A scoping review on drone technology applications in forensic science

Abstract

Drones, formally known as Unmanned Aerial Vehicles (UAVs), are versatile technology increasingly associated with many modern-day applications. The advancements in technology have brought about a revolution in drones, extending their applications in various fields, including forensic science. Despite their potential, the full extent of drone capabilities in forensic science remains unclear and limited by a lack of defined evidence. Therefore, this article aims to provide a comprehensive review of the current literature on the use of drones in forensic science, while also highlighting the challenges and limitations of their deployment. This review seeks to identify areas for further research and development in the use of drones in forensic science by exploring the key issues. The use of Arksey and O’Malley’s framework updated by Joanna Briggs Institute for Scoping Reviews methodology shows that drones have proven to be a valuable technology in various forensic-related events, including clandestine graves detection, crime scene investigations, traffic accident investigations, disaster assistance, and pollution detection. However, there is still inadequate information on the use of drones in forensic science, particularly in enhancing the Disaster Victim Identification (DVI) procedure during the initial phase of a disaster. Therefore, this paper aims to provide insights into the potential applications of drones in forensic science and promote their integration into related fields.

Article Highlights

The article represents the first comprehensive review that categorises drone applications in forensic science.

Deployment of drones in forensic science remains relatively limited, despite the advancement in drone technology.

Integration of external sensors and software allows drones to perform a wider range of contemporary applications.

Introduction

Unmanned Aerial Vehicles (UAVs) or interchangeably known as drones are any kind of autonomously or remotely controlled vehicles piloted through pre-programmed computer software or by a remote pilot on the ground [1]. Forensic science refers to the application of scientific methods and techniques to investigate and solve crimes or other legal issues. As the use of drones in forensic science has gained more popularity, there is a growing need for the classification of their applications to guide future studies. Currently, available review articles [2–5] were mostly conducted based on a broad search without a structured literature review method that could possibly result in the exclusion of relevant studies. Hence, the objective of our paper is to gather the existing evidence from recent studies and provide a comprehensive discussion on the various functions of drones in forensic science.

Drones are often associated with the ability to perform "3D" missions (dirty, difficult, and dangerous) resulting in their broadened use and in-depth research in various fields. Drones allow for procedures to be conducted quickly, and efficiently with less risk in comparison to manned operations [6, 7] such as delivering essential supplies to individuals affected by disasters in situations where traditional routes are inaccessible. Although drones have been widely adopted in many forensic procedures, there is still limited and unclear evidence regarding categorisations of drone applications in forensic science, highlighting the need for further research in this area.

A number of studies have been compiled in this paper, narrowing the scope of drone applications in forensic science into crime scene investigations, clandestine graves detection, traffic accident investigations, disaster assistance and pollution detection. This paper implements the Arksey and O’Malley’s framework updated by Joanna Briggs Institute for Scoping Review to summarise 30 research papers from 2012 to 2022, depicting the research trend of drone deployment in forensic science. A number of studies have proposed that combining drones as part of search and recovery of dead bodies could greatly improve the capabilities of Disaster Victim Identification (DVI) teams [8–10] but there is a lack of existing research on the correlation between drones and DVI. As such, this review paper exists to assess the potential of drones in forensic science and explore ways to broaden its current applications.

In the next section, Sect. 2., we consider the methodology comprising the research question, identification of relevant studies, studies selection, charting of data as well as collating, summarising, and reporting of results. Following that, Sect. 3 exhibit results of studies starting with clandestine graves detection, crime scene investigations, traffic accident investigations, disaster assistance, and pollution detection. In Sects. 4 and 5, we present the discussion and conclusion respectively. The final section includes the funding, declaration of competing interest and references of the study.

Methodology

The Arksey and O’Malley’s framework [11] updated by Joanna Briggs Institute (JBI) framework [12] for Scoping Reviews methodology was utilised to summarise multiple studies in order to clarify the key concepts and knowledge gaps of published literature. Scoping review is an outline of an indistinct subject orchestrated by mapping the existing evidence from different sources instead of seeking very specific research questions or measuring the quality of studies [11]. There are five steps in the Arksey and O’Malley’s framework: (1) identify the research question, (2) identify relevant studies, (3) studies selection, (4) data charting, and lastly (5) collating, summarising, and reporting the results [11]. The JBI framework is an extended version providing up-to-date guidance aligned with Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) to assist authors in conducting a scoping study [13].

Research question

To the best of our knowledge, there is very limited inclusive review that have been done to assess drone applications in forensic science. Hence, this review paper was created to measure the present use of drones in forensic science and identify drones’ advancement that can be utilised in future forensic science studies. The research question of this review is "What is the most common application of drones in forensic science?". Following this, the authors seek to collate and organise all relevant evidence to expand upon the subject matter to narrow down the research question.

Identification of relevant studies

Relevant articles were obtained from a variety of online sources between January 2012 and December 2022. The keywords used to search for relevant literatures are depicted in Table 1. The first two keywords are ‘drone’ and ‘forensic’ obtained from the research question and the rest were derived from the subsequent publications found.

Table 1. Summary of the keywords used

Main keywords	Other keywords	Description of keywords
Drone	Unmanned Aerial/Aircraft Vehicle (UAV) Unmanned Aerial/Aircraft System (UAS) Remotely Piloted Aircraft Systems (RPAS) Remotely Aerial/Aircraft Vehicle (RAV) Remotely Piloted Vehicles (RPV) Remotely Piloted Aircraft (RPA) Remotely Operated Aircraft (ROA)	A single or swarm unmanned aircraft(s) that can be either autonomously programmed or remotely piloted from the ground
Forensic	Crime scene Clandestine grave Disaster Traffic accident Environmental pollution	Situations that require forensic evaluations or conducted in forensic settings

Studies selection

The existing literatures were selected by evaluating the relevancy of their contents to the study topic. However, several exceptions have been made prior to the selection process as exhibited by the PRISMA-ScR selection process flow diagram (Fig. 1). Only articles with full-text in English were included meanwhile dissertation/thesis, news articles/reports and abstract proceedings were exempted from this paper. Similarly, studies involving other technologies, highly reliant on technical work, not in forensic context, grey literatures, and full-text not in English were excluded from this scoping review.

Fig. 1 [Images not available. See PDF.]

PRISMA-ScR selection process flow diagram

Charting the data

Figure 1 illustrates the systematic selection process flowchart, following the guidelines of PRISMA-ScR.

Collating, summarising, and reporting the results

Table 2 summarise all relevant studies included in the scoping review.

