Work place: Dept Mathematics& informatics Emerging Technologies Laboratory (LAVETE), Faculty of Sciences and Technology Hassan 1st University, Settat, Morocco
E-mail: mohamedmbida@gmail.com
Website:
Research Interests: Computer systems and computational processes, Information Security, Network Security, Information-Theoretic Security
Biography
Mbida Mohamed received his Phd degree in networks and Information Systems, from Hassan 1stUniversity, Faculty of Sciences and Technology of Settat, Morocco in 2017.
In 2012 and 2009 he received the B.Sc. degree in networks Information Systems and the M.Sc. degree in Network Computer engineering. Currently pursuing his research in Networks and Security Engineering, smart warehouse management and exploiting the sentimental bias between ratings and reviews with neural networks at the Laboratory of Emerging Technology (LAVETE), from Hassan 1st University, Faculty of Sciences and Technology of Settat, Morocco. His main research areas are how to use wireless sensor networks to secure and monitor mobile sensor networks, especially in Topology and Congestion of control. He is member of the National Smart Grid Committee Casablanca Morocco 2018.
DOI: https://doi.org/10.5815/ijisa.2019.11.02, Pub. Date: 8 Nov. 2019
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 ).
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