| 摘要(英) |
"Foot traffic" holds significant importance and application value across various fields. In production management, analyzing foot traffic helps assess production line efficiency, identify bottlenecks, optimize layouts, and enhance both productivity and quality. In marketing management, it is used to evaluate customer flow and consumer behavior, guide merchandise display and promotional strategies, thereby increasing sales and customer satisfaction. In human resources management, it aids in forecasting manpower needs, adjusting staff allocation, improving work environments, and boosting employee satisfaction and work efficiency. In financial management, foot traffic is used to evaluate the utilization of business hours, control costs, improve operational efficiency, and increase revenue. Overall, foot traffic has become a key tool for businesses to enhance production efficiency, marketing strategies, human resource allocation, and financial management, promoting sustainable development.
The staff cafeteria faces difficulties in managing ingredients, costs, and suppliers. The challenge of accurately predicting the demand for noodle and rice dishes can lead to either wastage of ingredients or insufficient supply, increasing costs. Real-time foot traffic data during meal pickup can indicate whether the current preparation is sufficient or if adjustments are needed to address potential stockpile and meal quality issues, impacting supplier relationships. A lack of real-time foot traffic counting also affects cooperation with suppliers, as it is difficult to accurately reflect demand, potentially leading to order errors and inventory management issues.
This study employs a CSI Camera to capture images, which are then processed in real time by a Jetson Orin Nano, combined with YOLOv8 for person detection and tracking. The results are then made available through a RESTful API via a web API method for other systems to access the foot traffic data, achieving efficient and real-time foot traffic counting.
The foot traffic counting system can satisfy the needs of the nutrition department in counting meal pickups. However, this study found that environmental control is necessary to achieve more accurate foot traffic counts. Due to the inadequacy of YOLOv8′s person detection and tracking for counting, I incorporated a baseline method to count foot traffic. Upon deployment, it was found that environmental control is necessary to achieve precise foot traffic counting. The numbers from the foot traffic counting system can also provide the hospital dashboard with current meal pickup counts, allowing nutrition department colleagues to use historical data to evaluate whether current dining numbers are reasonable, assess if the current food preparation is sufficient, and make necessary adjustments. In terms of dining cost expenditure, having the counts for noodle and rice dish pickups helps quickly identify if there are any anomalies in the costs of these specific categories, unlike in the past when only total data from fingerprint machines was available. |
| 參考文獻 |
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