Evidence map›Paper›PMID 36236579›Full record

ArticleSensors (Basel, Switzerland)2022

IoTMapper: A Metrics Aggregation System Architecture in Support of Smart City Solutions.

João Pedro Vitorino, Nuno Cruz

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. 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

2 authors.

João Pedro VitorinoFuture Internet Technologies-FIT, Instituto Superior de Engenharia de Lisboa-ISEL, Instituto Politécnico de Lisboa, 1500-335 Lisbon, Portugal.ORCID 0000-0003-1533-7231
Nuno CruzFuture Internet Technologies-FIT, Instituto Superior de Engenharia de Lisboa-ISEL, Instituto Politécnico de Lisboa, 1500-335 Lisbon, Portugal.ORCID 0000-0001-8570-8670

Funding

Fundação para a Ciência e Tecnologia LISBOA-01-0247-FEDER-04611Fundação para a Ciência e Tecnologia POCI-01-0247-FEDER-04611
6 · The paper itself

Abstract

Smart cities are, nowadays, an unavoidable and growing reality, supported on software platforms that support city management, through the processing and presentation of a large number of data, obtained from sensors used throughout the cities. Low-power wide area networks (LPWAN) leverage the sensorization process; however, urban landscape, in turn, induces a high probability of change in the propagation conditions of the LPWAN network, thus requiring active monitoring solutions for assessing the city LPWAN network condition. Currently existing solutions usually consider the existence of only one type of LPWAN network to be monitored. In this paper, an architecture for aggregation of metrics from heterogeneous LPWAN networks is presented. The architecture, named IoTMapper, combines purpose build components with existing components from the FIWARE and Apache Kafka ecosystems. Implementation details for the LPWAN networks are abstracted by adapters so that new networks may be easily added. The validation was carried out using real data collected for long-range wide-area network (LoRaWAN) in Lisbon, and a simulated data set extrapolated from the collected data. The results indicate that the presented architecture is a viable solution for metrics aggregation that may be expanded to support multiple networks. However, some of the considered FIWARE components present performance bottlenecks that may hinder the scaling of the architecture while processing new message arrivals.

Indexed as

EcosystemCitiesMonitoring, PhysiologicApache KafkaFIWAREinternet of thingsLoRaWANlow-power wide area network (LPWAN)smart cities

Identifiers

PMID36236579
PMCPMC9573566

What OpenQuestion holds

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LicenceCC BY
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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.