Evidence map›Paper›PMID 35712319›Full record

ArticleFrontiers in public health2022

Construction of a Traceability System for Food Industry Chain Safety Information Based on Internet of Things Technology.

Siyuan Lin, Qi Shi, Ning Zhou

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

3 authors.

Siyuan LinInstitute of Food and Strategic Reserves, Nanjing University of Finance and Economics, Nanjing, China.
Qi ShiSchool of Economics, Nanjing University of Finance and Economics, Nanjing, China.
Ning ZhouSchool of Economics, Nanjing University of Finance and Economics, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The continuous development of the social economy, has stimulataed an increase in the satndard of living and increased the deman for consumption resulting in the demand for high-quality and safe food has continued to increase. The so-called food safety means that the food that people eat under certain conditions will not harm human health. Frequent food safety incidents have highlighted the seriousness of my country's food safety problems and exposed loopholes in my country's food safety supervision. This article aims to study the construction of the Internet of Things technology in the food industry chain safety information traceability system, research on the RFID technology, GPS technology, and sensor technology in the Internet of things technology, and also conduct some research on the modules of the food industry chain safety information traceability system. This paper proposes to integrate the Internet of Things technology into the construction of the food industry chain safety information traceability system. First, a detailed analysis of some of the technologies that may be used is carried out, and then through the investigation of people on food safety and other aspects, and the food traceability system satisfaction survey. The experimental results in this article show that 40% of women pay more attention to food safety. Of course, in the satisfaction survey of the food safety traceability system based on the Internet of Things technology, it has been recognized by more than 20% of the people.

Indexed as

Internet of ThingsFemaleFood IndustryFood SafetyHumansInternetTechnologyfood industry chainindustry chainInternet of Things technologysafety systemtraceability system

Identifiers

PMID35712319
PMCPMC9196936

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.