With the emergence of the Internet of People (IoP) and its user-centric applications, novel solutions to the many issues facing today’s societies are to be expected. These problems include unhealthy diets, with obesity and diet-related diseases reaching epidemic proportions. We argue that the proliferation of mixed reality (MR) headsets as next generation primary interfaces provides promising alternatives to contemporary digital solutions in the context of diet tracking and interventions. Concretely, we propose the use of MR headset-mounted cameras for computer vision (CV) based detection of diet-related activities and the consequential display of visual real-time interventions to support healthy food choices. We provide an integrative framework and results from a technical feasibility as well as an impact study conducted in a vending machine (VM) setting. We conclude that current neural networks already enable accurate food item detection in real-world environments. Moreover, our user study suggests that real-time interventions significantly improve beverage (reduction of sugar and energy intake) as well as food choices (reduction of saturated fat). We discuss the results, learnings, and limitations and provide an overview of further technology- and intervention-related avenues of research required by developing an MR-based user support system for healthy food choices.

随着人联网（IoP）及其以用户为中心的应用程序的出现，人们有望期待针对当今社会面临的许多问题的新颖解决方案。这些问题包括不健康的饮食，肥胖和与饮食有关的疾病已达到流行病的程度。我们认为，在饮食跟踪和干预的背景下，混合现实（MR）耳机作为下一代主要接口的普及为当代数字解决方案提供了有希望的替代方案。具体而言，我们建议使用MR头戴式摄像头进行基于计算机视觉（CV）的饮食相关活动的检测，并相应显示视觉实时干预措施，以支持健康食品的选择。我们提供了一个综合框架和技术可行性的结果以及在自动售货机（VM）设置中进行的影响研究。我们得出的结论是，当前的神经网络已经可以在实际环境中进行精确的食品检测。此外，我们的用户研究表明，实时干预可以显着改善饮料（减少糖和能量的摄入）以及食物的选择（减少饱和脂肪）。我们讨论了结果，学习和局限性，并概述了通过开发基于MR的健康食物选择用户支持系统所需的其他与技术和干预相关的研究途径。我们的用户研究表明，实时干预可以显着改善饮料（减少糖和能量的摄入）以及食物的选择（减少饱和脂肪）。我们讨论了结果，学习和局限性，并概述了通过开发基于MR的健康食物选择用户支持系统所需的其他与技术和干预相关的研究途径。我们的用户研究表明，实时干预可以显着改善饮料（减少糖和能量的摄入）以及食物的选择（减少饱和脂肪）。我们讨论了结果，学习和局限性，并概述了通过开发基于MR的健康食物选择用户支持系统所需的其他与技术和干预相关的研究途径。