Recent advances in blockchain technology: prospects, applications and constraints in the minerals industry

International Journal of Mining Reclamation and Environment, Journal Year: 2024, Volume and Issue: 38(7), P. 497 - 533

Published: Feb. 26, 2024

One of the most important sectors world economy is mining and metals sector. Although, many operational commercial procedures continue to be ineffective out-of-date, which results in crucial data omissions, security flaws, sometimes corruption. Given that industry wants increase emphasis on ethical open practices, has been looking for ways incorporate these practices. It envisioned such practices will contribute modernisation supply chains addition helping reduce risks related sustainability reputation. The application blockchain technology minerals capable tracking natural resources discussed this study, giving a much-needed layer transparency technology. However, there are lot difficulties problems come up when thinking about technology; if it advance as an standard, stakeholders need evaluate usefulness scalability While can applied wide range areas industry, study shines more light conflict tracking, mineral reporting cheating scandals, rock mechanics designs monitoring strategy, blasting operation, mine ventilation applications, machinery maintenance management, surveying. reveals starting seriously evaluated used by variety stakeholders, even though broad acceptance not yet attained.

Language: Английский

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Comparative Analysis of Different UAV Swarm Control Methods on Unmanned Farms

Agronomy, Journal Year: 2023, Volume and Issue: 13(10), P. 2499 - 2499

Published: Sept. 28, 2023

Unmanned farms employ a variety of sensors, automated systems, and data analysis techniques to enable fully intelligent management. This not only heightens agricultural production efficiency but also reduces the costs associated with human resources. As integral components unmanned farms’ automation UAVs have been widely adopted across various operational stages due their precision, high efficiency, environmental sustainability, simplicity operation. However, present-day technological advancement levels relevant policy regulations pose significant restrictions on in terms payload endurance, leading diminished task when single UAV is deployed over large areas. Accordingly, this paper aggregates analyzes research pertaining swarms from databases such as Google Scholar, ScienceDirect, Scopus, IEEE Xplorer, Wiley past decade. An initial overview presents current control methods for swarms, incorporating summary features, merits, drawbacks diverse techniques. Subsequently, drawing four main (cultivation, planting, management, harvesting), we evaluate application each stage provide an most advanced swarm technologies utilized therein. Finally, scrutinize analyze challenges concerns applications forward-looking insights into future developmental trajectory technology farming, objective bolstering performance, scalability, adoption rates settings.

Language: Английский

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Comprehensive Investigation of Unmanned Aerial Vehicles (UAVs): An In-Depth Analysis of Avionics Systems

Sensors, Journal Year: 2024, Volume and Issue: 24(10), P. 3064 - 3064

Published: May 11, 2024

The evolving technologies regarding Unmanned Aerial Vehicles (UAVs) have led to their extended applicability in diverse domains, including surveillance, commerce, military, and smart electric grid monitoring. Modern UAV avionics enable precise aircraft operations through autonomous navigation, obstacle identification, collision prevention. structures of are generally complex, thorough hierarchies intricate connections exist between. For a comprehensive understanding design, this paper aims assess critically review the purpose-classified electronics hardware inside UAVs, each with corresponding performance metrics thoroughly analyzed. This includes an exploration different algorithms used for data processing, flight control, protection, communication. Consequently, enriches knowledge base offering informative background on various design processes, particularly those related applications. As future work recommendation, actual relevant project is openly discussed.

Language: Английский

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A Review on Deep Learning for UAV Absolute Visual Localization

Drones, Journal Year: 2024, Volume and Issue: 8(11), P. 622 - 622

Published: Oct. 29, 2024

In the past few years, use of Unmanned Aerial Vehicles (UAVs) has expanded and now reached mainstream levels for applications such as infrastructure inspection, agriculture, transport, security, entertainment, real estate, environmental conservation, search rescue, even insurance. This surge in adoption can be attributed to UAV ecosystem’s maturation, which not only made these devices more accessible cost effective but also significantly enhanced their operational capabilities terms flight duration embedded computing power. conjunction with developments, research on Absolute Visual Localization (AVL) seen a resurgence driven by introduction deep learning field. These new approaches have improved localization solutions comparison previous generation based traditional computer vision feature extractors. paper conducts an extensive review literature learning-based methods AVL, covering significant advancements since 2019. It retraces key developments that led rise provides in-depth analysis related sources Inertial Measurement Units (IMUs) Global Navigation Satellite Systems (GNSSs), highlighting limitations advantages integration AVL. The concludes current challenges proposes future directions guide further work

Language: Английский

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Accelerometer Bias Estimation for Unmanned Aerial Vehicles Using Extended Kalman Filter-Based Vision-Aided Navigation

Electronics, Journal Year: 2025, Volume and Issue: 14(6), P. 1074 - 1074

Published: March 7, 2025

Accurate estimation of accelerometer biases in Inertial Measurement Units (IMUs) is crucial for reliable Unmanned Aerial Vehicle (UAV) navigation, particularly GPS-denied environments. Uncompensated lead to an unbounded accumulation position error and increased velocity error, resulting significant navigation inaccuracies. This paper examines the effects bias on UAV accuracy introduces a vision-aided system. The proposed system integrates data from IMU, altimeter, optical flow sensor (OFS), employing Extended Kalman Filter (EKF) estimate both velocity. approach reduces positional errors. efficiency this was validated through simulation experiments involving navigating circular straight-line trajectories. Simulation results show that significantly enhances performance, providing more accurate estimates state while reducing growth use vision aiding Optical Flow Sensor.

