Evidence map›Paper›PMID 31878091›Full record

ArticleSensors (Basel, Switzerland)2019

Distributed Architecture to Integrate Sensor Information: Object Recognition for Smart Cities.

Jose-Luis Poza-Lujan, Juan-Luis Posadas-Yagüe, José-Enrique Simó-Ten, Francisco Blanes

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. 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

4 authors.

Jose-Luis Poza-LujanUniversity Institute of Control Systems and Industrial Computing (ai2), Universitat Politècnica de València (UPV) Camino de Vera, s/n. 46022 Valencia, Spain.
Juan-Luis Posadas-YagüeUniversity Institute of Control Systems and Industrial Computing (ai2), Universitat Politècnica de València (UPV) Camino de Vera, s/n. 46022 Valencia, Spain.
José-Enrique Simó-TenUniversity Institute of Control Systems and Industrial Computing (ai2), Universitat Politècnica de València (UPV) Camino de Vera, s/n. 46022 Valencia, Spain.
Francisco BlanesUniversity Institute of Control Systems and Industrial Computing (ai2), Universitat Politècnica de València (UPV) Camino de Vera, s/n. 46022 Valencia, Spain.

Funding

Spanish Science and Innovation Ministry MICINN: CICYT project PRECON-I4: "Predictable and dependable computer systems for Industry 4.0" TIN2017-86520-C3-1-R
6 · The paper itself

Abstract

Object recognition, which can be used in processes such as reconstruction of the environment map or the intelligent navigation of vehicles, is a necessary task in smart city environments. In this paper, we propose an architecture that integrates heterogeneously distributed information to recognize objects in intelligent environments. The architecture is based on the IoT/Industry 4.0 model to interconnect the devices, which are called smart resources. smart resources can process local sensor data and offer information to other devices as a service. These other devices can be located in the same operating range (the edge), in the same intranet (the fog), or on the Internet (the cloud). smart resources must have an intelligent layer in order to be able to process the information. A system with two smart resources equipped with different image sensors is implemented to validate the architecture. Our experiments show that the integration of information increases the certainty in the recognition of objects by 2-4%. Consequently, in intelligent environments, it seems appropriate to provide the devices with not only intelligence, but also capabilities to collaborate closely with other devices.

Indexed as

distributed architecturesinformation integrationobject detectionsmart citiessmart environmentsmart sensors

Identifiers

PMID31878091
PMCPMC6982956

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.