Results

Although forensic science is a vast field with multiple sub-disciplines, not many forensic disciplines incorporated drones in their operations. Table 2 categorised drone applications against several forensic sub-disciplines, and from this resulting literature, the following trends were observed.

Table 2. The summary of relevant articles

No	Author/ Year/ Origin	Title	Study Design/ Population	Concept	Context
1	Lega et al 2012 Italy [14]	Using advanced aerial platforms and infrared thermography to track environmental contamination	Experimental study	Using drones to detect, evaluate, and track signs of environmental contamination	Water pollution
2	Ruffell et al 2014 UK [15]	Search protocols for hidden objects beneath floors and within walls	Experimental study	• UAV takes dual images for the creation of stereo-pairs and digital terrain models • Instant camera changing for ultra-violet and infra-red mode to search for hidden objects	Clandestine graves (indoor)
3	Lega et al 2014 Italy [16]	Remote sensing in environmental police investigations: Aerial platforms and an innovative application of thermography to detect several illegal activities	Case study	Aerial infrared thermography used for detection of illicit water activities such as illegal sewer and storm-drain environmental policy violations	Water pollution
4	Cusack & Maeakafa 2016 New Zealand [17]	Establishing effective and economical traffic surveillance in Tonga	Experimental study	Using drones to detect the number plate of vehicles that are over height, overweight, over speed limit, and process the data in real-time	Traffic surveillance
5	Su et al 2016 China [18]	Developing an unmanned aerial vehicle-based rapid mapping system for traffic accident investigation	Case study	Developing UAV mapping system to acquire traffic accident scene diagrams	Traffic accident
6	Bucknell & Bassindale 2017 UK [19]	An investigation into the effect of surveillance drones on textile evidence at crime scenes	Experimental study	• Drone’s downwash effects are too powerful for smooth surfaces • Drones are not recommended for indoor use	Crime scene
7	Tannant et al 2017 Canada [20]	Characterization and analysis of a translational rockslide on a stepped-planar slip surface	Case study	• UAV live footages are useful during emergency responses • UAV help to analyse new condition of the rock slope	Disaster (rockslide)
8	Urbanova et al 2017 Czech Republic [21]	Using drone-mounted cameras for on-site body documentation: 3D mapping & active survey	Experimental study	Drones are capable of building high quality large-scale 3D models of outdoor crime scene	Crime scene (outdoor)
9	Stana et al 2017 Czech Republic [22]	Comparison of utilization of conventional and advanced methods for traffic accidents scene documentation in the Czech Republic	Case study	UAV imaging and documentation is preferable for the overview of traffic accident scene, especially when structural and technical conditions of the road are non-conventional	Traffic accident
10	Evers & Masters 2018 UK [23]	The application of low-altitude near-infrared aerial photography for detecting clandestine burials using a UAV and low-cost unmodified digital camera	Experimental study	• UAV with near-infrared filter able to differentiate soil and vegetation marks to locate clandestine graves • Weather condition have considerable effect on the acquisition and image processing phases	Clandestine graves
11	Girardot et al 2018 USA [24]	Application of the systems decision process to swarm drone nuclear detection	Experimental study	• Using swarm drone technology to survey & identify radiation gradient, monitoring the exposed area and collecting radiological samples • Swarm drone technology has the ability to coordinate even if a single drone is not mission capable or destroyed	Disaster (nuclear radiation)
12	Blau et al 2018 Australia [25]	Exploring non-invasive approaches to assist in the detection of clandestine human burials: Developing a way forward	Experimental study	Drones survey using LiDAR sensor can be used as a major detector of clandestine graves	Clandestine graves
13	Murray et al 2018 USA [26]	Survey and insights into unmanned aerial-vehicle-based detection and documentation of clandestine graves and human remains	Experimental study	UAV thermal imaging for graves detection is most productive around solar noon to minimise the impact of shadows	Clandestine graves
14	Burdziakowski 2018 Poland [27]	UAV in today’s photogrammetry – Application areas and challenges	Experimental study	Remotely-controlled UAV is recommended when operating indoor or many obstacles present to avoid collision with people or infrastructures	Photogrammetry
15	Cappelletti et al 2019 Italy [28]	Forensic engineering surveys with UAV photogrammetry and laser scanning techniques	Experimental study	• Circular pattern is the best flight plan to document a traffic accident • Photogrammetric point cloud density is determined by the camera resolution, flight height and data processing settings	Traffic accident
16	Kim et al 2019 Korea [29]	Applicability assessment of UAV mapping for disaster damage investigation in Korea	Case study	Using 3D terrain information and high-resolution ortho-imagery to analyse structural damage and evaluate mapping accuracy	Disasters (landslides, floods)
17	Kopeikin et al 2019 USA [30]	Unmanned aircraft system swarm for radiological and imagery data collection	Experimental study	• Drone swarming aid forensic analysis efforts in post-nuclear blast, e.g., providing radiation gradient heat-map • UAS quickly locate best area to collect nuclear sample	Disaster (nuclear radiation)
18	Parrott et al 2019 UK [31]	A low-cost approach to disturbed soil detection using low altitude digital imagery from an unmanned aerial vehicle	Experimental study	• UAV able to limit unnecessary footfall and minimise crime scene alteration • Proposed that future image processing could be completed in the field, providing access to a laptop preinstalled with MATLAB	Clandestine graves
19	Sharma et al 2019 UAE [32]	Comparative analysis and implication of UAV and AI in forensic investigations	Experimental study	• UAV with AI can help to interpret collected data and segregate the evidence type during photo capturing process • UAV able to look for invisible trace of evidences and photograph them without compromising the integrity	Crime scene
20	Pensieri et al 2020 Italy [33]	Drones as an integral part of remote sensing technologies to help missing people	Experimental study	Drones with thermographic tracking equipment and software able to detect human presence in darkness	Clandestine graves
21	Padua et al 2020 Portugal [34]	Digital reconstitution of road traffic accidents: A flexible methodology relying on UAV surveying and complementary strategies to support multiple scenarios	Experimental study	• UAV flight height and camera angle are important for orthorectification and virtual modelling • Nadiral images of camera angle provides best orthorectified mosaics • Lower flight heights allow for a higher spatial resolution, enabling more accurate measurements of traffic accident scene	Traffic accident
22	Rocke et al 2021 UK [35]	Drone aerial imagery for the simulation of a neonate burial based on the Geoforensic Search Strategy (GSS)	Case study	• Using Drone Deploy software to create topographic and vegetation index maps • Data from drone has higher resolution with cost- and time-efficiency than traditional methods • Drones are non-invasive, thus preserve any potential forensic evidence found	Clandestine graves (neonatal)
23	Butters et al 2021 Australia [8]	Application of forward-looking infrared (FLIR) imaging from an unmanned aerial platform in the search for decomposing remains	Experimental study	• Using UAV-mounted thermal sensor to detect a range of decomposition scenarios • Wrappings partly impeded detection of heat but still detectable because of their contrast to the background • UAV-detection of buried bodies were more difficult as remains integrated with the surrounding soil	Decomposition
24	Silvan-Cardenas et al 2021 Mexico [36]	Assessing optical remote sensing for graves detection	Experimental study	• Using UAV photogrammetry to detect burial anomalies • Thermal UAV can detect recently deceased bodies or in a decomposition process	Clandestine graves
25	Molina et al 2021 Colombia [37]	Monitoring of simulated clandestine graves of dismembered victims using UAVs, electrical tomography, and GPR over one year to aid investigations of human rights violations in Colombia, South America	Experimental study	• UAV able to detect buried remains in difficult terrain and climates, as well as smaller-sized graves of mutilated victims • Clothed remains have better UAV image detection, since clothes provide a good target surface for electromagnetic waves	Clandestine graves
26	Rocke & Ruffell 2022 UK [38]	Detection of single burials using multispectral drone data: Three case studies	Case study	• Using multispectral drone to detect graves of various age from the burial inception to full revegetation • Drone able to determine the plant health via sharp change in vegetation reflectance	Clandestine burials
27	Cunha et al 2022 Brazil [39]	Laser scanner and drone photogrammetry: A statistical comparison between 3D models and its impacts on outdoor crime scene registration	Experimental study	Drone photogrammetry is low-cost, less time-consuming technique and useful for large outdoor crime scenes but not recommended for small evidence (< 3 cm)	Crime scene (outdoor)
28	Loli et al 2022 Greece [40]	Flood characterization based on forensic analysis of bridge collapse using UAV reconnaissance and CFD simulations	Case study	UAV greatly enhanced rapid bridge inspection and structural health assessment by surveying on-site structural material characterisation	Disaster (flash floods)
29	Georgiou et al 2022 UK [41]	UAV-assisted real-time evidence detection in outdoor crime scene investigations	Experimental study	• UAV was faster in areas larger than 30 m × 50 m due to its accuracy and speed of detection • UAV able to detect smaller objects even when flying in high speed and highly reliant on communication data links	Crime scene (outdoor)
30	Wang et al 2022 China [42]	Reconstruction of a real-world car-to-pedestrian collision using geomatics techniques and numerical simulations	Case study	• UAV photogrammetry was more efficient in accident data collection since it shortens the data collecting time by 84% and removes traffic disruption • Data from UAV can help to analyse the severity and mechanism of injury	Traffic accident