Language: Английский

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Explainable AI and monocular vision for enhanced UAV navigation in smart cities: prospects and challenges

Frontiers in Sustainable Cities, Journal Year: 2025, Volume and Issue: 7

Published: March 14, 2025

Explainable Artificial Intelligence (XAI) is increasingly pivotal in Unmanned Aerial Vehicle (UAV) operations within smart cities, enhancing trust and transparency AI-driven systems by addressing the 'black-box' limitations of traditional Machine Learning (ML) models. This paper provides a comprehensive overview evolution UAV navigation control systems, tracing transition from conventional methods such as GPS inertial to advanced AI- ML-driven approaches. It investigates transformative role XAI particularly safety-critical applications where interpretability essential. A key focus this study integration into monocular vision-based frameworks, which, despite their cost-effectiveness lightweight design, face challenges depth perception ambiguities limited fields view. Embedding techniques enhances reliability these providing clearer insights paths, obstacle detection, avoidance strategies. advancement crucial for adaptability dynamic urban environments, including infrastructure changes, traffic congestion, environmental monitoring. Furthermore, work examines how frameworks foster decision-making high-stakes planning disaster response. explores critical challenges, scalability, evolving conditions, balancing explainability with performance, ensuring robustness adverse environments. Additionally, it highlights emerging potential integrating vision models Large Language Models (LLMs) further enhance situational awareness autonomous decision-making. Accordingly, actionable advance next-generation technologies, transparency. The findings underscore XAI's bridging existing research gaps accelerating deployment intelligent, explainable future cities.

Language: Английский

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Gnss-denied unmanned aerial vehicle navigation: analyzing computational complexity, sensor fusion, and localization methodologies

Satellite Navigation, Journal Year: 2025, Volume and Issue: 6(1)

Published: April 6, 2025

Abstract Navigation without Global Satellite Systems (GNSS) poses a significant challenge in aerospace engineering, particularly the environments where satellite signals are obstructed or unavailable. This paper offers an in-depth review of various methods, sensors, and algorithms for Unmanned Aerial Vehicle (UAV) localization outdoor GNSS unavailable denied. A key contribution this study is establishment critical classification system that divides GNSS-denied navigation techniques into two primary categories: absolute relative localization. enhances understanding strengths weaknesses different strategies operational contexts. Vision-based identified as most effective approach environments. Nonetheless, it’s clear no single-sensor-based algorithm can fulfill all needs comprehensive Therefore, vital to implement hybrid strategy merges sensors outcomes. detailed analysis emphasizes challenges possible solutions achieving reliable UAV unreliable multi-faceted analysis, highlights complexities potential pathways efficient dependable

Language: Английский

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CoEF: Vehicular cooperative perception based on entropy theory and feature re-projection

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127371 - 127371

Published: April 1, 2025

Language: Английский

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Enhancing Multi-Flight Unmanned-Aerial-Vehicle-Based Detection of Wheat Canopy Chlorophyll Content Using Relative Radiometric Correction

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(9), P. 1557 - 1557

Published: April 27, 2025

Unmanned aerial vehicle (UAV) remote sensing has emerged as a powerful tool for precision agriculture, offering high-resolution crop monitoring capabilities. However, multi-flight UAV missions introduce radiometric inconsistencies that hinder the accuracy of vegetation indices and physiological trait estimation. This study investigates efficacy relative correction in enhancing canopy chlorophyll content (CCC) estimation winter wheat. Dual sensor configurations captured imagery across three experimental sites key wheat phenological stages (the green-up, heading, grain filling stages). Sentinel-2 data served an external reference. The results indicate significantly improved spectral consistency, reducing RMSE values (in bands by >86% 38–96%) correlations with reflectance. predictive CCC models after correction, validation errors decreasing 17.1–45.6% different growth full-season integration yielding 44.3% reduction. These findings confirm critical role optimizing UAV-based estimation, reinforcing its applicability dynamic agricultural monitoring.

Language: Английский

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Multi-modular UAV for Mars exploration: A concept feasibility study

Chinese Journal of Aeronautics, Journal Year: 2025, Volume and Issue: unknown, P. 103562 - 103562

Published: April 1, 2025

Language: Английский

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