Optimizing warehouse management system with blockchainand machine learning predictive data analytics

Abstract

Blockchaintechnology  is  proving  to  be  a  disruptive  technology  in  many areas  of  supply  chain,  manufacturing,  medical,  agriculture,  and  so  on. Warehouses  are  an  inevitable  part  of  the  supply  chain.  Issues  like  space optimization,  route  optimization,  quick  item  pick-up,demand  forecasting, and  transaction  management  are  of  importance  to  address  in warehouse management systems (WMS). Traditional database systems have limitations of   interoperability   among   different   entities   involved   in   warehouses. This paper presents an innovative application of blockchaintechnology and machine  learning(ML)to  build  a smart  warehouse  management  system  in Web3 (SWMW3).  We  developed a  decentralized application (DApp) using Web3.0  principles,  integrating  ReactJS  for  the  frontend, express  for  the backend, and blockchainthrough smart contracts. This integration enhances security   and   transparency   by   storing   WMS   operational   data   in   the blockchainand   automating   payments   and   verifications   through   smart contracts. Additionally, we implemented a MLmodel for predicting the total time  from  order  receipt  to  delivery,  leveraging  historical  data  to  optimize workflow, reduce  delays, and  improve  overall  efficiency. This  combination of blockchainfor  secure  transactions  and MLfor  predictive  analytics generates  a  robust,  efficient,  and  optimized  management  system  for  the warehouse.