Supply and demand management is integrated into supply chain management and throughout the many members and channels of the supply chain. There is an increasing demand for highly efficient supply chains and logistics systems, especially pertaining to the needs of the smart cities of today. Moreover, supply chain systems are far more complex for these modern smart cities as there is a huge supply and demand for appropriate and optimized logistics and many parameters and factors that these data-driven cities can provide for model training. Supply chain management systems can be enhanced to a greater extent by utilizing modern-day smart city parameters. The proposed work highlights the role of AI in supply chain management and the importance of data-driven solutions for smart cities. A deep learning mechanism has been introduced to make predictions related to supply chain management considering the conventional datasets with smart parameters. The model has then been used to predict various output features as a part of the entire decision system.
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