International Journal of Intelligent Systems and Applications (IJISA)
IJISA Vol. 11, No. 11, 8 Nov. 2019
Cover page and Table of Contents: PDF (size: 572KB)
Smart Warehouse Management using Hybrid Architecture of Neural Network with Barcode Reader 1D / 2D Vision Technology
Full Text (PDF, 572KB), PP.16-24
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Author(s)
Mbida Mohamed
1,*
Index Terms
Neural, network, smart, wharehouse, hybride, management
Abstract
Manually, to manage stocks amounts spending the every day in the rays to count for each product the number which it remains in stores, or to record by a scanner head barcode information dependent of each product. However, the mission become increasingly difficult if several warehouses are found, that involves much time to pass from a product to another, moreover that requires agents to carry out these spots. In this article we use a network architecture neuron combined with the readers bar code of technology vision, this method allows to know in real time information concerning each product in stock. It will allow besides introducing the concept of real stocks rather than physical. However The basic classical use of data and to feed it will be completely changed by the spheres of knowledge which generates the NN (Neural Network) to store information on the quantity at a given time (Dynamic inventory), the entries(delivery of suppliers ) and the outputs ( delivery or sale with the customers and use of manufacturing pieces or repair ).
Cite This Paper
Mbida Mohamed, "Smart Warehouse Management using Hybrid Architecture of Neural Network with Barcode Reader 1D / 2D Vision Technology", International Journal of Intelligent Systems and Applications(IJISA), Vol.11, No.11, pp.16-24, 2019. DOI:10.5815/ijisa.2019.11.02
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