Requirements and Limitations of Thermal Drones for Effective Search and Rescue in Marine and Coastal Areas

Burke, Claire; McWhirter, Paul R.; Veitch-Michaelis, Joshua; McAree, Owen; Pointon, Harry A. G.; Wich, Serge A.; Longmore, S.

doi:10.3390/drones3040078

Cited by 41 publications

(33 citation statements)

References 27 publications

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“…This allows a LWIR thermal imaging camera to detect human activity day and night. The multirotor equipped with a thermal imaging camera can be used for search and rescue missions in hazardous areas as well as security and surveillance [6,7]. It is also useful for many applications such as wildlife monitoring, agricultural and industrial inspection [8,9].…”

Section: Introductionmentioning

confidence: 99%

Moving People Tracking and False Track Removing with Infrared Thermal Imaging by a Multirotor

Yeom

2021

Drones

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Infrared (IR) thermal imaging can detect the warm temperature of the human body regardless of the light conditions, thus small drones equipped with the IR thermal camera can be utilized to recognize human activity for smart surveillance, road safety, and search and rescue missions. However, the unpredictable motion of the drone poses more challenges than a fixed camera. This paper addresses the detection and tracking of people through IR thermal video captured by a multirotor. For object detection, each frame is first registered with a reference frame to compensate for its coordinates. Then, the objects in each frame are segmented through k-means clustering and morphological operations. Falsely detected objects are removed considering the actual size and the shape of the object. The centroid of the segmented area is considered the measured position for target tracking. The track is initialized with two-point differencing initialization, and the target states are continuously estimated by the interacting multiple model (IMM) filter. The nearest neighbor association rule assigns the measurement to the track. Tracks that move slower than the minimum speed are terminated at the proposed criteria. In the experiments, three videos were captured with a long-wave IR band thermal imaging camera mounted on a multirotor. In the first and second videos, eight pedestrians on a pavement and three hikers on a mountain on winter nights were captured, respectively. In the third video, two walking people with complex backgrounds were captured on a windy summer day. The image characteristics vary between videos depending on the climate and surrounding objects, but the proposed scheme shows the robust performance in all cases; the average root mean squared errors in position and velocity are obtained as 0.08 m and 0.53 m/s, respectively for the first video, 0.06 m and 0.58 m/s, respectively for the second video, and 0.18 m and 1.84 m/s, respectively for the third video. The proposed method reduces false tracks from 10 to 1 in the third video.

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Section: Introductionmentioning

confidence: 99%

Moving People Tracking and False Track Removing with Infrared Thermal Imaging by a Multirotor

Yeom

2021

Drones

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“…For cheaper versions, they can measure relative temperature differences, but more advanced radiometric sensors can measure absolute temperatures. Their uses range from infrastructure inspections to fire fighting and search and rescue activities (Burke et al 2019 ).…”

Section: Uav and Related Technologymentioning

confidence: 99%

“…UAVs can be very effective tools in supporting search and rescue activities (Jiménez López and Mulero-Pázmány 2019 ; Rajabifard 2019 ; Burke et al 2019 ). UAV platforms equipped with visible or thermal sensors can be used to search large, potentially difficult-to-access or inaccessible areas and detect people in distress on the ground or at sea.…”

Section: Applications Of Uav Technology To Support Sustainable Development and Iczmmentioning

confidence: 99%

Applications of Uncrewed Aerial Vehicles (UAV) Technology to Support Integrated Coastal Zone Management and the UN Sustainable Development Goals at the Coast

Kandrot¹,

Hayes

Holloway

2021

Estuaries and Coasts

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Data and information obtained from low-cost uncrewed aerial vehicles (UAVs), commonly referred to as ‘drones’, can be used to support integrated coastal zone management (ICZM) and sustainable development at the coast. Several recent studies in various disciplines, including ecology, engineering, and several branches of physical and human geography, describe the applications of UAV technology with practical coastal management potential, yet the extent to which such data can contribute to these activities remains underexplored. The main objective of this paper is to collate this knowledge to highlight the areas in which UAV technology can contribute to ICZM and can influence the achievement of the UN Sustainable Development Goals (SDGs) at the coast. We focus on applications with practical potential for coastal management activities and assess their accessibility in terms of cost, ease of use, and maturity. We identified ten (out of the 17) SDGs to which UAVs can contribute data and information. Examples of applications include surveillance of illegal fishing and aquaculture activities, seaweed resource assessments, cost-estimation of post-storm damages, and documentation of natural and cultural heritage sites under threat from, for example, erosion and sea-level rise. An awareness of how UAVs can contribute to ICZM, as well as the limitations of the technology, can help coastal practitioners to evaluate their options for future management activities.

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“…Additionally, objects of interest vary in position, orientation, viewpoint, cloth color, scale, etc., and can be camouflaged within the environment causing the lack of details that distinguish the object from the background. That is why many published papers related to drone usage in SAR operations rely on the addition of Thermal Infrared (TIR) cameras, which allow warm bodies to be seen distinctly from their surroundings [23,24]. However, in the area where we performed our research, using thermal cameras for person detection is often not appropriate since in summer months, the ground temperature may be even higher than the human body temperature.…”

Section: Search and Rescue Operationsmentioning

confidence: 99%

Multimodel Deep Learning for Person Detection in Aerial Images

Vasić

Papić

2020

Electronics

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In this paper, we propose a novel method for person detection in aerial images of nonurban terrain gathered by an Unmanned Aerial Vehicle (UAV), which plays an important role in Search And Rescue (SAR) missions. The UAV in SAR operations contributes significantly due to the ability to survey a larger geographical area from an aerial viewpoint. Because of the high altitude of recording, the object of interest (person) covers a small part of an image (around 0.1%), which makes this task quite challenging. To address this problem, a multimodel deep learning approach is proposed. The solution consists of two different convolutional neural networks in region proposal, as well as in the classification stage. Additionally, contextual information is used in the classification stage in order to improve the detection results. Experimental results tested on the HERIDAL dataset achieved precision of 68.89% and a recall of 94.65%, which is better than current state-of-the-art methods used for person detection in similar scenarios. Consequently, it may be concluded that this approach is suitable for usage as an auxiliary method in real SAR operations.

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Requirements and Limitations of Thermal Drones for Effective Search and Rescue in Marine and Coastal Areas

Cited by 41 publications

References 27 publications

Moving People Tracking and False Track Removing with Infrared Thermal Imaging by a Multirotor

Moving People Tracking and False Track Removing with Infrared Thermal Imaging by a Multirotor

Applications of Uncrewed Aerial Vehicles (UAV) Technology to Support Integrated Coastal Zone Management and the UN Sustainable Development Goals at the Coast

Multimodel Deep Learning for Person Detection in Aerial Images

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