Evidence map›Paper›PMID 33930047›Full record

ArticlePloS one2021

A decentralized hybrid computing consumer authentication framework for a reliable drone delivery as a service.

Abdul Hannan, Faisal Hussain, Noman Ali, Muhammad Ehatisham-Ul-Haq, Muhammad Usman Ashraf, Ahmed Mohammad Alghamdi, Ahmed Saeed Alfakeeh

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Abdul HannanUniversity of Management and Technology, Sialkot, Pakistan.ORCID 0000-0001-9426-9470
Faisal HussainAl-Khwarizmi Institute of Computer Science (KICS), University of Engineering and Technology (UET), Lahore, Pakistan.ORCID 0000-0001-9812-7488
Noman AliUniversity of Management and Technology, Sialkot, Pakistan.
Muhammad Ehatisham-Ul-HaqSino-Pak Center for Artificial Intelligence (SPCAI), Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology, Haripur, Khyber Pakthunkhwa, Pakistan.
Muhammad Usman AshrafUniversity of Management and Technology, Sialkot, Pakistan.
Ahmed Mohammad AlghamdiDepartment of Software Engineering, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia.
Ahmed Saeed AlfakeehDepartment of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The thriving adoption of drones for delivering parcels, packages, medicines, etc., is surging with time. The application of drones for delivery services results in faster delivery, fuel-saving, and less energy consumption. Giant companies like Google, Amazon, Facebook, etc., are actively working on developing, testing, and improving drone-based delivery systems. So far, a lot of work has been done for improving the design, speed, operating range, security of the delivery drones, etc. However, very limited work has been done to ensure a complete and reliable last-mile delivery from the merchant's store to the hands of the actual customer. To ensure a complete and reliable last-mile delivery, a drone must authenticate the consumer before dropping the package. Therefore, in this work, we propose a consumer authentication (Consumer-Auth) hybrid computing framework for drone delivery as a service to make sure that the parcel is perfectly delivered to the intended customer. The proposed Consumer-Auth framework enables a drone to reach the exact destination by using the GPS coordinates of the customer autonomously. After reaching the exact location, the drone waits for the customer to come to the specific pinned location then it starts a two-factor consumer authentication process, i.e., one-time password (OTP) verification and face Recognition. The experimental results manifest the effectiveness of the proposed Consumer-Auth framework to ensure a complete and reliable drone-based last-mile delivery.

Indexed as

AircraftBiometric IdentificationAlgorithmsHumansRemote Sensing Technology

Identifiers

PMID33930047
PMCPMC8087081

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.