Clandestine graves detection

Single or mass clandestine graves are commonly built by criminals to conceal the dead bodies. Searching for clandestine graves often start with large-scale methods including drones [37], which can systematically explore a wide range of area and pinpoint high-probability regions in a short span of time [25]. Drones offer not only non-intrusive and non-destructive benefits [43, 44], but also serve as a valuable tool for aerial photography, especially for gathering information from wide areas, providing a cost-effective alternative to traditional techniques [23]. The revolution of drones from aircraft and satellites was driven by increased accessibility to much lower altitudes and higher image resolution [35, 38]. According to Murray et al. [26], drone-mounted sensors provide a highly effective method of detecting evidence that may be beyond the scope of human vision. This approach also provides a cost-effective and time-efficient method of obtaining high-resolution documentation output, both in terms of spectral and spatial information [25]. It is important to note that working towards a multi-sensor platform must be undertaken with experts in the relevant fields [25].

Environmental influences have always been considered a limiting factor for the universal use of drones [38]. However, Ruffell et al. [15] claimed that air gaps, soil disturbance, and waterlogged conditions are able to assist drone to locate a sub-surface anomaly when searching for clandestine graves beneath concrete. Meanwhile, burial sites located among complex topography and dense vegetation can be detected using drone spectral imaging based on different reflectance characteristics [23]. Normalised Difference Vegetation Index (NDVI) has been used to measure the density and health of vegetation [37] by determining the difference in reflectance of visible red and near-infrared (NIR) light [35]. Evers and Masters [23] reported that NIR reflectance is able to identify disturbed soil from non-disturbed soil, and differentiate healthy green versus stressed vegetation when attempting to locate areas that are commonly characterise as clandestine graves. Clandestine graves can be recognised visually by features like spoil heaps or depressions measuring one-by-two metres, abnormal vegetation growth patterns, animal scavenging, and potential concealment using specific materials to divert suspicion [45–47]. Thermal imageries were also useful in identifying unusual patches of vegetation, especially where a recent burial is suspected [25, 26, 36]. Furthermore, drone data can be acquired and processed in a short time without disturbing vegetation and soil to preserve potential forensic evidence [35].

A drone equipped with forward‐looking infrared (FLIR) camera can also be used to detect heat emitted by insect and microbial activity on decomposing remains [8]. Thermal detection of dead bodies was greatest when the ambient temperatures were between 10–35°C with highest thermal contrast to the adjacent soil occurring during peak insect activity [8]. Additionally, clothing offers an excellent target surface for electromagnetic waves and stands out in contrast to the surrounding ground surface [37, 48, 49]. The application of electrical resistivity imaging after burial can detect a minor positive resistivity anomaly caused by greater conductivity of the clothing in comparison to the surrounding soil [48]. Moreover, clothing tends to absorb more sunlight, generating more heat compared to the insect infestations [8]. As a result, drones can detect clothed victims easier than unclothed remains [8, 37, 48, 49]. Drones also able to detect thermal signatures from a whole body or smaller body fragments even when they are concealed in a variety of ways [8, 37]. Although thermal signals were evident in night-time [8], thermal imaging is most productive just before sunrise or after sunset [25] with flying operations typically conducted around solar noon to minimise the shadow impacts [26]. It is worth noting that cooled thermal camera offers better magnification capabilities, sensitivity and spectral filtering [8].

