Food Temperature Analysis and Forecasting

Narayana Darapaneni, Nandan Garimella, Santhosh Vadlamani, Sulekha Dileep, S. Manchala, A. Paduri, Dinakar Komanduri, Prajwal Nagisetti
{"title":"Food Temperature Analysis and Forecasting","authors":"Narayana Darapaneni, Nandan Garimella, Santhosh Vadlamani, Sulekha Dileep, S. Manchala, A. Paduri, Dinakar Komanduri, Prajwal Nagisetti","doi":"10.1109/AIIoT52608.2021.9454182","DOIUrl":null,"url":null,"abstract":"Our work delves into the analysis of temperature time-series data, deployment of forecasting models, and their effectiveness in predicting food temperature based on historical data. The temperature of several food items recorded over a period of three months has been utilized for this purpose. Multiple Machine Learning models and their effectiveness in predicting food temperature have been analyzed. The results of these findings are discussed herein during the conclusion.","PeriodicalId":443405,"journal":{"name":"2021 IEEE World AI IoT Congress (AIIoT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE World AI IoT Congress (AIIoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIIoT52608.2021.9454182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Our work delves into the analysis of temperature time-series data, deployment of forecasting models, and their effectiveness in predicting food temperature based on historical data. The temperature of several food items recorded over a period of three months has been utilized for this purpose. Multiple Machine Learning models and their effectiveness in predicting food temperature have been analyzed. The results of these findings are discussed herein during the conclusion.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
食品温度分析与预测
我们的工作深入研究了温度时间序列数据的分析,预测模型的部署,以及它们在基于历史数据预测食品温度方面的有效性。为此目的利用了在三个月内记录的几种食物的温度。分析了多种机器学习模型及其在预测食物温度方面的有效性。本文在结论部分讨论了这些发现的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
CR-LPWAN: issues, solutions and research directions Automatic Detection of Vehicle Congestion by Using Roadside Unit Improved Noise Filtering Technique For Wake Detection In SAR Image Under Rough Sea Condition First Enriched Legal Database in Bangladesh with Efficient Search Optimization and Data Visualization for Law Students and Lawyers Differentially-Private Federated Learning with Long-Term Budget Constraints Using Online Lagrangian Descent
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1