Article, Emergency Medicine

The potential use of unmanned aircraft systems (drones) in mountain search and rescue operations

a b s t r a c t

Objective: This study explores the potential use of drones in searching for and locating victims and of motorized transportation of Search and rescue providers in a mountain environment using a Simulation model.

Methods: This prospective randomized simulation study was performed in order to compare two different search and rescue techniques in searching for an unconscious victim on snow-covered ground. In the control arm, the Classical Line Search Technique (CLT) was used, in which the search is performed on foot and the victim is reached on foot. In the intervention arm, the Drone-snowmobile Technique (DST) was used, the search being performed by drone and the victim reached by snowmobile. The primary outcome of the study was the compar- ison of the two search and rescue techniques in terms of first human contact time.

Results: Twenty search and rescue operations were conducted in this study. Median time to arrival at the manne- quin was 57.3 min for CLT, compared to 8.9 min for DST. The median value of the total searched area was 88,322.0 m2 for CLT and 228,613.0 m2 for DST. The median area searched per minute was 1489.6 m2 for CLT and 32,979.9 m2 for DST (p b 0.01 for all comparisons).

Conclusions: In conclusion, a wider area can be searched faster by drone using DST compared to the classical tech- nique, and the victim can be located faster and reached earlier with rescuers transported by snowmobile.

(C) 2017

Introduction

Unmanned aerial aircraft, or drones, are small vehicles that are con- trolled by an operator on the ground without a pilot. Drones were ini- tially designed as simple devices, but are now becoming increasingly complex. After being primarily used for military purposes, drones have since become available for civilian use. Their scope of use has grown rapidly, and they have now begun being employed in industry, logistics, research, agriculture, photography and video filming, as a hobby and in medicine [1-4]. Using drones in medicine is a novel con- cept and one especially attractive for EMS and search & rescue providers.

Most mountain rescue victims are injured, ill or lost, and some will have been involved in avalanche accidents. Drones have the potential to shorten search times and accelerate subsequent intervention in all these groups. According to the Wilderness Medical Society Practice Guidelines for Prevention and Management of Avalanche and Non-ava- lanche Snow Burial Accidents, it is vitally important to reach the patient

? Presented at a meeting: No.

?? Grant: No.

* Corresponding author at: Karadeniz Technical University, Faculty of Medicine, Department of Emergency Medicine, 61080 Trabzon, Turkey.

E-mail address: [email protected] (S. Turedi).

within the first 60 min during mountain rescue operations [6]. The loca- tion of a casualty is a critical step in mountain rescue. Drones are now used in many different environments, and some research is now emerg- ing concerning their use in other pre-hospital care medical situations. There have also been case reports of drones used in search and rescue operations.

The aim of this study was to compare two search and rescue tech- niques in terms of first human contact time. The study explores the po- tential use of drones in seeking and locating victims, and the use of motorized transportation of search and rescue providers in a mountain environment using a simulation model.

Materials-methods

Design and setting

This prospective randomized simulation study was performed in order to compare two different techniques in searching for an uncon- scious victim in snow-covered ground at an altitude of 2150 m in the Zigana Mountain region in the province of Gumushane in the north of Turkey.

The task was to locate an unconscious victim on an exposed, snow- covered slope. Two stages were involved, locating the victim and then reaching the victim.

http://dx.doi.org/10.1016/j.ajem.2017.09.025

0735-6757/(C) 2017

The study compared two different strategies. In the control arm (Classical Line Search Technique CLT) the search was performed on foot and the victim was reached on foot. In the intervention arm (Drone-Snowmobile Technique – DST) the search was performed by drone and the victim was reached by snowmobile. A snowmobile di- rected toward the victim of an accident detected by a drone providing live video coverage was compared with the rescue of a victim using CLT. A scenario involving an unconscious victim in snow-covered ground was enacted 10 times for each group using a 180 cm shop window man- nequin to represent the accident victim. In order to ensure randomiza- tion, on each occasion the place where the mannequin was to be left was selected by lots from 10 previously determined points. On each oc- casion, the mannequin was randomly left on the peak known as Yagli Tepe on Mount Zigana by an official on a snowmobile. The official was blinded to the study arms. The slope was traversed 7-8 times from one end to the other in order to eliminate tracks in the snow that might provide a clue as to the direction taken. The sites where the man- nequins were dropped were recorded using the Google Maps (www. google.com.tr/maps) application by mobile phone. At the time of the search, the mannequin was wearing dark-colored trousers and a dark sweater. All scenarios were performed with the mannequin clothed in

the same way.