Crime scene investigation (CSI)

Photography represents the gold standard for forensic documentation and serves as a powerful source of evidence in court [32, 50] and drones provide a unique perspective in taking photos and videos from various angles, exclusively the aerial view. With the advent of drone technology, modern forensic practitioners can augment their procedures by incorporating drone photography into their existing protocols [21]. Drones equipped with various sensors and software are capable of performing a range of crime scene investigation (CSI) tasks, including aerial mapping and planning of crime scene without tampering the evidence; continuous observation, surveying, and monitoring of crime scenes with minimal human intervention; as well as utilising artificial intelligence (AI) techniques for automatic recognition and recording of evidence [5, 32]. Additionaly, the basic ability of recording by drones itself can be extremely valuable in CSI, especially if the area is widespread or of a complex nature [3, 39].

According to Bornik et al. [51], digital evidence have proven to be invaluable in documenting and reconstructing crime scenes. In court trials, photography allows the jury to closely examine the visual evidence [52] since these photographs effectively relay information and play a crucial role in proving a case [53]. Their significance lies in their ability to clarify crime scenes and present compelling visual evidence during investigations and court proceedings [54]. Moreover, photograph act as digital witnesses, containing descriptive elements that vividly describe incidents at the scene [7]. They also serves as a powerful medium for gathering evidence and relevant information to assist in the investigation [50]. Interestingly, courts have become increasingly receptive to digital evidence, sometimes without insisting on scientific verifications [55]. This shift demonstrates the growing importance of digital proof, which in some cases has surpassed the reliance on traditional eyewitness testimonies [53].

Preservation of a crime scene is a crucial step in an investigation. Thus, a preliminary scene survey conducted by drones can be performed even before investigators get into the site. Quick analysis of the scene survey allows method of scene examination to be determined rapidly, reducing the investigation period, and increasing the chances of identifying and apprehending suspects [19, 21]. By using drone images, investigators can have a better understanding of the crime scene layout including the extent, entry and exit points [19]. While being a valuable tool for photography, drones potentially serve as a medium in tele-forensic investigations, enabling real-time data transmission from the crime scene to the laboratory for immediate analysis by the experts (e.g., blood spatter analysis) [3–5]. Those who were not available at both the crime scene and laboratory could also have access to the situations through drones’ data provided by the investigators.

Bucknell et al. [19] expressed that drones might preserve a scene better than having the investigators on-site because drones are better at photographing small evidence without damaging the traces [5], or approaching the evidence at a closer range [3]. Drones are capable of taking footage or sensory information from different viewpoints of the crime scene [3] as well as videotaping the large, inaccessible crime scenes efficiently in a short span of time [5]. Furthermore, evidence necessary for forensic data collection can possibly be discovered by drones [5] with better precision and detection of speed across a variety of terrain types [41]. Artificial Intelligence (AI) is the creation of algorithms and models that enable machines to perform tasks that typically require human intelligence. Sharma et al. [32] proposed that drones equipped with AI are capable of aiding pre-planning of evidence collection, in addition to identifying and sorting evidence using a barcode scanning.

Drones rely on the Global Positioning System (GPS) for navigation and positioning. Therefore, in an outdoor crime scene, drones flight path logs are considered valuable in court as they raise the credibility of the recorded crime scene footage [3]. A study by Georgiou et al. [41] mentioned that drones are considered to be ultimately more effective for areas larger than 1,500 m² since they achieved better outcomes in terms of accuracy and speed detection compared to the on-foot field team. Light Detection and Ranging (LiDAR) is a remote sensing technology that uses lasers to measure distances and create detailed maps. By integrating LiDAR sensors with drones, the entire crime scene can be digitally mapped, forming a three-dimensional (3D) scene reconstruction [5, 21] to gather precise distance and depth information.

With drone photogrammetry, larger image of crime scene can be acquired, subsequently defining the topographic information [39] and provide accurate outline of crime scene along with interpersonal distances of evidence [4, 32]. Additionally, Urbanová et al. [56] reported that digital camera-based photogrammetry and stereophotogrammetry-based handheld scanners were proven to be very advantageous for post-mortem body documentation in forensic pathology. If combined with high resolution texture, they can also offer information on subtle external interferences and time-sensitive coloration, both of which are crucial for finding forensic evidence [21].

Traffic accident investigation

Drones are increasingly used in traffic accidents investigations for its undeniable advantages including safer [27], faster [28, 34, 42], and more thorough applications [22, 34] which indirectly minimising the investigation cost [17]. Furthermore, drones has greater accuracy and efficiency in accident data collection than hand sketch and measurements [34, 42]. It shortens the data collecting time by 84% and these data can be used to analyse the severity and mechanism of the injuries [42]. Most drones have an SD card or small storage device to store the data due to the large file sizes associated with drone imagery. If the camera being used is the camera integrated into the drone and not an external remote sensor, data can be processed either on the drone motherboard and stored for later analysis; or reviewed it in real-time using a laptop processing unit [17]. In drone surveillance context, investigators simply need to process, analyse, and evaluate the footage since evidence has been made available [17], minimising the need for human intervention in data acquisition process and lowering the risk of human error [34]. Apart from recording footages of moving vehicles as well as processing their number plates and speed data automatically [17], drones can instantly collect data for digital reconstruction [18, 27, 28, 34, 42], and monitor secondary crashes along with the alternate routes [34, 57]. Followed by traffic rerouting procedures, drones able to digitally preserve the scene through photogrammetry reconstitution with a comprehensive context and debris location [34]. It is important to note that the drones setup and documentation of the entire crash scene can be conducted in a short time [34] without neglecting details even when the scene is no longer preserved [28]. Without sufficient detailed input data, the collision process and results of reconstruction could compromises the forensic investigations [42].

Photographic image documentation can be created for rectification from selected points, viewing the collision scene and its closest surroundings [22, 28, 58]. The collected data are processed using photogrammetric software to create orthophoto mosaic, dense point clouds and textured virtual to digitally document the traffic accident [27, 34]. While density of the laser point cloud can be simply set by adjusting the scan resolution, density of photogrammetric point cloud is determined by the camera resolution, flight height and data processing settings [28]. Both flight height and camera angle are important keys for orthorectification and virtual modelling [34]. Meanwhile, nadiral images produce best orthorectified mosaics [34], and circular flight plan resulted in a more complete and undistorted reconstruction [28]. In addition, lower flight heights with higher spatial resolutions enabled more accurate measurements [34]. Since it is highly dependent on the imagery quality to deliver complete and accurate digital outcomes, portable lightweight light sources can be mounted on the drone, ensuring the camera is neither obstructed nor overexposed [34]. However, very dark and metallic surfaces are difficult to detect due to the high degree of absorbed energy and reflectivity respectively [28].

