{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:50:35Z","timestamp":1776811835150,"version":"3.51.2"},"reference-count":17,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2023,4,4]]},"abstract":"<jats:p>The engineering project warehouse can combine various sensor devices and smart devices under the Internet of Things technology to realize the convenient management of the warehouse. The Internet of Things technology combined with the machine learning model can make various industries transform to intelligence. The use of IoT technology and machine learning models for warehouse management can achieve an unattended warehouse effect. The Internet of Things has gradually developed into the intelligent technology that attracts the most attention in various industries with the advancement of electronic components required by various sensors. Combining various sensor devices and smart devices under the Internet of Things technology to achieve convenient management of warehouses, its intelligent management of warehouse security, environment, fire protection, energy consumption, etc. can save a lot of manpower and material resources, and improve the project warehouse, Utilization of supplies. Machine learning technology is a new type of computer self-learning technology produced along with artificial intelligence technology, which can combine the corresponding algorithm and the definition of the developer to realize the learning of the defined transaction. Because the way of this operation is similar to the human learning ability, machine learning Warehouse management for engineering projects will maximize the unattended effect of the warehouse. The research adopts a combination of questionnaire survey and modeling analysis. At first, analyzes the current demand points of engineering project warehouse management in various industries through a questionnaire survey, and designs the Internet of Things auxiliary scheme for engineering project warehouse management according to the demand points. The IoT-assisted machine learning model compares the IoT engineering project warehouse management solution without machine learning model with the IoT engineering project warehouse management solution with machine learning. It is found that the solution with machine learning model can effectively improve the engineering project warehouse management. abilities in all aspects including the effective utilization rate of necessities, manpower saving and safety accident control, which proves that the research has high use value.<\/jats:p>","DOI":"10.3233\/jcm-226630","type":"journal-article","created":{"date-parts":[[2022,12,6]],"date-time":"2022-12-06T13:07:14Z","timestamp":1670332034000},"page":"663-673","source":"Crossref","is-referenced-by-count":2,"title":["IoT-assisted machine learning model for engineering project warehouse management"],"prefix":"10.66113","volume":"23","author":[{"given":"Yongke","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","reference":[{"issue":"11","key":"10.3233\/JCM-226630_ref1","first-page":"110","article-title":"Design and implementation of project warehouse system based on low-code 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