Artificial Intelligence Based Store Management
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Abstract
The project proposes innovative ideas such as personalized customer interactions through a mobile application and optimizing queues through the sliding checkout model. It also leverages existing kiosks for digital customer connections. The project's methodology is based on comprehensive needs analysis, consultations with industry experts, and the identification of processes suitable for automation. It also prioritizes Research and Development (R&D) in retail merchandising by securing R&D licenses from industry giants.
The project's technological infrastructure is designed for the Azure cloud environment, ensuring operational efficiency and seamless integration with various systems. A robust logging infrastructure is in place to maintain an uninterrupted connection between artificial intelligence support and the backend architecture. The project also develops a mobile application with user-friendly interfaces and cross-platform functionality using Flutter.
The anticipated benefits of the project include time savings for store managers, data-driven decision-making, and experimental positioning for testing and implementing novel methods in store operation. Overall, the "Artificial Intelligence Based Store Management" project aims to set new industry standards by integrating artificial intelligence and machine learning into retail merchandising.
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