Applications, challenges, and solutions of unmanned aerial vehicles in smart city using blockchain

PeerJ Computer Science, Journal Year: 2024, Volume and Issue: 10, P. e1776 - e1776

Published: Feb. 8, 2024

Real-time data gathering, analysis, and reaction are made possible by this information communication technology system. Data storage is also it. This a good move since it enhances the administration operation services essential to any city’s efficient operation. The idea behind “smart cities” that (ICTs) need be included in routine activities order gather, analyze, store enormous amounts of real-time. helpful makes managing governing urban areas easier. “drone” or “uncrewed aerial vehicle” (UAV), which can carry out ordinarily call for human driver, serves as an example this. UAVs could used integrate geospatial data, manage traffic, keep eye on objects, help emergency part smart fabric. study looks at benefits drawbacks deploying conception, development, management cities. article describes importance advantages designing, developing, maintaining overviews UAV uses types, applications, challenges. Furthermore, we presented blockchain approaches addressing given problems research topics recommendations improving security privacy Blockchain Researcher graduate students audience our article.

Language: Английский

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Advanced Air Mobility Operation and Infrastructure for Sustainable Connected eVTOL Vehicle

Drones, Journal Year: 2023, Volume and Issue: 7(5), P. 319 - 319

Published: May 16, 2023

Advanced air mobility (AAM) is an emerging sector in aviation aiming to offer secure, efficient, and eco-friendly transportation utilizing electric vertical takeoff landing (eVTOL) aircraft. These vehicles are designed for short-haul flights, transporting passengers cargo between urban centers, suburbs, remote areas. As the number of flights expected rise significantly congested metropolitan areas, there a need digital ecosystem support AAM platform. This requires seamless integration traffic management systems, ground control communication networks, enabling effective systems ensure safe efficient operations. Consequently, industry seeking develop new aerospace framework that promotes shared practices, ensuring safety, sustainability, efficiency However, lack adequate wireless coverage cities disconnected rural communities poses challenges large-scale deployments. In immediate recovery phase, incorporating with air-to-ground connectivity presents difficulties such as overwhelming terrestrial network data requests, maintaining link reliability, managing handover occurrences. Furthermore, eVTOL areas airspace necessitates high levels routing information vehicles. paper introduces novel concept addressing future flight proposes integrating operations, infrastructure, connectivity, ecosystems mobility. Specifically, it includes performance analysis illustrate impact extensive vehicle on base station infrastructure environments. work aims pave way by introducing vision backbone supports sustainable through advanced technology.

Language: Английский

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Real-Time Fire Detection: Integrating Lightweight Deep Learning Models on Drones with Edge Computing

Drones, Journal Year: 2024, Volume and Issue: 8(9), P. 483 - 483

Published: Sept. 13, 2024

Fire accidents are life-threatening catastrophes leading to losses of life, financial damage, climate change, and ecological destruction. Promptly efficiently detecting extinguishing fires is essential reduce the loss lives damage. This study uses drone, edge computing, artificial intelligence (AI) techniques, presenting novel methods for real-time fire detection. proposed work utilizes a comprehensive dataset 7187 images advanced deep learning models, e.g., Detection Transformer (DETR), Detectron2, You Only Look Once YOLOv8, Autodistill-based knowledge distillation techniques improve model performance. The approach has been implemented with YOLOv8m (medium) as teacher (base) model. distilled (student) frameworks developed employing YOLOv8n (Nano) DETR techniques. attains best performance 95.21% detection accuracy 0.985 F1 score. A powerful hardware setup, including Raspberry Pi 5 microcontroller, camera module 3, DJI F450 custom-built constructed. deployed in setup identification. achieves 89.23% an approximate frame rate 8 conducted live experiments. Integrating drone devices demonstrates system’s effectiveness potential practical applications hazard mitigation.

Language: Английский

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A Multi-Drone System Proof of Concept for Forestry Applications

Drones, Journal Year: 2025, Volume and Issue: 9(2), P. 80 - 80

Published: Jan. 21, 2025

This study presents a multi-drone proof of concept for efficient forest mapping and autonomous operation, framed within the context OPENSWARM EU Project. The approach leverages state-of-the-art open-source simultaneous localisation (SLAM) frameworks, like LiDAR (Light Detection And Ranging) Inertial Odometry via Smoothing Mapping (LIO-SAM), Distributed Collaborative SLAM Framework Robotic Swarm (DCL-SLAM), seamlessly integrated MRS UAV System Formation packages. integration is achieved through series procedures compliant with Robot Operating middleware (ROS), including an auto-tuning particle swarm optimisation method enhanced flight control stabilisation, which crucial operation in challenging environments. Field experiments conducted multiple drones demonstrate system’s ability to navigate complex terrains as coordinated swarm, accurately collaboratively areas. Results highlight potential this concept, contributing development scalable solutions forestry management. findings emphasise significance integrating technologies advance sustainable practices using swarms drones.