Disaster assistance

Drones with radiation sensor deployed in the Fukushima nuclear post-blast played an important role in collecting radiation data of the catastrophe [24, 30]. Multi-drone or swarm system was developed to aid the post-blast data collection and analysis through monitoring of radiation levels, generating gradient heat-maps, continuous surveillance of the exposed area, identifying the materials and sources involved, assessing visual damage, and maintaining the public safety [24, 30]. Drone swarm system can quickly locate areas that have been contaminated with radiological debris and select the best areas to safely collect the sample due to its capability to collect imagery and radiation data rapidly [24, 30]. Swarm system specifically offered faster data acquisition with a much safer alternative especially in hazardous environments [24]. According to Girardot et al. [24], the swarm operates as a unit and their ability to coordinate allows them to adapt to changes and continue the mission even if a single drone is not mission-capable or destroyed. The swarm behaviour continues until each survey point is reached by one drone and data is transmitted to the home station. The swarm is limited by a boundary which forces drones to return to a rally point if they breach the fence. As drones reach low battery, they automatically return to home station where the battery can be swapped without disconnecting drones from the system to avoid restarting of behaviour. Furthermore, drone data from the post-blast can revealed important aspects of the weapon to conclude the origin and medium of detonation [24].

Drones were also helpful in assessing the structural damage as a result of a disaster [20, 29, 40]. Drone mapping is essential in enabling rapid data collection necessary for the interpretation of structural failure [40] and its suitability for mapping is dependent on mapping extent, geometric accuracy, flight time, control distance, etc. [29]. According to Kim et al. [29], 3D point cloud data obtained from drones in a landslide event provide an accurate measure of width and depth of the outflows, as well as the soil runoff distance. During a rockslide incident, drone footages allow for quick decision-making during the first phase of the emergency response and the aerial images were used to analyse new condition of the rock slope [20]. As stated by Loli et al. [40], drones greatly enhanced rapid bridge inspection, becoming a particularly valuable tool for post-disaster reconnaissance and collection of perishable data due to their ease of use and ability to collect high-quality data remotely and safely. Forensic investigations were conducted in conjunction with drone surveying and on-site structural material characterisation, where the rapid damage reconnaissance by drone allow material field testing to be conducted immediately before the onset of restoration works [40]. Drones were employed to develop 3D models of the target infrastructure but due to the intricate geometry, autonomously-collected photos were complemented thru additional photos captured by piloted drone [40]. In addition, drones could potentially be beneficial in Disaster Victim Identification (DVI) with image processing techniques from drone-mounted thermal camera used to enhance early on-site forensic victim identification [10]. DVI is a formal process of establishing the identity of individuals who have died as a result of a mass mortality event using scientifically proven techniques.

Pollution detection

Drones coupled with thermal imager were used to detect environmental water pollution such as unlawful factory waste disposal by scanning the region and locally focusing on the suspected site [14, 16]. As the aerial platform shifted from helicopters to drones, decrease in flight altitude resulted in an increase in resolution, allowing for detection of environmental micro anomalies as well as spatially comprehensive coverage at a much higher spatial resolution [14]. However, the environmental surveillance still requires an integrated system based on data from several sources including space, air, waterways, and land monitoring as well as gathering forensic data and information from navigation systems. With proper tools in the hands of government and law enforcement agencies, intentional acts of environmental damage can be deterred [14].

Discussion

To the best of our knowledge, this is the first PRISMA-guided review paper focusing on drone technology applications in forensic science. The available review articles were mostly conducted using a general search approach without a systematic literature review method, which may have led to the exclusion of pertinent studies. It should be highlighted that this topic had limited research to conduct a systematic review due to the absence of drone standardisation for forensic practice, insufficient drone ethics and law regulations, along with limited knowledge and awareness of drone use. Therefore, the rationale behind writing this paper is to provide comprehensive information on drone technology applications in forensic science. This article reviewed the function of drones in existing forensic operations and its future direction in forensic science.

At the present time, there is increasing number of publications showing a growing interest in the application of drone technology in forensic science. Drones have been progressively used in forensic science to offer a high-quality documentation data, scene reconstruction, evidence detection, searching for missing person, targeting suspects, etc. However, the evolution of forensic cases in recent years has rendered some aspects of the established methodology inapplicable, highlighting the need for modern solutions such as drone technology to tackle contemporary challenges. While drones offered various advantages for use in forensic science, limitations and knowledge gaps in previous studies are still significant.

Drones are ideal for providing an overview of a particular situation. However, when flying through an area with many obstacles such as people and infrastructure, it is advisable to have a drone pilot operating the aircraft to prevent collisions with the surroundings. Flying drones at a higher altitude provides a larger field of view but production of low-resolution images resulting in failure of detecting smaller evidence. Hence, there is a need to standardise a certain range of height before flying the drone, to avoid any waste of time in determining the best altitudes out of many available height options. Although drones can digitally preserve the scene better and faster than the traditional methods, it is more practical for use in large outdoor regions instead of a smaller space, especially enclosed areas. This is due to their downwash effects being too powerful for indoor use, consequently affecting the integrity of potential forensic evidence. However, drone with lesser downwash effects, perhaps a small-sized drone could be opted for use in confined areas as a substitute.

Studies that are highly reliant on simulated environment tend to overestimate and provide insufficient data to represent real-world cases. Previous research studies were mostly conducted under normal conditions, meanwhile urgent outdoor forensic operations e.g., disasters and traffic accidents are likely to happen under unfavourable environments. Therefore, future studies are envisioned to deploy drones under extreme conditions, or even better if executed in an actual scenario. Although many studies concentrated on detecting clandestine burials regardless day or night, among complex vegetation or concrete, small- or large-sized graves; very few studies have mentioned the use of drones to search for deceased disaster victims, let alone complementing and facilitating Disaster Victim Identification (DVI) process using drones at disaster sites. In post-disaster, victims might get concealed under rubble due to collapsed building or buried when landslides happen, depicting how valuable drones can be in such situations. Thus, future studies are warranted to examine the potential application and roles of drones in assisting and supporting on-site DVI process.

