats such as spoofing attacks. While machine learning (ML) methods have shown promise in detecting these attacks, they often lack interpretability, causing uncertainty about the reasons for classifying a signal spoofed. Furthermore, ML typically overlooked underlying causal relationships among features, which offer valuable insights analysis and strategies...

To effectively track resident space objects (RSOs), the tasking of sensors in a distributed network requires flexible and adaptive approaches. While Deep Reinforcement Learning (DRL) has shown potential solving sensor allocation problem (SAP), resulting solutions lack transparency, combinatorial complexity SAP remains uninterpretable. address this, we propose method that utilizes counterfactual explanation to explain reasoning behind DRL agents' RSO selection. This involves building an...

Low probability of intercept (LPI) radar waveform recognition is one the crucial functions in electronic intelligence systems. Advances artificial promote performance LPI with various signal features defined analytical expressions. However, noisy still a challenge for traditional approaches even noise elimination techniques, especially heavily contaminated signals. Recently, adaptive analysis such as variational mode decomposition (VMD) and empirical (EMD) provide potential methods that...

Rapid advancements in the fifth generation (5G) communication technology and mobile edge computing (MEC) paradigm have led to proliferation of unmanned aerial vehicles (UAV) urban air mobility (UAM) networks, which provide intelligent services for diversified smart city scenarios. Meanwhile, widely deployed Internet drones (IoD) cities has also brought up new concerns regarding performance, security, privacy. The centralized framework adopted by conventional UAM networks is not adequate...

Space object tracking and maneuver detection play an essential role in space situation awareness (SSA). The ordinary Kalman filter its variants may give large error due to the of object. In this paper, consistently track a maneuvering object, interacting multiple model (IMM) is utilized. Multiple Models with different process noise levels are used distinguish effects. IMM cubature (IMM-CKF) which considers geometric relations between based optical (SBO) sensor, sun. relation highly affects...

This paper presents a satellite communications (SATCOM) situational awareness and decision-making methodology that incorporates uncertainty with probabilistic reasoning representation of the SATCOM network operating environment. The decision model is developed using Functional Causal Modeling (FCM) multiattribute utility theory. FCM Bayesian Network from mathematical functions represent underlying phenomena system, environment, operational dynamics. provides formal system for representing...

Imaging studies are one of the leading drivers modern medical decision making, and thus, their accessibility to healthcare providers patients is critical importance. However, current techniques for storage transferring imaging data inconvenient sometimes wholly inadequate. In this paper, we propose a decentralized autonomous image processing approach using blockchain technology. Blockchain will enable sharing key relevant distributed, decentralized, shared ledger that available participants....

In modern security situations, tracking multiple human objects in real-time within challenging urban environments is a critical capability for enhancing situational awareness, minimizing response time, and increasing overall operational effectiveness. Tracking entities enables informed decision-making, risk mitigation, the safeguarding of civil-military operations to ensure safety mission success. This paper presents multi-modal electro-optical/infrared (EO/IR) radio frequency (RF) fused...

The proliferation of unmanned aerial vehicle (UAV) networks is increasing, driven by their capacity to deliver automated services tailored the varied demands numerous smart city applications. Trust, security, and privacy remain paramount in public domain. Traditional centralized network designs fall short ensuring device authentication, data integrity, within highly dynamic adaptable environments UAV networks. Decentralized reputation systems have emerged as a promising solution for...

Cooperative communication mechanisms have been proposed as an effective way of exploiting the spatial diversity to improve quality wireless transmissions. To best our knowledge, a number research efforts paid study how employ network layer routing design, realizing minimum energy expenditure in data transmission. However, there is lack systematic strategy for evaluating existing schemes. address this issue, we first develop taxonomy summarize energy-efficient cooperative algorithms and...

Rapid advancements in the fifth generation (5G) communication technology and mobile edge computing (MEC) paradigm lead to proliferation of unmanned aerial vehicles (UAV) urban air mobility (UAM) networks, which provide intelligent services for diversified smart city scenarios. Meanwhile, widely deployed internet drones (IoD) cities also brings up new concerns on performance, security, privacy. The centralized framework adopted by conventional UAM networks is not adequate handle high...

The rapid development of three-dimensional (3D) acquisition technology based on 3D sensors provides a large volume data, which is often represented in the form point clouds. Point cloud representation can preserve original geometric information along with associated attributes space. Therefore, it has been widely adopted many scene-understanding-related applications such as virtual reality (VR) and autonomous driving. However, massive amount data aggregated from distributed also poses...

This paper discusses using ground-based imagery to determine the attitude of a flying projectile assuming prior knowledge its external geometry. It presents segmentation-based approach follow object and evaluates it quantitatively with simulated data qualitatively both real data. Two experimental cases are considered: One assumes reliable target distance measurement from an auxiliary range sensor, while other no information. The results show that in case unknown projectile–camera distance,...

In this study, we introduce an innovative Robot State Estimation (RSE) methodology incorporating a learning-based contact estimation framework for legged robots, which obviates the need external physical sensors. This approach integrates multimodal proprioceptive sensory data, employing Physics-Informed Neural Network (PINN) in conjunction with Unscented Kalman Filter (UKF) to enhance state process. The primary objective of RSE technique is calibrate Inertial Measurement Unit (IMU)...

Cooperative Augmented Reality (AR) can provide real-time, immersive, and context-aware situational awareness while enhancing mobile sensing capabilities benefiting various applications. Distributed edge computing has emerged as an essential paradigm to facilitate cooperative AR. We designed implemented a distributed system enable fast, reliable, scalable In this paper, we present novel approach architecture that integrates advanced sensing, communications, processing techniques create such...

Inertial Navigation Systems (INS) stand as a foundational technology in navigation, finding diverse applications across aerospace engineering, marine exploration, and terrestrial vehicles. Traditional Newtonian-based inertial navigation methods are susceptible to errors, they involve double integration of IMU measurements. In recent years, data-driven methodologies like IONet IDOL have demonstrated their efficacy harnessing well-trained neural networks achieve precise based on However, many...

In modern security situations, tracking multiple human objects in real-time within challenging urban environments is a critical capability for enhancing situational awareness, minimizing response time, and increasing overall operational effectiveness. Tracking entities enables informed decision-making, risk mitigation, the safeguarding of civil-military operations to ensure safety mission success. This paper presents multi-modal electro-optical/infrared (EO/IR) radio frequency (RF) fused...

The rapid development of three-dimensional (3D) acquisition technology based on 3D sensors provides a large volume data, which are often represented in the form point clouds. Point cloud representation can preserve original geometric information along with associated attributes space. Therefore, it has been widely adopted many scene-understanding-related applications such as virtual reality (VR) and autonomous driving. However, massive amount data aggregated from distributed also poses...