Each group carried out blinded searches for the same 10 sites. The starting point was determined as 40?38?35.87?N latitude and 39?24?

9.63?E longitude. The same mannequin was deposited to 10 separate lo- cations. These sites were at a minimum 473 m and a maximum 866 m (mean 654 m) from the search and rescue team starting point. The dis- tance between these 10 sites ranged from a minimum 53 m to a maxi- mum 492 m (mean 235 m).

Five individuals took part in the classic search group. All five rescuers were certified by the Turkish Ministry of Health. Three rescuers were in- volved in the drone group. Time to arrival at the mannequin from base- line expressed in minutes, total area scanned in that time frame and area scanned per minute expressed as square meters were calculated. Both searches were conducted in March 2017. The weather on the days of the study was slightly cloudy and clear, with a mean tempera- ture of 1-5 ?C and a wind speed of 20-25 km/h. The study took place on snow-covered ground in good visibility. The snow thickness ranged between 40 and 100 cm.

Classical line technique

In order to mimic the number of rescuers in a standard search and rescue team in Turkey, five certified rescuers took part in each search in this group. All were equipped and accoutered against hypothermia in mountainous conditions. The search was conducted with 10 m be- tween each rescuer (Fig. 1). A chronometer was started at the beginning of the search and stopped on arrival at the mannequin to calculate the total search time. The rescuer in the middle of the search team was given a mobile phone equipped with the RWG program, and the routes taken throughout the search were recorded with the help of that soft- ware. These routes were downloaded from the RWG website in .kml format and opened using GEP software. The total area scanned on each route was calculated in square meters with the help of the GEP software. The search speed was calculated as square meters/min the di- viding total area searched on foot by total time walked.

The drone-snowmobile technique

This search group consisted of three rescuers, an experienced drone pilot, a rescuer monitoring the drone screen and a certified snowmobile driver. Images at a quality of 1080p obtained from the DJI Phantom 3 Pro (Fig. 2) brand drone were transferred in real time to an Ipad tablet (Fig. 3). The images were also recorded by the drone onto a microSD card. The chronometer, drone engines and video recording were all started when the search began. Scanning by drone was started from a height of 40 m. When any image evaluated as possibly representing the mannequin was detected, the drone began descending in order to clarify the image. The snowmobile set off the moment that the drone definitively determined the mannequin’s location (Fig. 4). The drone pilot lowered the device to a distance of 10 m in order to indicate the lo- cation of the mannequin to the snowmobile rider. The chronometer was halted the moment the snowmobile reached the mannequin. The area scanned by the drone was calculated in the form of square meters by ex- amining the videos taken by the drone using Google Earth Pro. The total area calculated was divided by the time taken to express the area scanned expressed as square meters/min. The drone was programmed to return to the starting point when its battery level fell beneath 20% or if the signal was lost. The flights were carried out by a certified

Fig. 1. Five individuals in search with the classical line technique.

Fig. 2. Images at a quality of 1080p obtained from the DJI Phantom 3 Pro.

drone pilot with permission from the Ministry of Transport, Maritime Affairs and Communication.

Primary outcome

The study focuses on search area and time to location. The primary outcome was a comparison of two search and rescue techniques in terms of first human contact time.

Statistical analysis

Areas searched calculated using Google Earth Pro and times to reaching the mannequin were analyzed on SPSS 23.0 software. Varia- tion between the classic and drone search techniques in terms of time to reaching the mannequin and area searched per unit of time were compared using the Mann-Whitney U test. p values b 0.05 were regarded as statistically significant.

