一个基于社区的移动应用程序,利用社交媒体减少未使用自行车的浪费

IF 1.7 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal Pub Date : 2023-04-29 DOI:10.5121/csit.2023.130707
{"title":"一个基于社区的移动应用程序,利用社交媒体减少未使用自行车的浪费","authors":"","doi":"10.5121/csit.2023.130707","DOIUrl":null,"url":null,"abstract":"Around 15 million bikes are discarded annually, which poses an environmental risk [1]. The rubber from bike tires takes a long time to decompose, and toxic chemicals are released into the soil during this process [2]. Additionally, the popularity of e-bikes is increasing, and the lithium batteries they use harm the environment during extraction. To address this problem, a bike donation app is proposed, which reduces the number of bikes produced, minimizes waste, and benefits those in need [3]. By operating online, the cost of running the operation is minimal, and the project can reach and help anyone with internet access. However, the app's success relies on a user base, which may be a significant challenge. Furthermore, the app's design may need improvement to attract users. Blind spots in the program may include inaccurate bike donation recommendations and a lack of proper verification for donated bikes' safety and condition. An A/B test shows that personalized recommendations through the app increased the conversion rate for successful bike donations. The verification process for donated bikes was effective in ensuring the bikes' safety and quality. By developing a mobile app that provides personalized recommendations and addresses bike waste, the project contributes to sustainable transportation and reduces environmental harm [4].","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"85 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Community-Based Mobile Application to Reduce Waste from Un-used Bikes Using Social Media\",\"authors\":\"\",\"doi\":\"10.5121/csit.2023.130707\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Around 15 million bikes are discarded annually, which poses an environmental risk [1]. The rubber from bike tires takes a long time to decompose, and toxic chemicals are released into the soil during this process [2]. Additionally, the popularity of e-bikes is increasing, and the lithium batteries they use harm the environment during extraction. To address this problem, a bike donation app is proposed, which reduces the number of bikes produced, minimizes waste, and benefits those in need [3]. By operating online, the cost of running the operation is minimal, and the project can reach and help anyone with internet access. However, the app's success relies on a user base, which may be a significant challenge. Furthermore, the app's design may need improvement to attract users. Blind spots in the program may include inaccurate bike donation recommendations and a lack of proper verification for donated bikes' safety and condition. An A/B test shows that personalized recommendations through the app increased the conversion rate for successful bike donations. The verification process for donated bikes was effective in ensuring the bikes' safety and quality. By developing a mobile app that provides personalized recommendations and addresses bike waste, the project contributes to sustainable transportation and reduces environmental harm [4].\",\"PeriodicalId\":42597,\"journal\":{\"name\":\"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal\",\"volume\":\"85 1\",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-04-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/csit.2023.130707\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/csit.2023.130707","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

摘要

每年大约有1500万辆自行车被丢弃,这构成了环境风险[1]。自行车轮胎的橡胶需要很长时间才能分解,在这个过程中,有毒化学物质会释放到土壤中[2]。此外,电动自行车越来越受欢迎,它们使用的锂电池在提取过程中会损害环境。为了解决这一问题,我们提出了一款自行车捐赠app,它可以减少自行车的生产数量,最大限度地减少浪费,并使有需要的人受益[3]。通过在线运营,运营成本最低,该项目可以触及并帮助任何有互联网接入的人。然而,这款应用的成功依赖于用户基础,这可能是一个重大挑战。此外,应用程序的设计可能需要改进以吸引用户。该计划的盲点可能包括不准确的自行车捐赠建议,以及对捐赠自行车的安全性和状况缺乏适当的验证。A/B测试表明,通过该应用程序的个性化推荐提高了成功捐赠自行车的转化率。捐赠自行车的验证过程有效地确保了自行车的安全和质量。通过开发一款提供个性化建议并解决自行车浪费的移动应用程序,该项目为可持续交通和减少环境危害做出了贡献[4]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A Community-Based Mobile Application to Reduce Waste from Un-used Bikes Using Social Media
Around 15 million bikes are discarded annually, which poses an environmental risk [1]. The rubber from bike tires takes a long time to decompose, and toxic chemicals are released into the soil during this process [2]. Additionally, the popularity of e-bikes is increasing, and the lithium batteries they use harm the environment during extraction. To address this problem, a bike donation app is proposed, which reduces the number of bikes produced, minimizes waste, and benefits those in need [3]. By operating online, the cost of running the operation is minimal, and the project can reach and help anyone with internet access. However, the app's success relies on a user base, which may be a significant challenge. Furthermore, the app's design may need improvement to attract users. Blind spots in the program may include inaccurate bike donation recommendations and a lack of proper verification for donated bikes' safety and condition. An A/B test shows that personalized recommendations through the app increased the conversion rate for successful bike donations. The verification process for donated bikes was effective in ensuring the bikes' safety and quality. By developing a mobile app that provides personalized recommendations and addresses bike waste, the project contributes to sustainable transportation and reduces environmental harm [4].
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
1.40
自引率
0.00%
发文量
22
审稿时长
4 weeks
期刊最新文献
Enhancing Energy Efficiency in Cluster Based WSN using Grey Wolf Optimization Comparison of Pre-trained vs Custom-trained Word Embedding Models for Word Sense Disambiguation Healthcare Data Collection Using Internet of Things and Blockchain Based Decentralized Data Storage Development of an Extended Medical Diagnostic System for Typhoid and Malaria Fever Comparison of Swarm-based Metaheuristic and Gradient Descent-based Algorithms in Artificial Neural Network Training
×
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