{"title":"Booming Blooming: When Can You Enjoy Flowering Season?","authors":"Yun-Chiao Cheng, Yan-Hung Chou, Chia-Yu Lin","doi":"10.1109/ICCE-Taiwan58799.2023.10226926","DOIUrl":null,"url":null,"abstract":"The blooming season is a crucial aspect of tourism in Taiwan, but it is subject to annual variations caused by weather factors such as rainfall and temperature. While many AI models are on the market for predicting flowering, they often need more applicability to specific regions due to climate variations. Moreover, Taiwan’s climate is known for being changeable, which can further complicate flower prediction. Using Taiwan’s climate and flowering date as training parameters, our model can achieve significantly higher accuracy than models that do not incorporate Taiwan’s climate information. This paper presents an App called \"Booming Blooming,\" which integrates a flower prediction model with real-time weather information. The App utilizes weather data from Taiwan’s Central Weather Bureau to predict the optimal time for flower viewing and provides users with up-to-date weather forecasts. With this App, users can plan their flower-viewing trips more effectively. Moreover, the App includes a built-in Google map to assist users in locating nearby stores, traffic conditions, and other people at popular flower-viewing locations. Additionally, Booming Blooming offers a flower-sharing platform where users can share the latest information on flower blooming conditions. Overall, the proposed flower blooming prediction model and App provide a convenient and efficient way for Taiwanese to enjoy flower-viewing activities.","PeriodicalId":112903,"journal":{"name":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE-Taiwan58799.2023.10226926","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The blooming season is a crucial aspect of tourism in Taiwan, but it is subject to annual variations caused by weather factors such as rainfall and temperature. While many AI models are on the market for predicting flowering, they often need more applicability to specific regions due to climate variations. Moreover, Taiwan’s climate is known for being changeable, which can further complicate flower prediction. Using Taiwan’s climate and flowering date as training parameters, our model can achieve significantly higher accuracy than models that do not incorporate Taiwan’s climate information. This paper presents an App called "Booming Blooming," which integrates a flower prediction model with real-time weather information. The App utilizes weather data from Taiwan’s Central Weather Bureau to predict the optimal time for flower viewing and provides users with up-to-date weather forecasts. With this App, users can plan their flower-viewing trips more effectively. Moreover, the App includes a built-in Google map to assist users in locating nearby stores, traffic conditions, and other people at popular flower-viewing locations. Additionally, Booming Blooming offers a flower-sharing platform where users can share the latest information on flower blooming conditions. Overall, the proposed flower blooming prediction model and App provide a convenient and efficient way for Taiwanese to enjoy flower-viewing activities.