Results

Twenty search and rescue operations were conducted in this study. Median time to arrival at the mannequin was 57.3 min for CLT, com- pared to 8.9 min for DST. The median value of the total searched area was 88,322.0 m2 for CLT and 228,613.0 m2 for DST. The median area searched per minute was 1489.6 m2 for CLT and 32,979.9 m2 for DST (p b 0.01 for all comparisons). All search times and areas searched are shown in detail in Table 1.

Fig. 3. Drone’s control panel.

Discussion

The principal finding of this study is that locating and then reaching the victim were carried out much faster using DST compared to CLT.

Our study focuses on the potential value of drones in searching for and locating victims in a mountain environment. It was performed on snow-covered ground, and the victims were relatively visible. However, most mountain rescue victims are injured, ill or lost. Our scenario is more closely related to these more common non-avalanche subjects of mountain rescue. The use of drones may be preferable in this group in order to shorten the time to locate the victim and time to subsequent in- tervention. However, some mountain search and rescue operations in- volve avalanche victims. In addition, such victims may be visible on the surface or else buried. Buried victims would not be visible to a drone flying overhead. The rescue of buried victims involves multiple steps, including locating the victim below the surface and digging for extrication. This study does not explore the role of drones in such situations.

The task was to locate an unconscious victim on an open snow-cov- ered slope, with a simulated unconscious subject. In CLT, visual and au- ditory cues from the victim help guide the search group. However, unconscious injured victims cannot call for help and cannot respond to auditory signals. They cannot, therefore, guide the search team in a useful manner. This represents a significant disadvantage of the classic search method. In drone-assisted searches, however, visual cues from the injured victim are particularly important. Although drone-guided searches will be most effective with conscious victims, they may also be more useful than the classic search method when unconscious vic- tims are involved. Our model is therefore a logical one, and our results can be applied to real-world situations.

In one branch of our study (CLT), the search was performed by walk- ing in a linear pattern. When the victim was located, the search team reached the victim by walking to him, representing a search and rescue method commonly encountered in real life. In the other arm (DST), the injured victim was located by a drone, and the search and rescue team subsequently reached the victim by snowmobile. The primary end- point of our study, first human contact, was achieved faster using DST. Search and location being faster by drone together the search and res- cue team reaching the injured victim faster by snowmobile of course made a significant contribution to this more rapid achievement of the primary end-point. Since, as required by the study scenario, location of the injured party by the search and rescue team and first human con- tact occurred very close to one another or simultaneously, the rescuers were not transported by snowmobile. This difference in transport must be borne in mind in faster access to the victim using DST compared to the classic technique.

Classic line searching is a slow and highly resource-dependent method. It is usually used in a “fine search.” This may be because the ter- rain is very complex or due to a need for increased certainty that an area has been covered and thus eliminated during a search. This is not the most efficient method for urgently locating an unconscious victim on an open snow-covered slope. The total area covered and the speed achieved depends on the number of rescuers deployed in the line. In our study, only five individuals were used, in single line deployment and with 1-m spacing. The number of rescuers was kept limited in our study in order to mimic the number of members of a usual SAR team in Turkey, where the study was carried out. This may limit the chances of a rapid find and first human contact.

Examination of the literature indicates that the use of drones will be- come increasingly widespread in the medical sphere. Although this was not assessed directly in our study, Drone technology can make a positive contribution to several very different mountain rescue scenarios. The scenario in this study involved an unconscious patient. Two particularly important potential health problems in unconscious patents in moun- tainous terrain are hypothermia and cardiac arrest. We think that the use of drones can result in positive outcomes in terms of patient health

Fig. 4. When any image evaluated as possibly representing the mannequin was detected, the drone began descending in order to clarify the image.

in both conditions. The greatest potential benefit would be to quickly lo- cate those at risk form cold exposure and to prevent deterioration. Once cardiac arrest has occurred, even with the best treatment, the outcome will be very poor.

