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导航营养:对实时食品营养分类和推系统的范围审查

Asim Moin Saad¹, Md Manirul Islam¹

¹Department of Mechatronics Engineering, Rajshahi University of Engineering and Technology (RUET), Rajshahi, 6204, Bangladesh.

Computers in biology and medicine

|May 6, 2025

概括

实时食品营养系统使用机器学习和传感器等技术来分类和推食物. 需要进一步的研究来提高它们在促进忙碌个体更健康的饮食习惯方面的有效性.

科学领域:

营养科学营养科学
计算机科学计算机科学
公共卫生公共卫生

背景情况:

现代生活方式对保持健康的饮食习惯提出了挑战.
需要创新的解决方案来帮助个人做出明智的营养选择.
实时食品营养分类和推系统提供了一个有希望的方法.

研究的目的:

对实时食品营养推和分类系统进行全面的范围审查.
识别和评估技术方法,营养参数和应用.
了解这些系统的功能,有效性和公共卫生影响.

主要方法:

在Scopus,IEEE Xplore和PubMed数据库中的系统文献搜索.
包括过去十年的同行评审研究和会议记录.
从最初的166.6人中选择了36篇相关论文.

主要成果:

该评论综合了实时营养系统中的方法,趋势和挑战.
技术进步,包括机器学习和基于传感器的数据,至关重要.
目前的系统显示出潜力,但需要进一步研究以提高效率.

结论:

技术进步对于开发有效的实时营养系统至关重要.
需要进一步的研究来优化这些系统,以促进健康饮食.
这些系统为用户提供了多种途径,使他们能够做出明智的饮食决策.

关键词:

人工智能的人工智能是人工智能.卷积神经网络 (CNN) 是一种神经网络.深度学习是一种深度学习.机器学习是机器学习.基于营养的饮食建议个性化营养个性化营养

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