Language: Английский

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UAV-based studies in railway infrastructure monitoring

Automation in Construction, Journal Year: 2024, Volume and Issue: 167, P. 105714 - 105714

Published: Aug. 20, 2024

Language: Английский

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Fire Detection and Geo-Localization Using UAV’s Aerial Images and Yolo-Based Models

Applied Sciences, Journal Year: 2023, Volume and Issue: 13(20), P. 11548 - 11548

Published: Oct. 21, 2023

The past decade has witnessed a growing demand for drone-based fire detection systems, driven by escalating concerns about wildfires exacerbated climate change, as corroborated environmental studies. However, deploying existing systems in real-world operational conditions poses practical challenges, notably the intricate and unstructured environments dynamic nature of UAV-mounted cameras, often leading to false alarms inaccurate detections. In this paper, we describe two-stage framework geo-localization. key features proposed work included compilation large dataset from several sources capture various visual contexts related scenes. bounding boxes regions interest were labeled using three target levels, namely fire, non-fire, smoke. second feature was investigation YOLO models undertake localization tasks. YOLO-NAS retained best performing model compiled with an average mAP50 0.71 F1_score 0.68. Additionally, scheme based on stereo vision introduced, hardware implementation executed drone equipped Pixhawk microcontroller. test results very promising showed ability approach contribute comprehensive effective system.

Language: Английский

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Artificial Intelligence-Based Control Strategies for Unmanned Aerial Vehicles

2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Journal Year: 2023, Volume and Issue: unknown

Published: Dec. 1, 2023

Drones, also known as Unmanned Aerial Vehicles, or UAVs, are becoming more and well-liked a multifunctional tool that can be used in variety of industries, including environmental monitoring, search rescue, agricultural, surveillance. In this work, we explore the potential for significantly increased UAV efficiency, versatility, durability with AI-based control techniques. The research technique combines simulation, experimental validation, mathematical modelling to fully investigate systems. We develop model dynamics use deep reinforcement learning (DRL) based on Proximal Policy Optimisation (PPO) drones. Both theoretical analysis real-world testing DJI Matrice 210 RTK platform validate method's efficacy. algorithm's capacity provide precise accurate answers is shown by average location error's steady decline over time. It very resilient, remaining stable face wind gusts, remarkably flexible, quick response times. These patterns graphically. According study's findings, algorithms might greatly advance technology increasing its precision, adaptability, dependability. Future priorities will include advanced machine techniques, multi-agent systems, safety measures, ethical frameworks, human-AI collaboration, impact assessments, urban integration. Through creation new capabilities resolution urgent concerns, these activities have significant development future.

Language: Английский

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A Cyber-Physical System for Wildfire Detection and Firefighting

Future Internet, Journal Year: 2023, Volume and Issue: 15(7), P. 237 - 237

Published: July 6, 2023

The increasing frequency and severity of forest fires necessitate early detection rapid response to mitigate their impact. This project aims design a cyber-physical system for using advanced technologies. incorporates Internet Things sensors autonomous unmanned aerial ground vehicles controlled by the robot operating system. An IoT-based wildfire node continuously monitors environmental conditions, enabling fire detection. Upon detection, UAV autonomously surveys area precisely locate can deploy an extinguishing payload or provide data decision-making. communicates fire’s precise location collaborative UGV, which reaches designated support ground-based firefighters. CPS includes control station with web-based dashboards real-time monitoring parameters telemetry from UAVs UGVs. article demonstrates capabilities proposed simulated scenarios. objective is practical approach open-source technologies fires, potential applications in various industries, surveillance, precision agriculture.

Language: Английский

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In-depth review of AI-enabled unmanned aerial vehicles: trends, vision, and challenges

Discover Artificial Intelligence, Journal Year: 2024, Volume and Issue: 4(1)

Published: Dec. 2, 2024

In recent times, AI and UAV have progressed significantly in several applications. This article analyzes applications of with modern green computing various sectors. It addresses cutting-edge technologies such as computing, generative AI, future scope, related concerns UAV. The research investigates the role combination UAVs for navigation, object recognition tracking, wildlife monitoring, precision agriculture, rescue operations, surveillance, communication. study examines how are being applied disaster management, other areas. ethics applications, including safety, legal frameworks, issues, thoroughly investigated. AI-based across different disciplines, using open-source data current advancements growth this domain. investigation will aid researchers their exploration technologies.

Language: Английский

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Machine learning approaches to intrusion detection in unmanned aerial vehicles (UAVs)

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(29), P. 18009 - 18041

Published: Aug. 23, 2024

Language: Английский

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