It is of utmost importance for drone operators to obtain flight training from professional drone pilot or practice using an online flight simulator for a better forensic operation, in addition to having relevant expertise on-site when working with multi-sensor platforms. This is because, cooperation between trained drone operators with appropriate sensor experts could produce a time-efficient and enhanced investigation. On the other hand, appearance of drones in public are sometimes viewed as a threat. Therefore, it is important to educate the society about the benefits of drones, to reduce their negative perceptions on this technology and gain their attention and cooperation, especially in critical incidents such as disaster. Furthermore, for multi-sensor drones to be acknowledged and implemented by the academic and medicolegal groups, best practices with standard operating procedures and protocols of drones use in forensic investigations need to be established. Or else, it will all remain academic and will not be used by those in relevant fields.

Overall, there is a lot more to explore and improve but the existing limitations and challenges must be first addressed for imminent advancement. Most studies have shown that computer software are key enablers for drone-based forensic investigations. Hence, it is important to highlight that drone technology exists to support the investigation and not entirely replace the labour-intensive operations.

Conclusion

This article represents the first PRISMA-structured scoping review that categorises drone applications in forensic science. Despite the growing research, in terms of work-related capacity, it can be concluded that drones are scarcely used in forensic works such as clandestine graves detection, crime scene investigation, traffic accident investigation, disaster assistance, and pollution detection. Existing research on this topic are still inadequate to produce a systematic review because many of the articles found were comprehensive technical studies and not in forensic frameworks. However, not many studies have mentioned about drones use to search and recover for dead bodies of major disaster, let alone to complement and facilitate Disaster Victim Identification (DVI) process. Drones may transfer fingerprint data or DNA samples taken on-site to DVI command centre for rapid identification. As such, initial response efforts by first responders can be enhanced, leading to increased efficiency and effectiveness of forensic specialists in their subsequent work. Overall, additional comprehensive research is needed to address the efficiency and cost-effectiveness of drones in forensic science, especially in DVI.

Funding

This study was funded by the Malaysia Ministry of Higher Education TRGS (Trans-disciplinary Research Grant Scheme) [Grant code: 600-IRMI/TRGS 5/3 (001/2019)-2] awarded to the corresponding author.

Declarations

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

1. D'Andrea, R. Guest editorial can drones deliver?. IEEE Trans Autom Sci Eng; 2014; 11, 3 pp. 647-648. [DOI: https://dx.doi.org/10.1109/TASE.2014.2326952]

2. Kelly, AB; Kelly, NM. Validating the remotely sensed geography of crime: A review of emerging issues. Remote Sens; 2014; 6, 12 pp. 12723-12751. [DOI: https://dx.doi.org/10.3390/rs61212723]

3. Slak B (2022) Drones in (Slovene) criminal investigation. Kriminalistička teorija i praksa 2016; Available from: https://hrcak.srce.hr/file/268980. Accessed 7 Sept 2022

4. Mendis, N; Dharmarathne, T; Wanasinghe, N. Use of unmanned aerial vehicles in crime scene investigations-novel concept of crime scene investigations. Forensic Res Criminol Int J; 2016; 4, 1 00094. [DOI: https://dx.doi.org/10.15406/frcij.2017.04.00094]

5. Mishra V, Dedhia H, and Wavhal S (2022) Application of drones in the investigation and management of a crime scene. Forensic Science 2015; Available from: https://www.worldwidejournals.com/global-journal-for-research-analysis-GJRA/fileview/April_2015_1430372928__83.pdf. Accessed 1 Sept 2022

6. Naidoo Y, Stopforth R, and Bright G (2011) Development of an UAV for search & rescue applications. IEEE Africon'11, pp 1–6. https://doi.org/10.1109/AFRCON.2011.6072032.

7. Horsman, G. Unmanned aerial vehicles: a preliminary analysis of forensic challenges. Digit Investig; 2016; 16, pp. 1-11. [DOI: https://dx.doi.org/10.1016/j.diin.2015.11.002]

8. Butters, O; Krosch, MN; Roberts, M; MacGregor, D. Application of forward-looking infrared (FLIR) imaging from an unmanned aerial platform in the search for decomposing remains. J Forensic Sci; 2021; 66, 1 pp. 347-355. [DOI: https://dx.doi.org/10.1111/1556-4029.14581]

9. Daud, SMSM; Yusof, MYPM; Heo, CC; Khoo, LS; Singh, MKC; Mahmood, MS; Nawawi, H. Applications of drone in disaster management: a scoping review. Sci Justice; 2022; 62, 1 pp. 30-42. [DOI: https://dx.doi.org/10.1016/j.scijus.2021.11.002]

10. Khoo LS, Mohd Yusof MYP, Chainchel Singh MK, Md Tahir N, Muhamat AA, Mahmood MS and Nawawi H (2021) Emerging Issues and DVI Research in Malaysia, in Disaster Victim Identification Malaysia – MH17 Tragedy: The Untold Story, UiTM Press: Malaysia. pp 160–179. ISBN: 978–967–363–758–4.

11. Arksey, H; O'Malley, L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol; 2005; 8, 1 pp. 19-32. [DOI: https://dx.doi.org/10.1080/1364557032000119616]

12. Peters MD, Godfrey CM, McInerney P, Soares CB, Khalil H and Parker D (2015) The Joanna Briggs Institute reviewers' manual 2015: methodology for JBI scoping reviews. Available from: https://reben.com.br/revista/wp-content/uploads/2020/10/Scoping.pdf. Accessed 9 June 2022

13. Peters, MD; Marnie, C; Tricco, AC; Pollock, D; Munn, Z; Alexander, L; McInerney, P; Godfrey, CM; Khalil, H. Updated methodological guidance for the conduct of scoping reviews. JBI Evid Synthesis; 2020; 18, 10 pp. 2119-2126. [DOI: https://dx.doi.org/10.11124/JBIES-20-00167]

14. Lega, M; Kosmatka, J; Ferrara, C; Russo, F; Napoli, R; Persechino, G. Using advanced aerial platforms and infrared thermography to track environmental contamination. Environ Forensics; 2012; 13, 4 pp. 332-338. [DOI: https://dx.doi.org/10.1080/15275922.2012.729002]

15. Ruffell, A; Pringle, JK; Forbes, S. Search protocols for hidden forensic objects beneath floors and within walls. Forensic Sci Int; 2014; 237, pp. 137-145. [DOI: https://dx.doi.org/10.1016/j.forsciint.2013.12.036]

16. Lega, M; Ferrara, C; Persechino, G; Bishop, P. Remote sensing in environmental police investigations: aerial platforms and an innovative application of thermography to detect several illegal activities. Environ Monit Assess; 2014; 186, 12 pp. 8291-8301. [DOI: https://dx.doi.org/10.1007/s10661-014-4003-3]

17. Cusack B and Maeakafa G (2016) Establishing effective and economical traffic surveillance in Tonga. The Proceedings of 14th Australian digital forensics conference, pp 50–56. https://doi.org/10.4225/75/58a4fe76b3d3a.

