摘要
由一名新闻记者兼机器人与机器学习每日新闻的工作人员新闻编辑根据来自华盛顿特区的新闻报道来源，由NewsRx记者提出的专利申请由Neve Ntors Ahmed，Nabeel（加利福尼亚州圣何塞）；Kim，Sophia Hyein（加利福尼亚州桑尼维尔，美国）于2022年9月8日被释放，2024年5月30日在线提供。本专利申请没有受让人。记者们从发明人提供的背景资料中获得了以下引述：“传统的食物消费是由一个人监控的，他们独立地跟踪和记录他们吃了什么，吃了多少，什么时候吃，日志可以是手写的，也可以输入到一个应用程序中，该应用程序只提供输入食物的分量和种类的卡路里估计值。这两种情况的准确性在很大程度上取决于人们跟踪所摄入食物的勤奋程度。因此，对于那些没有时间/精力准确跟踪所消费食物的人来说，传统系统的效用会下降。此外，即使一个人准确跟踪所消费食物，传统系统也不能主动监控，例如，用户是否窒息和/或用户是否在吃饭困难(例如，很难拿起食物等)。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting originatin g from Washington, D.C., by NewsRx journalists, a patent application by the inve ntors Ahmed, Nabeel (San Jose, CA, US); Kim, Sophia Hyein (Sunnyvale, CA, US), f iled on September 8, 2022, was made available online on May 30, 2024. No assignee for this patent application has been made. Reporters obtained the following quote from the background information supplied by the inventors: "Conventionally food consumption is monitored by a person indi vidually tracking and logging what they eat, how much they eat, when they eat, e tc. The log may be hand written or input into an application that simply provide s calorie estimates for the portions and types of foods input. Accuracy of both instances rely heavily on how diligent the person is in tracking what food was c onsumed. As such, utility of conventional systems goes down for people who do no t have the time/dedication to accurately track what food was consumed. Moreover, even if a person accurately tracks what food was consumed, conventional systems are not able to actively monitor, e.g., whether a user is choking and/or whethe r a user is having a hard time eating (e.g., having a hard time picking up their food, etc.)."
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