Verification of the effects of layout changes in hotel dining venues using image analysis AI.
It has been implemented in a nationwide hotel chain, quantitatively analyzing the flow and congestion in dining venues, and is being used for effectiveness verification and operational improvements.
Features Visualization of movement lines and congestion situations By visualizing users' movement trajectories and dwell times as heat maps, it is possible to intuitively grasp areas of congestion and biases in movement lines. Comparison before and after using quantitative indicators Using stop rates, straight movement rates, and seating rates, differences before and after layout changes can be quantitatively compared, allowing for a clear evaluation of the presence and degree of improvement. Can be implemented using only camera footage There is no need for the installation of dedicated sensors, as analysis can be conducted based on footage from cameras installed within the venue, enabling low-cost verification that leverages the existing environment. Use Cases Verification of the effects of layout changes in dining venues Identification of congestion points and time periods Consideration of improvements in serving stations and furniture arrangements Comparative analysis before and after renovations or renewals Decision-making on layout deployment to other facilities By utilizing quantitative data from video analysis AI, we support operational improvements and management decisions that do not rely on subjective evaluations.
- 企業：ファントム
- 価格：Other
