{"title":"利用雾计算设计服装工人自动推荐工作场所系统","authors":"Arunavo Dey, Md Nahid Newaz","doi":"10.1109/ICASERT.2019.8934631","DOIUrl":null,"url":null,"abstract":"Garments industry is one of the biggest industries of Bangladesh and a large portion of our population comprises of garments workers who face several problems starting from health and financial problems, discrimination, safety issues and lack of skill development opportunities – which make them more vulnerable and obstruct them from finding a better tomorrow. A country can’t march forward with a large portion of it leaving behind and thus we target to improve their conditions by designing an intervention which propels to achieve the target by maintaining a predictive model which predicts on the data collected from the users. It suggests the users who are garment workers, about the available and better opportunities for workspace in the easiest way.","PeriodicalId":6613,"journal":{"name":"2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT)","volume":"29 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Designing an automatic workplace recommendation system for garment workers using fog computing\",\"authors\":\"Arunavo Dey, Md Nahid Newaz\",\"doi\":\"10.1109/ICASERT.2019.8934631\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Garments industry is one of the biggest industries of Bangladesh and a large portion of our population comprises of garments workers who face several problems starting from health and financial problems, discrimination, safety issues and lack of skill development opportunities – which make them more vulnerable and obstruct them from finding a better tomorrow. A country can’t march forward with a large portion of it leaving behind and thus we target to improve their conditions by designing an intervention which propels to achieve the target by maintaining a predictive model which predicts on the data collected from the users. It suggests the users who are garment workers, about the available and better opportunities for workspace in the easiest way.\",\"PeriodicalId\":6613,\"journal\":{\"name\":\"2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT)\",\"volume\":\"29 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASERT.2019.8934631\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASERT.2019.8934631","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Designing an automatic workplace recommendation system for garment workers using fog computing
Garments industry is one of the biggest industries of Bangladesh and a large portion of our population comprises of garments workers who face several problems starting from health and financial problems, discrimination, safety issues and lack of skill development opportunities – which make them more vulnerable and obstruct them from finding a better tomorrow. A country can’t march forward with a large portion of it leaving behind and thus we target to improve their conditions by designing an intervention which propels to achieve the target by maintaining a predictive model which predicts on the data collected from the users. It suggests the users who are garment workers, about the available and better opportunities for workspace in the easiest way.