standard CPR techniques must be performed on victims in the first 60 min, and satisfactory results can be achieved in such cases. The 2015 Guidelines for Resuscitation published by the European Resuscita- tion Council state that CPR can be terminated or withheld in victims with asystole and arrest exceeding 60 min in duration together with air- way obstruction in cases of arrest following contact with snow [7]. The longest time to arrival at the mannequin in our study was 13.12 min. Of course, the period concerned might have been this short since ours was a simulation study, and may be longer in real-life scenarios. When the search periods were considered, locating the victim using a drone and reaching the victim by snowmobile was much faster compared to the classic search method. This shortened time to arrival at the victim is of vital significance considering that a faster arrival time will protect brain functions in the long term after arrest, particularly in hypothermic patients, and that prolonged CPR is indicated after arrest. A study by Claesson et al. involving a scenario of rescuing a drowning patient re- ported, similarly to our study, that the victim was reached very much faster in the drone group, and that a much larger surface area was searched by drone [8]. Searching a larger area in a shorter period of

time will increase the success enjoyed by rescuers, particularly in moun- tain rescue operations that require a large area to be searched in a short space of time. In a mapping study, again by Claesson et al., the authors reported that much earlier access to an automatic external defibrillator (AED) could be achieved in out-of-hospital cardiac arrests using drones [9]. There is thus a greater possibility of keeping the patient alive through earlier arrival using drone technology and consequently with early AED use.

Another potential benefit of drone use in SAR operations is that risks to the rescuers can also be reduced. Van Tilburg recently reported cases of drone searches being performed in areas potentially hazardous to rescuers, including a mountaineer who disappeared while engaged in canyoneering rappel and whose body was located by rescue teams with the help of a drone, and a patient who drove off into a canyon as the result of a road accident and who could not be located for 2 weeks [10]. In our study too, regions of difficult access for rescuers and with a risk of avalanche as well as deep valleys were safely searched by means of a drone. The victim was thus reached early and safely.

In addition, drone imaging can provide important information for rescuers about the route needing to be taken during search and rescue operations. Drone images during search operations will also protect res- cuers by identifying cliffs with a danger of avalanches or landslide. Amukele et al. showed that blood products can be transported by

Table 1

Characteristics of classic search versus drone search in the mountain rescue scenarios

Operation no

CLT

DCT

First human contact

Total searched area

Searched area for a minute

First human contact

Total searched area

Searched area for a minute

(min)

(m2)

(m2/min)

(min)

(m2)

(m2/min)

1

39.0

66,408

1702.8

7.7

168,395

28,065.8

2

53.1

78,209

1475.6

8.2

217,624

33,225.1

3

67.1

88,664

1323.3

8.5

239,602

35,080.8

4

95.0

120,891

1272.5

11.2

310,981

32,734.8

5

50.2

85,861

1717.2

5.6

192,224

49,162.1

6

95.2

104,479

1099.8

13.1

346,268

30,294.7

7

54.0

98,385

1821.9

7.4

144,480

25,302.9

8

61.1

77,378

1268.5

4.2

138,945

54,488.2

9

59.1

87,980

1503.7

9.7

266,722

33,340.3

10

56.1

99,375

1774.6

12.9

313,525

27,968.3

Median

57.3a

88,322.0b

1489.7c

8.4a

228,613.0b

32,979.9c

(25-75%)

(52.3-74.0)

(78,001.3-100,651.0)

(1271.5-1731.6)

(6.9-11.6)

(162,416.0-311,617.0)

(28,041.4-8601.1)

p b 0.001 for a, b, c.

drones. Although we encountered no studies on the subject, Amuke et al.’s study reveals the significant potential of drone use in mountain res- cue operations in terms of transporting food and drink, clothing and medical equipment.

Limitations

The wind speed during the study was approximately 15-25 km/h. No problems were encountered during drone flight at that speed, al- though drone flight quality might be impaired at higher wind speeds.

The temperature when the study was performed was 1-5 ?C, which is not a particularly cold environment for mountain search and rescue. The weather was relatively clear, and drone images were sharp under the study conditions, and no problems were encountered with these. However, it may be more difficult to control drones in heavy rain and snow. In addition, the prevailing temperature during the study would not be expected to compromise control of the drone controlling or me- chanical aspects such as battery life.

