Intelligent Decision-making Algorithm for IoT Enabled Smart shopping

In today’s fast-changing retail industry, IoT and data-driven analytics have changed consumer buying and business operations. In IoT-enabled smart shopping environments, intelligent decision-making algorithms are crucial. This paper presents an intelligent decision-making system for IoT-enabled smart purchasing. The program improves various shopping aspects using real-time data from IoT sensors, RFID tags, and cameras. The algorithm includes data integration, advanced analytics, decision optimization, real-time adaptation, and customization. The programme provides actionable information from customer behaviour, product inventories, and environmental elements to aid decision-making. These choices include inventory management, pricing, product recommendations, and targeted promotions to enhance the shopping experience. The real-time algorithm adapts to demand, inventory, and client preferences. Personalized recommendations and promotions boost retailer revenue and consumer engagement. The algorithm streamlines inventory management, improving efficiency, cost, and retail competitiveness.