Evidence map›Paper›PMID 30311001›Full record

ArticleJournal of medical systems2018

Internet of things for knowledge administrations by wearable gadgets.

Sivakumar Krishnan, S Lokesh, M Ramya Devi

RetractedAbstract readRetracted Publication
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. 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

5 · Who and what money

Authors and funding

3 authors.

Sivakumar KrishnanPrincipal - Academics, Rathinam Technical Campus, Coimbatore, Tamil Nadu, India. rksivakumar@gmail.com.
S LokeshDepartment of Computer Science and Engineering, Hindusthan Institute of Technology, Coimbatore, Tamil Nadu, India.
M Ramya DeviDepartment of Computer Science and Engineering, Hindusthan College of Engineering and Technology, Coimbatore, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The novel gadgets are associated constantly at a quick phase for the development of Internet of Things (IoT). Wearable gadgets are another gathering development in those available gadgets. The recent method in gadgets is to coordinate with IoT and idea is implementing the remote sensor systems that convey novel encounters in day by day exercises. Here, I exhibit a regular day to day existence application including a Wireless Sensor Networks (WSN) for gaming situation. By using this, the physical factors of sports person are estimated and directed by wearable gadgets to Wireless Sensor Networks. The end goal to incorporate diverse equipment stages and to present an administration situated semantic middleware arrangement hooked on a solitary request also utilization of Enterprise Service Bus (ESB) is introduced as a scaffold to ensure coordination of the distinctive conditions and interoperability. Through proposed method everyone can procure information by introducing framework to fresh client. Those clients would be able to get to the information through a wide assortment of gadgets (cell phones, tablets, and PCs) and working frameworks (Android, Windows, Linux, iOS, and so on). Finally we introduced one case study of football match for monitoring 11 players and acquiring data's and to predict the real time situation in football ground.

Indexed as

InternetWearable Electronic DevicesWireless TechnologyBody TemperatureData CompressionElectrocardiography, AmbulatoryHeart RateHumansMaleMonitoring, AmbulatorySmartphoneSoccerWeatherYoung AdultEnterprise service busHealth monitoringIoTWearable devicesWireless sensor networks

Identifiers

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.