The study took place with snow cover on the ground. The weather was relatively clear, and visibility was good for aerial reconnaissance. The ability of the drone to search and locate may well have been very different in the event of actual snowfall or other factors such as foggy or rainy conditions. This limits the applicability of our findings to the cold and snowy conditions often experienced in real mountain rescue situations. In addition, avalanche victims are often buried. This study did not explore the role of drones under such circumstances.

This study compared a slow, standard search and rescue technique with a rapid, experimental one. The rescue teams only used motorized transport in one of the two study arms. Search and location being faster by drone together the search and rescue team reaching the injured vic- tim faster by snowmobile of course made a significant contribution to this faster time to first human contact. In the other branch, as required by the study scenario, since location of the injured party by the search and rescue team and first human contact occurred very close to one an- other or simultaneously, motorized transport was not used. However, the addition of motorized transport to the classic search and rescue technique can still shorten time to first human contact under conditions in which it is difficult or impossible to reach the victim on foot after vi- sual location.

The number of rescuers deployed in classic line searching is impor- tant. In our study, in order to replicate the numbers in a usual search and rescue team, only five people were used in single line deployment, with 10-m spacing. This may limit the probability of a rapid find and first human contact.

In our study, the same official deployed the mannequin in each test scenario. This person was blinded to the study arms. However, there is still a possibility of unpreventable operator-related bias. Similarly, the same search teams were used for each scenario, and some bias deriving from knowledge of previous locations will again be inevitable.

The clothing on the mannequin could have a positive or adverse ef- fect on location of the victim by both the drone and classic search arms. At the time of the search, the mannequin was wearing dark-colored trousers and a dark sweater. The dark-colored clothing used in our sce- nario was not easily distinguishable from the natural environment, and made locating the victim more difficult. It will be much easier to locate a victim in the field wearing highly visible clothing, such as orange apparel.

The images taken by the drone camera may not be optimal at High altitude, and particularly under foggy conditions. We therefore recom- mend that for the moment classic searches be performed concurrently with drone searches. Additionally, there may be national restrictions concerning the use of drones. In our study, there was no restriction under Turkish law on using the drone in mountainous terrain since it weighed b 4 kg and the altitude involved was b 100 m. Different coun- tries’ laws on the use of drones may vary, and operators must comply with these restrictions.

A much larger area can be searched per unit of time in a search using a drone compared to CST. Although consequences such as impaired tab- let screen visibility due to wind, rain or excessive sunlight may occur in a drone search, such interruptions will be minimized as the technology improves.

We think that a clearer image can be obtained when the imAge SI– multaneously transferred to the tablet is also transmitted to units with a larger screen located in the shade. Indeed, when images of the search for the first mannequin, detected in 7.69 min, were monitored on a large screen at the end of the study, the drone entered the search area within 2 min, but it could not be seen on the tablet screen due to reflection of sunlight. It may therefore be anticipated that problems encountered in drone studies will be resolved through advances in drone technology and that aid can be brought to victims and patients much more quickly.

Conclusions

In conclusion, of the two different search and rescue methods evalu- ated, DST makes it possible to search a larger area in a shorter space of time, to locate the victim faster and for rescuers transported by snow- mobile to reach the victim faster compared to CLT.

Acknowledgements

We are grateful to Mr. Yunus Batmaz for flying the drone during our study.

Conflicts of interests statement

The authors declare that they have no significant competing finan- cial, professional or personal interests that might have influenced the performance or presentation of the work described in this manuscript.

Financial/material support

None. Disclosures None.

Author contributions

YK, MC, ST: substantial contributions to conception and design, ac- quisition of data, analysis and interpretation of data, drafting the article or revising it critically for important intellectual content and final ap- proval of the version to be published; OT, AS, SP: acquisition of data, in- terpretation of data, drafting the article or revising it critically for important intellectual content and final approval of the version to be published; SP, OT, AS, MFB: acquisition of data, drafting the article and final approval of the version to be published; YK, MC, ST: interpretation of data, drafting the article or revising it critically for important intellec- tual content and final approval of the version to be published.

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