Evidence map›Paper›PMID 35296688›Full record

ArticleScientific reports2022

Design and test of intelligent inspection and monitoring system for cotton bale storage based on RFID.

Weipeng Zhang, Bo Zhao, Qizhi Yang, Liming Zhou, Hanlu Jiang, Kang Niu, Jian Ding

Abstract read
In one paragraph

Article in Scientific reports, 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

7 authors.

Weipeng ZhangThe State Key Laboratory of Soil-Plant-Machinery System Technology, Chinese Academy of Agricultural Mechanization Sciences, Beijing, 100083, China.
Bo ZhaoThe State Key Laboratory of Soil-Plant-Machinery System Technology, Chinese Academy of Agricultural Mechanization Sciences, Beijing, 100083, China. zhaoboshi@126.com.
Qizhi YangJiangsu University, Zhenjiang, China.
Liming ZhouThe State Key Laboratory of Soil-Plant-Machinery System Technology, Chinese Academy of Agricultural Mechanization Sciences, Beijing, 100083, China.
Hanlu JiangThe State Key Laboratory of Soil-Plant-Machinery System Technology, Chinese Academy of Agricultural Mechanization Sciences, Beijing, 100083, China.
Kang NiuThe State Key Laboratory of Soil-Plant-Machinery System Technology, Chinese Academy of Agricultural Mechanization Sciences, Beijing, 100083, China.
Jian DingAgricultural Machinery Service Center in Pingdu City, Pingdu, 266700, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To solve the inspection problems in cotton storage, as well as the need for environmental monitoring in the process of modern cotton bale storage, an intelligent inspection and temperature and humidity intelligent monitoring system based on RFID cotton bale was developed by adopting RFID (Radio Frequency Identification) technology, wireless temperature and humidity real-time monitoring technology and handheld terminal intelligent inspection technology. The system was composed of RFID positioning inspection module and temperature and humidity real-time monitoring and transmission module. The artificial neural network (ANN) based on the particle swarm optimization (PSO) algorithm was used to process the monitoring data of the system by Gaussian filtering, and an accurate classification model of RSSI and label position was established. The test results showed that: Through the comparative analysis of the RFID indoor positioning algorithm, the positioning error of the PSO-ANN algorithm was small. In the actual cotton bale warehouse test, the relative error of positioning and monitoring for RFID cotton bale intelligent inspection and monitoring system was less than 6.7%, which effectively improved the working efficiency of inspection personnel and the security of cotton bale storage. The relative error of temperature and humidity was less than 8% and less than 7%, which could display the temperature and humidity information in real time and meet the real-time demand. This study improved the management personnel's effective positioning and inspection of the cotton bale, prevented the loss of cotton bale, reduced the deterioration probability of cotton bale, and effectively improved the storage management level of the cotton bale. It was of great practical significance to realize the networking, automation, and intelligence of cotton bale storage management.

Indexed as

Radio Frequency Identification DeviceAlgorithmsIntelligenceMonitoring, PhysiologicNeural Networks, Computer

Identifiers

PMID35296688
PMCPMC8927612

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Registered trials

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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.