通過智慧團體餐飲獲取飲食數據的成本（CS Society）
- 2020 年 1 月 3 日
- 筆記
隨著公眾對食物攝入的認識，對飲食數據管理的需求正在增長。 結果，越來越多的智慧食堂部署通過基於射頻識別（RFID）或基於電腦視覺（CV）的解決方案來收集飲食數據。 由於這兩種情況都涉及人工，因此人力分配對於數據品質至關重要。 在人力需求被低估的地方，數據品質會受到損害。 本文利用基於從多個智慧食堂收集的真實數據的數值模擬，研究了膳食數據品質與投入人力之間的關係。 我們發現，在基於RFID和CV的系統中，飲食數據獲取的長期成本都由人力決定。 我們的研究為飲食數據獲取的成本構成提供了全面的了解，並對未來具有成本效益的系統提供了有用的見解。
原文題目：Cost of Dietary Data Acquisition with Smart Group Catering
原文：The need for dietary data management is growing with public awareness of food intakes. As a result, there are increasing deployments of smart canteens where dietary data is collected through either Radio Frequency Identification (RFID) or Computer Vision(CV)-based solutions. As human labor is involved in both cases, manpower allocation is critical to data quality. Where manpower requirements are underestimated, data quality is compromised. This paper has studied the relation between the quality of dietary data and the manpower invested, using numerical simulations based on real data collected from multiple smart canteens. We found that in both RFID and CV-based systems, the long-term cost of dietary data acquisition is dominated by manpower. Our study provides a comprehensive understanding of the cost composition for dietary data acquisition and useful insights toward future cost effective systems.
原文作者：Jiapeng Dong,Pengju Wang,Weiqiang Sun
原文地址：https://arxiv.org/abs/2001.00367
