# Federated Learning for Clients' Data Privacy Assurance in Food Service Industry
## 6 Conclusions  
This study presents a federated learning model for identifying and segmenting organic-based contamination and biofilms on various surfaces. We captured video frames using a fluorescence-imaging technology developed by SafetySpect Inc. and used two state-of-the-art deep learning algorithms, MobileNetV3 and DeepLabv3+, for classification and semantic segmentation. FL allows a model to be trained without transferring client datasets to a central server, helping to address client data privacy and confidentiality concerns. In this study, we used FedML, with some modifications, as our FL framework and FedAvg as the aggregation algorithm. We collected data from 10 institutional kithens and restaurants. We trained and validated the model on eight clients, including 35,858 _clean_ and 36,523 _contamination_ frames, and tested it on two clients (_clean_: 8327, _contamination_: 10,359). For differentiation between _clean_ and _contamination_ frames, the model achieved respective accuracies of 95.84% and 94.92% for clients 9 and 10. The FL-based semantic segmentation model was trained and validated on 12,000 annotated contamination frames from eight clients and tested on 5859 (3770 and 2089) annotated frames from two new clients. The model resulted in a mean IoU score of 91.23% for client 9 and 89.45% for client 10. The results demonstrated that using new fluorescence imaging technology combined with FL-based deep learning models can not only improve the performance of cleanliness and safety auditing systems for food preparation facilities but also can improve data privacy assurance for clients in the food-service industry. Conceptualization, H.T.G., N.M., M.S.K., F.V., A.A. and K.T. ; methodology, H.T.G., M.S., E.M., F.V., A.A., S.A. and K.T. ; validation, M.S.K., F.V., A.A., J.Q. and K.T. ; formal analysis, H.T.G. and E.M.; investigation, N.M., F.V., S.A., K.T. and M.S.K. ; resources, M.S.K., D.E.C. and J.Q. ; data collection, and curation, H.T.G., H.K.Z. and S.S.; writing--original draft preparation, H.T.G., M.S. and K.H. ; writing--review and editing, N.M., H.T.G., D.E.C., F.V., S.A., K.T., J.Q., A.A. and I.B. ; visualization, S.M.S. and H.T.G. ; supervision, K.T., N.M., F.V., M.S.K. and I.B. ; project administration, F.V. and K.T. ; funding acquisition, N.M., F.V. and K.T. All authors have read and agreed to the published version of the manuscript. This research was partially funded by the United States Department of Agriculture's National Institute of Food and Agriculture (Grant number 2020-33610-32479) and by the North Dakota Department of Agriculture (grant number 20-340) and by the Bioscience Innovation Grant Program (BIG) (grant number 21-282). Not applicable. The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. The authors would like to thank [PERSON] of the North Dakota Bioscience Association, and [PERSON] of ComDel Innovation, Wahpeton, ND, for their advice and support. The author would also like to thank [PERSON], [PERSON], and [PERSON] for their support and guidance and for providing access to Edgewood long-term care facilities. The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. The authors would like to thank [PERSON] of the North Dakota Bioscience Association, and [PERSON] of ComDel Innovation, Wahpeton, ND, for their advice and support. The author would also like to thank [PERSON], [PERSON], and [PERSON] for their support and guidance and for providing access to Edgewood long-term care facilities. The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. The authors would like to thank [PERSON] of the North Dakota Bioscience Association, and [PERSON] of ComDel Innovation, Wahpeton, ND, for their advice and support. The author would also like to thank [PERSON], [PERSON], and [PERSON] for their support and guidance and for providing access to Edgewood long-term care facilities.