• C.Nayanatara
• P.Sharmila

Material recognition is the process of classifying materials into different categories based on the constituent material of the object under study. It is a very important problem in many fields and especially in the industrial field. In factories that use production lines to manufacture their products, one step is to separate materials and package different materials. A number of small and medium scale industries that cannot afford complete automation are utilizing manual methods of data collection and compilation for producing reports.Manual data process leaves room for both inconsistencies and inaccuracies. This leads to minor growth of such industries in the competitive market. Low cost automation using Inter of Things (IoT) is one solution especially for medium and small scale industries. The IoT based automatic data collection and processing system is the alternative to manual data handling. This paper presents the benefits of automated data collection and display system thatsaves money, time andincreases efficiency. It significantly improves the accuracy of the reports for the management. We utilized the advances in deep learning to water can product system, and we tested it on the Flicker Materials Database (FMD). The system is self-contained,economical and accurate that can be

Internet of Things, Low Cost Automation, Flicker Materials Database, Efficiency

"REAL TIME LOW COST AUTOMATED PRODUCTION SYSTEMUSING INTERNET of THINGS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.145-150, June 2019, Available :http://www.jetir.org/papers/JETIRDF06029.pdf

"REAL TIME LOW COST AUTOMATED PRODUCTION SYSTEMUSING INTERNET of THINGS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp145-150, June 2019, Available at : http://www.jetir.org/papers/JETIRDF06029.pdf