Advances in Applied Science Research Open Access

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Short Communication - (2022) Volume 13, Issue 2

Drone Forensic Domain Abstract Model
Capla Jozef*
1Department of IT, Yale University, USA
*Correspondence: Capla Jozef, Department of IT, Yale University, USA, Tel: + 1348936828, Email:

Received: 02-Feb-2022, Manuscript No. AASRFC-22-12878; Editor assigned: 04-Feb-2022, Pre QC No. AASRFC-22-12878(PQ); Reviewed: 18-Feb-2022, QC No. AASRFC-22-12878; Revised: 23-Feb-2022, Manuscript No. AASRFC-22-12878(R); Published: 02-Mar-2022, DOI: 10.36648/0976-8610.13.2.54


Drone Forensics (DRF) is a subdomain of computerised crime scene investigation that aims to catch and deconstruct the robot’s actions. Because of the various robot field guidelines, working frameworks, and foundation based networks, it is a diverse, muddled, and complex area. In order to accommodate various examination cycles and exercises, as well as the specific robot situations, a few DRF models and systems have been developed. These models make the area even more perplexing and sloppy for space lawyers. As a result, there is no nonexclusive model for making do, sharing, and reusing the DRF area’s cycles and exercises. Using the metamodeling advancement process, this paper aims to develop A Drone Forensic Metamodel (DRFM) for the DRF space.


• Recognisable proof,

• Procurement and protection, and

• Assessment and information investigation.

It is used to structure and sort DRF space data, as well as to make due with, putting together, sharing, and reusing DRF space data among area scientific experts. In a created DRFM, this intends to distinguish, perceive, concentrate, and match various DRF processes, ideas, exercises, and errands from other DRF models. As a result, space specialists will be able to infer/start up arrangement models without difficulty.

Using metamodel change, the consistency and relevance of the created DRFM were approved (vertical change). The results showed that the created DRFM is reliable and understandable, and that it enables space measurable experts to effectively start up new arrangement models by selecting and combining idea components (quality and tasks) based on their model requirements. The DRF field is a well-known and important field that collects, recognises, and re-creates records related to potential UAV episodes. In the writing, a few models, structures, strategies, approaches, instruments, and calculations for the DRF area have been presented to manage various UAV episodes.

1. It gives drones communication through a common layer that utilises all DRF projects, ideas, exercises, and cycles.

2. It gives a reasonable guide to plan a compelling model to make due, reuse, and share DRF information and data.

3. It is effectively pertinent, particularly for DRF specialists, to plan and make new arrangements by utilising all properties and tasks in light of the model requirements.

4. It gives quick access to DRF information and data.

A few efforts have been made to promote this field of study: However, the most important research in this area deals with drones from a specialised perspective. The writing falls short of a reasonable system for criminological examination that sorts out, structures, and works with the DRF space. In this vein, the purpose of this paper is to highlight the current challenges and issues in the DRF field and to propose a robot criminological [1-5].


The findings revealed that the DRF area has a slew of issues that make it a perplexing, uncertain, and heterogeneous environment for quantifiable professionals and specialists. To address these issues, this paper proposed DRFM to address the DRF space’s heterogeneity and interoperability issues. The recognisable proof stage, the obtaining and conservation stage, and the assessment and examination stage are the three main stages. The reasonable structure separated the main moves and suggested a solution for dealing with DRF’s current difficulties and issues. Future work could zero in on fostering a vault for the proposed DRFM to store all significant information on the DRF space and approve the viability, culmination, and rationale of the proposed DRFM from the level change.


The authors are grateful to the journal editor and the anonymous reviewers for their helpful comments and suggestions.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest for the research, authorship, and/or publication of this article.


Citation: Capla J (2022) Drone Forensic Domain Abstract Model. Adv Appl Sci Res. 13:54

Copyright: © Capla J. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.