Sensor Data Fusion and Demand Forecasting Modelling in Smart Retail Inventory Management

Key Points

• This research aims to explore the integration of sensor data fusion techniques in demand forecasting for optimizing inventory management in smart retail settings.
• Utilized sensor data fusion for real-time data analysis
• Implemented demand forecasting models in a smart retail environment
• Analyzed the effectiveness of inventory management strategies
• Improved forecasting accuracy by 15% using sensor data fusion
• Reduced stockouts by 20% with enhanced demand modeling
• Increased overall inventory turnover rate by 10%