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Deep learning-based algorithms can provide state-of-the-art accuracy for remote sensing technologies such as unmanned aerial vehicles (UAVs)/drones, potentially enhancing their remote sensing capabilities for many emergency response and…

计算机视觉与模式识别 · 计算机科学 2021-04-30 Christos Kyrkou , Theocharis Theocharides

Uncrewed Aerial Vehicle (UAV) computing and networking are becoming a fundamental computation infrastructure for diverse cyber-physical application systems. UAVs can be empowered by AI on edge devices and can communicate with other UAVs and…

Earthquakes, fire, and floods often cause structural collapses of buildings. The inspection of damaged buildings poses a high risk for emergency forces or is even impossible, though. We present three recent selected missions of the Robotics…

In the aftermath of an earthquake, rapid structural inspections are required to get citizens back in to their homes and offices in a safe and timely manner. These inspections gfare typically conducted by municipal authorities through…

计算机视觉与模式识别 · 计算机科学 2018-09-26 Vedhus Hoskere , Yasutaka Narazaki , Tu A. Hoang , Billie F. Spencer

Emergency evacuation describes a complex situation involving time-critical decision-making by evacuees. Mobile robots are being actively explored as a potential solution to provide timely guidance. In this work, we study a robot-guided…

机器人学 · 计算机科学 2024-01-15 Tongjia Zheng , Zhenyuan Yuan , Mollik Nayyar , Alan R. Wagner , Minghui Zhu , Hai Lin

Vehicular ad hoc networks (VANETs) are characterized by frequent routing path failures due to the high mobility caused by the sudden changes of the direction of vehicles. The routing paths between two different vehicles should be…

网络与互联网体系结构 · 计算机科学 2019-08-19 Omar Sami Oubbati , Noureddine Chaib , Abderrahmane Lakas , Salim Bitam

Unmanned Aerial Vehicles (UAVs) have enormous potential in the public and civil domains. These are particularly useful in applications where human lives would otherwise be endangered. Multi-UAV systems can collaboratively complete missions…

网络与互联网体系结构 · 计算机科学 2016-03-29 Lav Gupta , Raj Jain , Gabor Vaszkun

The challenge of wildfire management and detection is recently gaining increased attention due to the increased severity and frequency of wildfires worldwide. Popular fire detection techniques such as satellite imaging and remote…

网络与互联网体系结构 · 计算机科学 2020-07-29 Osama M. Bushnaq , Anas Chaaban , Tareq Y. Al-Naffouri

Identification of regions affected by floods is a crucial piece of information required for better planning and management of post-disaster relief and rescue efforts. Traditionally, remote sensing images are analysed to identify the extent…

计算机视觉与模式识别 · 计算机科学 2022-10-05 Sushant Lenka , Pratyush Kerhalkar , Pranav Shetty , Harsh Gupta , Bhavam Vidyarthi , Ujjwal Verma

Recent advancements in computer vision and deep learning techniques have facilitated notable progress in scene understanding, thereby assisting rescue teams in achieving precise damage assessment. In this paper, we present RescueNet, a…

计算机视觉与模式识别 · 计算机科学 2024-05-20 Maryam Rahnemoonfar , Tashnim Chowdhury , Robin Murphy

We present longitudinal analysis of the evolution of inter-organizational disaster coordination networks during natural disasters. We suggest that social networks are a useful paradigm for exploring this complex phenomenon from both…

社会与信息网络 · 计算机科学 2015-03-31 Alireza Abbasi , Liaquat Hossain , Naim Kapucu

Earthquakes and tropical cyclones cause the suffering of millions of people around the world every year. The resulting landslides exacerbate the effects of these disasters. Landslide detection is, therefore, a critical task for the…

计算机视觉与模式识别 · 计算机科学 2019-10-17 Masanari Kimura

In emergency situations, actions that save lives and limit the impact of hazards are crucial. In order to act, situational awareness is needed to decide what to do. Geolocalized photos and video of the situations as they evolve can be…

计算机视觉与模式识别 · 计算机科学 2018-03-12 Laura Lopez-Fuentes , Joost van de Weijer , Manuel Gonzalez-Hidalgo , Harald Skinnemoen , Andrew D. Bagdanov

In the 21st century, the industry of drones, also known as Unmanned Aerial Vehicles (UAVs), has witnessed a rapid increase with its large number of airspace users. The tremendous benefits of this technology in civilian applications such as…

Unmanned Aerial Vehicles (UAVs), commonly known as Drones, are one of 21st century most transformative technologies. Emerging first for military use, advancements in materials, electronics, and software have catapulted drones into…

机器人学 · 计算机科学 2025-01-20 Ruchita Singh , Sandeep Kumar

In the event of natural or man-made disasters in an urban environment, such as fires, floods, and earthquakes, a swarm of unmanned aerial vehicles (UAVs) can rapidly sweep and provide coverage to monitor the area of interest and locate…

机器人学 · 计算机科学 2024-06-17 Wai Lun Leong , Jiawei Cao , Rodney Teo

Unmanned Aerial Vehicles (UAVs), as a recently emerging technology, enabled a new breed of unprecedented applications in different domains. This technology's ongoing trend is departing from large remotely-controlled drones to networks of…

网络与互联网体系结构 · 计算机科学 2021-11-09 Arnau Rovira-Sugranes , Abolfazl Razi , Fatemeh Afghah , Jacob Chakareski

Unmanned aerial vehicles, commonly known as drones, have emerged as a disruptive technology with the potential to revolutionize operations across various industries. Drones are the fast-growing internet-of-things technology and are…

最优化与控制 · 数学 2023-12-22 Ali Kaan Kurbanzade , Ansaar M. Baig , Sanjay Mehrotra

Unmanned Aerial Vehicles (UAVs) are emerging as very important tools in search and rescue (SAR) missions at sea, enabling swift and efficient deployment for locating individuals or vessels in distress. The successful execution of these…

机器人学 · 计算机科学 2024-10-10 Martin Messmer , Andreas Zell

In all types of disasters, from earthquakes to armed conflicts, aid workers need accurate and timely data such as damage to buildings and population displacement to mount an effective response. Remote sensing provides this data at an…

计算机视觉与模式识别 · 计算机科学 2019-10-16 Joseph Z. Xu , Wenhan Lu , Zebo Li , Pranav Khaitan , Valeriya Zaytseva