Evidence map›Paper›PMID 34054219›Full record

ArticleJournal of intelligent & robotic systems2021

HMDCS-UV: A concept study of Hybrid Monitoring, Detection and Cleaning System for Unmanned Vehicles.

Salima Bella, Ghalem Belalem, Assia Belbachir, Hichem Benfriha

Abstract read
In one paragraph

Article in Journal of intelligent & robotic systems, 2021. 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
–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

0 citing papers in PubMed.

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

4 authors.

Salima BellaDepartment of Computer Science, Faculty of Exact and Applied Sciences, Computer Laboratory of Oran (LIO), Université Oran 1, Oran, Algeria.ORCID 0000-0001-8185-3782
Ghalem BelalemDepartment of Computer Science, Faculty of Exact and Applied Sciences, Computer Laboratory of Oran (LIO), Université Oran 1, Oran, Algeria.
Assia BelbachirMechatronics Department, Polytechnic Institute of Advanced Sciences, IPSA, Ivry-sur-Seine, France.
Hichem BenfrihaDepartment of Computer Science, Faculty of Exact and Applied Sciences, Computer Laboratory of Oran (LIO), Université Oran 1, Oran, Algeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Incidents of hydraulic or oil spills in the oceans/seas or ports occur with some regularity during the exploitation, production and transportation of petroleum products. Immediate, safe, effective and environmentally friendly measures must be adopted to reduce the impact of the oil spill on marine life. Due to the difficulty to detect and clean these areas, semi-autonomous vehicles can make a significant contribution by implementing a cooperative and coordinated response. The paper proposes a concept study of Hybrid Monitoring Detection and Cleaning System (HMDCS-UV) for a maritime region using semi-autonomous unmanned vehicles. This system is based on a cooperative decision architecture for an unmanned aerial vehicle to monitor and detect dirty zones (i.e., hydraulic spills), and clean them up using a swarm of unmanned surface vehicles. The proposed solutions were implemented in a real cloud and were evaluated using different simulation scenarios. Experimental results show that the proposed HMDCS-UV can detect and reduce the level of hydraulic pollution in maritime regions with a significant gain in terms of energy consumption.

Indexed as

DetectionHybrid architectureSwarmTrajectory planningUAV (Unmanned Aerial Vehicle)USV (Unmanned Surface Vehicle)

Identifiers

PMID34054219
PMCPMC8147586

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.