Evidence map›Paper›PMID 35340699›Full record

ArticleJournal of ambient intelligence and humanized computing2022

Human robot interaction as a service for combatting COVID-19: an experimental case study.

Yusuf Özçevik

Open access · bronzeAbstract read
In one paragraph

Article in Journal of ambient intelligence and humanized computing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 47% of its field
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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

1 author at 1 institution in 1 country.

Yusuf ÖzçevikDepartment of Software Engineering, Manisa Celal Bayar University, Manisa, Turkey.ORCID 0000-0002-0943-9226
Manisa Celal Bayar University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 pandemic has changed today's routines in a variety of fields such as society, economics, health, etc. It is surely known that the most powerful weapon to fight against the disease is the social distancing. Hence, it is strongly recommended by the authorities to decrease human to human interaction (HHI) in order to stop the spread. However, daily routine of people must continue somehow, because of the fact that it is not known when the pandemic will end permanently. Thus, new approaches should be adapted in social environments for COVID-19 prevention. Human robot interaction (HRI) can be seen as a vital mechanism to provide risk free routines in the society. For this purpose, we offer a human robot interaction as a service (HRIaaS) for eatery locations such as restaurants, cafes, etc. where customers should interact with the staff. The proposed service aims to utilize personal smartphones and decrease the number of HHIs for such environments in which strange people involved. Moreover, an experimental case study is conducted to obtain an evaluation with a real world scenario when the proposed service is used versus a contemporary routine with HHIs. The evaluation results show that an average reduction of 41% is achieved per customer in the number of HHIs between customers and serving staff.

Indexed as

Cloud servicesCombatting COVID-19Human robot interactionPost pandemic

Identifiers

PMID35340699
PMCPMC8934408
OpenAlexW4221005141

What OpenQuestion holds

Textmetadata
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.