18. Su, S; Liu, W; Li, K; Yang, G; Feng, C; Ming, J; Liu, G; Liu, S; Yin, Z. Developing an unmanned aerial vehicle-based rapid mapping system for traffic accident investigation. Aust J Forensic Sci; 2016; 48, 4 pp. 454-468. [DOI: https://dx.doi.org/10.1080/00450618.2015.1073787]

19. Bucknell, A; Bassindale, T. An investigation into the effect of surveillance drones on textile evidence at crime scenes. Sci Justice; 2017; 57, 5 pp. 373-375. [DOI: https://dx.doi.org/10.1016/j.scijus.2017.05.004]

20. Tannant, D; Giordan, D; Morgenroth, J. Characterization and analysis of a translational rockslide on a stepped-planar slip surface. Eng Geol; 2017; 220, pp. 144-151. [DOI: https://dx.doi.org/10.1016/j.enggeo.2017.02.004]

21. Urbanová, P; Jurda, M; Vojtíšek, T; Krajsa, J. Using drone-mounted cameras for on-site body documentation: 3D mapping and active survey. Forensic Sci Int; 2017; 281, pp. 52-62. [DOI: https://dx.doi.org/10.1016/j.forsciint.2017.10.027]

22. Stáňa, I; Tokař, S; Bucsuházy, K; Bilík, M. Comparison of utilization of conventional and advanced methods for traffic accidents scene documentation in the Czech Republic. Procedia Eng; 2017; 187, pp. 471-476. [DOI: https://dx.doi.org/10.1016/j.proeng.2017.04.402]

23. Evers, R; Masters, P. The application of low-altitude near-infrared aerial photography for detecting clandestine burials using a UAV and low-cost unmodified digital camera. Forensic Sci Int; 2018; 289, pp. 408-418. [DOI: https://dx.doi.org/10.1016/j.forsciint.2018.06.020]

24. Girardot A, Ratliff W, Volpe M and Morales R (2022) Application of the systems decision process to swarm drone nuclear detection. West Point Annual General Donald R. Keith Memorial Conference. SISE 2018; Available from: http://www.ieworldconference.org/content/WP2018/Papers/GDRKMCC-18_2.pdf. Accessed 2 Sept 2022

25. Blau, S; Sterenberg, J; Weeden, P; Urzedo, F; Wright, R; Watson, C. Exploring non-invasive approaches to assist in the detection of clandestine human burials: developing a way forward. Forensic Sci Res; 2018; 3, 4 pp. 320-342. [DOI: https://dx.doi.org/10.1080/20961790.2018.1493809]

26. Murray, B; Anderson, DT; Wescott, DJ; Moorhead, R; Anderson, MF. Survey and insights into unmanned aerial-vehicle-based detection and documentation of clandestine graves and human remains. Hum Biol; 2018; 90, 1 pp. 45-61. [DOI: https://dx.doi.org/10.13110/humanbiology.90.1.03]

27. Burdziakowski, P. Uav in todays photogrammetry – application areas and challenges. Int Multidiscipl Sci GeoConf Survey Geol and Mining Ecol Manag, SGEM; 2018; 18, pp. 241-248. [DOI: https://dx.doi.org/10.5593/sgem2018/2.3/S10.031]

28. Cappelletti, C; Boniardi, M; Casaroli, A; De Gaetani, CI; Passoni, D; Pinto, L. Forensic engineering surveys with UAV photogrammetry and laser scanning techniques. ISPRS Annals of the Photogramm, Remote Sens and Spatial Inf Sci; 2019; 42, pp. 227-234. [DOI: https://dx.doi.org/10.5194/isprs-archives-XLII-2-W9-227-2019]

29. Kim, S.S., Kim, T.H., and Sim, J.S., (2019) Applicability Assessment of UAV Mapping for Disaster Damage Investigation in Korea. ISPRS ICWG III/IVA GI4DM 2019 - Geoinformation for Disaster Management, 42-3: pp 209-214. https://doi.org/10.5194/isprs-archives-XLII-3-W8-209-2019.

30. Kopeikin AN, Heider SA, Larkin DM, Bluman JE, Korpela CM and Morales RO, (2019) Unmanned aircraft system swarm for radiological and imagery data collection. AIAA Scitech 2019 Forum, https://doi.org/10.2514/6.2019-2286.

31. Parrott, E; Panter, H; Morrissey, J; Bezombes, F. A low cost approach to disturbed soil detection using low altitude digital imagery from an unmanned aerial vehicle. Drones; 2019; 3, 2 50. [DOI: https://dx.doi.org/10.3390/drones3020050]

32. Sharma BK, Chandra G and Mishra VP (2019) Comparitive Analysis and Implication of UAV and AI in Forensic Investigations. In: Proceedings - 2019 Amity international conference on artificial intelligence, AICAI 2019, pp 824–827. https://doi.org/10.1109/AICAI.2019.8701407.

33. Pensieri, MG; Garau, M; Barone, PM. Drones as an integral part of remote sensing technologies to help missing people. Drones; 2020; 4, 2 pp. 1-10. [DOI: https://dx.doi.org/10.3390/drones4020015]

34. Pádua, L; Sousa, J; Vanko, J; Hruška, J; Adão, T; Peres, E; Sousa, A; Sousa, JJ. Digital reconstitution of road traffic accidents: a flexible methodology relying on UAV surveying and complementary strategies to support multiple scenarios. Int J Environ Res Public Health; 2020; 17, 6 1868. [DOI: https://dx.doi.org/10.3390/ijerph17061868]

35. Rocke, B; Ruffell, A; Donnelly, L. Drone aerial imagery for the simulation of a neonate burial based on the geoforensic search strategy (GSS). J Forensic Sci; 2021; 66, 4 pp. 1506-1519. [DOI: https://dx.doi.org/10.1111/1556-4029.14690]

36. Silván-Cárdenas, J; Caccavari-Garza, A; Quinto-Sánchez, M; Madrigal-Gómez, J; Coronado-Juárez, E; Quiroz-Suarez, D. Assessing optical remote sensing for grave detection. Forensic Sci Int; 2021; 329, 111064. [DOI: https://dx.doi.org/10.1016/j.forsciint.2021.111064]

