{"title":"iLid: IoT-Assisted Low-Cost and Scalabel Inventory-Management System","authors":"Chandra Shekhar, Rishikesh Vepura, Sudipta Saha","doi":"10.1109/ICORT52730.2021.9581806","DOIUrl":null,"url":null,"abstract":"Management of inventory is an extremely important issue in our day-to-day life. Starting from the kitchen, workshop, to retail stores everywhere, it is very essential to keep enough stock of each of the required items. However, manual management of the inventory often fails to maintain an up-to-date status of the stock of all the items all the time. Existing solutions based on RFID tags, weight-sensors-based automated measurements, etc. are not scalabel. A solution for smart-inventory management should support a plug-and-play installation and operation which is largely missing in the existing solutions too. Finally, appropriate coordination with the host systems such as smart-home or smart-retail management, etc. is also an important need which the existing solutions fail to achieve efficiently. In this work we propose the design of iLid, an IoT-assisted smart-inventory management system, to satisfy all these above mentioned needs in a cost-effective way. We take the help of low-power IoT-devices equipped with low-resolution cameras to realize an automated scalabel and cost-effective inventory management system. Automated measurement of the quantity of each individual item in the inventory as well as efficient collection of the measurement data are two fundamental components in iLid. In this paper, through extensive evaluation study we demonstrate that iLid can carry out quantity measurement efficiently with an average accuracy of 98%. Through simulation we also show that the data collection module of iLid is highly energy and time efficient as well as scalabel.","PeriodicalId":344816,"journal":{"name":"2021 2nd International Conference on Range Technology (ICORT)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 2nd International Conference on Range Technology (ICORT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICORT52730.2021.9581806","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
Management of inventory is an extremely important issue in our day-to-day life. Starting from the kitchen, workshop, to retail stores everywhere, it is very essential to keep enough stock of each of the required items. However, manual management of the inventory often fails to maintain an up-to-date status of the stock of all the items all the time. Existing solutions based on RFID tags, weight-sensors-based automated measurements, etc. are not scalabel. A solution for smart-inventory management should support a plug-and-play installation and operation which is largely missing in the existing solutions too. Finally, appropriate coordination with the host systems such as smart-home or smart-retail management, etc. is also an important need which the existing solutions fail to achieve efficiently. In this work we propose the design of iLid, an IoT-assisted smart-inventory management system, to satisfy all these above mentioned needs in a cost-effective way. We take the help of low-power IoT-devices equipped with low-resolution cameras to realize an automated scalabel and cost-effective inventory management system. Automated measurement of the quantity of each individual item in the inventory as well as efficient collection of the measurement data are two fundamental components in iLid. In this paper, through extensive evaluation study we demonstrate that iLid can carry out quantity measurement efficiently with an average accuracy of 98%. Through simulation we also show that the data collection module of iLid is highly energy and time efficient as well as scalabel.