Industrial IoT and Long Short-Term Memory Network-Enabled Genetic Indoor-Tracking for Factory Logistics

Author:

Wu Wei1ORCID,Shen Leidi1,Zhao Zhiheng2ORCID,Li Ming3ORCID,Huang George Q.1ORCID

Affiliation:

1. Department of Industrial Manufacturing and Systems Engineering, University of Hong Kong, Hong Kong

2. School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China

3. School of Intelligent Systems Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

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1. On the accuracy of BLE indoor localization systems: An assessment survey;Computers and Electrical Engineering;2024-09

2. Logistics 4.0 – digital transformation with smart connected tracking and tracing devices;International Journal of Production Economics;2024-09

3. BLIPS: Bluetooth locator for an Indoor Positioning System in Realtime;Proceedings of the 7th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies;2024-07-08

4. Predicting Factory Equipment Lifespan Through Manufacturing Data Analysis using AI;Journal of Machine and Computing;2024-07-05

5. LOJİSTİK FİRMALARINDA NESNELERİN İNTERNETİ ÜZERİNDE YAPILAN ÇALIŞMANIN BİLİMSEL HARİTALAMA YÖNTEMİ İLE ANALİZİ;Beykoz Akademi Dergisi;2024-06-26

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