Evidence map›Paper›PMID 34300447›Full record

ArticleSensors (Basel, Switzerland)2021

Driving Behaviour Analysis Using Machine and Deep Learning Methods for Continuous Streams of Vehicular Data.

Nikolaos Peppes, Theodoros Alexakis, Evgenia Adamopoulou, Konstantinos Demestichas

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Demand-Driven Data Acquisition for Large Scale Fleets.Sensors (Basel, Switzerland) · 2021
    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

4 authors.

Nikolaos PeppesInstitute of Communication and Computer Systems, Zografou, 15773 Athens, Greece.ORCID 0000-0002-9911-0837
Theodoros AlexakisInstitute of Communication and Computer Systems, Zografou, 15773 Athens, Greece.ORCID 0000-0002-9138-2926
Evgenia AdamopoulouInstitute of Communication and Computer Systems, Zografou, 15773 Athens, Greece.ORCID 0000-0001-7137-012X
Konstantinos DemestichasInstitute of Communication and Computer Systems, Zografou, 15773 Athens, Greece.ORCID 0000-0002-8858-6389

Funding

Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH-CREATE-INNOVATE T1EDK-04610-MANTIS
6 · The paper itself

Abstract

In the last few decades, vehicles are equipped with a plethora of sensors which can provide useful measurements and diagnostics for both the vehicle's condition as well as the driver's behaviour. Furthermore, the rapid increase for transportation needs of people and goods together with the evolution of Information and Communication Technologies (ICT) push the transportation domain towards a new more intelligent and efficient era. The reduction of CO

Indexed as

Automobile DrivingDeep LearningAccelerationHumansTransportationdata streamingdeep learning (DL)driving behaviour analysis (DBA)machine learning (ML)vehicle sensors

Identifiers

PMID34300447
PMCPMC8309619

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.