37. Molina, CM; Wisniewski, K; Heaton, V; Pringle, J; Avila, EF; Herrera, LA; Guerrero, J; Saumett, M; Echeverry, R; Duarte, M; Baena, A. Monitoring of simulated clandestine graves of dismembered victims using UAVs, electrical tomography, and GPR over one year to aid investigations of human rights violations in Colombia, South America. J Forensic Sci; 2021; [DOI: https://dx.doi.org/10.1111/1556-4029.14962]

38. Rocke, B; Ruffell, A. Detection of single burials using multispectral drone data: three case studies. Forensic Sci; 2022; 2, 1 pp. 72-87. [DOI: https://dx.doi.org/10.3390/forensicsci2010006]

39. Cunha, RR; Arrabal, CT; Dantas, MM; Bassaneli, HR. Laser scanner and drone photogrammetry: a statistical comparison between 3-dimensional models and its impacts on outdoor crime scene registration. Forensic Sci Int; 2022; 330, 111100. [DOI: https://dx.doi.org/10.1016/j.forsciint.2021.111100]

40. Loli, M; Mitoulis, SA; Tsatsis, A; Manousakis, J; Kourkoulis, R; Zekkos, D. Flood characterization based on forensic analysis of bridge collapse using UAV reconnaissance and CFD simulations. Sci Total Environ; 2022; 822, 153661. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2022.153661]

41. Georgiou, A; Masters, P; Johnson, S; Feetham, L. UAV-assisted real-time evidence detection in outdoor crime scene investigations. J Forensic Sci; 2022; 67, 3 pp. 1221-1232. [DOI: https://dx.doi.org/10.1111/1556-4029.15009]

42. Wang, J; Li, Z; Zou, D; Chen, Y. Reconstruction of a real-world car-to-pedestrian collision using geomatics techniques and numerical simulations. J Forensic and Legal Med; 2022; 91, 102433. [DOI: https://dx.doi.org/10.1016/j.jflm.2022.102433]

43. Kalacska, M; Bell, LS. Remote sensing as a tool for the detection of clandestine mass graves. Canadian Soc Forensic Sci J; 2006; 39, 1 pp. 1-13. [DOI: https://dx.doi.org/10.1080/00085030.2006.10757132]

44. Doolittle, JA; Bellantoni, NF. The search for graves with ground-penetrating radar in Connecticut. J Archaeol Sci; 2010; 37, 5 pp. 941-949. [DOI: https://dx.doi.org/10.1016/j.jas.2009.11.027]

45. Cox M and Hunter J (2005) Forensic archaeology: advances in theory and practice. Routledge. ISBN: 9780415273121.

46. France, DL; Griffin, TJ; Swanburg, JG; Lindemann, JW; Davenport, GC; Trammell, V; Armbrust, CT; Kondratieff, B; Nelson, A; Castellano, K. A multidisciplinary approach to the detection of clandestine graves. J Forensic Sci; 1992; 37, pp. 1445-1445. [DOI: https://dx.doi.org/10.1520/JFS13337J]

47. Larson, DO; Vass, AA; Wise, M. Advanced scientific methods and procedures in the forensic investigation of clandestine graves. J Contemp Crim Justice; 2011; 27, 2 pp. 149-182. [DOI: https://dx.doi.org/10.1177/10439862114058]

48. Pringle, JK; Stimpson, IG; Wisniewski, KD; Heaton, V; Davenward, B; Mirosch, N; Spencer, F; Jervis, JR. Geophysical monitoring of simulated homicide burials for forensic investigations. Sci Rep; 2020; 10, 1 7544. [DOI: https://dx.doi.org/10.1038/s41598-020-64262-3]

49. Schultz, JJ. Sequential monitoring of burials containing small pig cadavers using ground penetrating radar. J Forensic Sci; 2008; 53, 2 pp. 279-287. [DOI: https://dx.doi.org/10.1111/j.1556-4029.2008.00665.x]

50. Zahari, F; Harun, A; Nasrijal, NMH. A systematic literature review on the usage of digital photography at crime scene investigation process. J Pharm Negative Results; 2022; [DOI: https://dx.doi.org/10.47750/pnr.2022.13.S06.269]

51. Bornik, A; Urschler, M; Schmalstieg, D; Bischof, H; Krauskopf, A; Schwark, T; Scheurer, E; Yen, K. Integrated computer-aided forensic case analysis, presentation, and documentation based on multimodal 3D data. Forensic Sci Int; 2018; 287, pp. 12-24. [DOI: https://dx.doi.org/10.1016/j.forsciint.2018.03.031]

52. Sheppard, K; Fieldhouse, S; Cassella, J. Experiences of evidence presentation in court: an insight into the practice of crime scene examiners in England, Wales and Australia. Egypt J Forensic Sci; 2020; 10, pp. 1-12. [DOI: https://dx.doi.org/10.1186/s41935-020-00184-5]

53. Senthil, P; Selvakumar, S. RETRACTED ARTICLE: digital proof collective model using integrated fusion data modelling. Wireless Pers Commun; 2022; 127, Suppl 1 pp. 11-11. [DOI: https://dx.doi.org/10.1007/s11277-021-08713-8]

54. Gilmour, PM. The application of photography in investigating fraud. Imaging Sci J; 2019; 67, 4 pp. 215-223. [DOI: https://dx.doi.org/10.1080/13682199.2019.1600254]

55. Stoykova, R. Digital evidence: unaddressed threats to fairness and the presumption of innocence. Computer Law & Security Rev; 2021; 42, 105575. [DOI: https://dx.doi.org/10.1016/j.clsr.2021.105575]

56. Urbanová, P; Hejna, P; Jurda, M. Testing photogrammetry-based techniques for three-dimensional surface documentation in forensic pathology. Forensic Sci Int; 2015; 250, pp. 77-86. [DOI: https://dx.doi.org/10.1016/j.forsciint.2015.03.005]

57. Stevens Jr CR and Blackstock T (2022) Demonstration of Unmanned Aircraft Systems Use for Traffic Incident Management (UAS-TIM). 2017; Available from: https://static.tti.tamu.edu/tti.tamu.edu/documents/PRC-17-69-F.pdf. Accessed 20 Nov 2022

58. Ly, C; Yusof, M; Hasmi, AH; Mahmood, MS. Death of two military pilots in Hawk-108 fighter jet crash. J Forensic Sci and Med; 2018; 4, 2 pp. 101-103. [DOI: https://dx.doi.org/10.4103/jfsm.jfsm_91_17]