TY - GEN
T1 - Using Middleware and Digital Twin to Enable Agronomic Produce Tracking on Mobile Devices Supporting Consumers to Know When Produce Will Get to the Store
AU - Lomotey, Richard
AU - Kumi, Sandra
AU - Deters, Ralph
AU - Hilton, Maxwell
AU - Snow, Charlie
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/12/11
Y1 - 2023/12/11
N2 - It is always uncertain to know when your favorite farm produce will be arriving on the shelves when you cannot find one at the grocery store. Most consumers simply return home and come back to the grocery store at a future date/time in anticipation that they will find the produce. However, there is no guarantee that on their return, the produce will have arrived in the store or be available on the shelves. These events can lead to disappointments, wasted travel time and effort, and cost. The goal of this paper is to enable farm produce consumers to track the location, distribution, and time when their produce will be arriving at the grocery store via a mobile application. However, there are challenges to address such as not disclosing the actual location of drivers/distributors to the public due to safety and privacy concerns. Thus, we adopted digital twin (i.e., virtual replicas of the actual location data) techniques to enhance data confidentiality. The mobile application is a distributed architecture with a cloud-based middleware server and a database. The preliminary testing of the work shows that consumers are happy with the mobile application, and the system evaluation also confirms the feasibility of deploying such a mobile product.
AB - It is always uncertain to know when your favorite farm produce will be arriving on the shelves when you cannot find one at the grocery store. Most consumers simply return home and come back to the grocery store at a future date/time in anticipation that they will find the produce. However, there is no guarantee that on their return, the produce will have arrived in the store or be available on the shelves. These events can lead to disappointments, wasted travel time and effort, and cost. The goal of this paper is to enable farm produce consumers to track the location, distribution, and time when their produce will be arriving at the grocery store via a mobile application. However, there are challenges to address such as not disclosing the actual location of drivers/distributors to the public due to safety and privacy concerns. Thus, we adopted digital twin (i.e., virtual replicas of the actual location data) techniques to enhance data confidentiality. The mobile application is a distributed architecture with a cloud-based middleware server and a database. The preliminary testing of the work shows that consumers are happy with the mobile application, and the system evaluation also confirms the feasibility of deploying such a mobile product.
UR - https://www.scopus.com/pages/publications/85181817790
UR - https://www.scopus.com/pages/publications/85181817790#tab=citedBy
U2 - 10.1145/3631319.3632301
DO - 10.1145/3631319.3632301
M3 - Conference contribution
AN - SCOPUS:85181817790
T3 - Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of: MIDDLEWARE 2023
SP - 7
EP - 12
BT - Midd4DT 2023 - Proceedings of the 1st International Workshop on Middleware for Digital Twin, Part of
PB - Association for Computing Machinery, Inc
T2 - 1st International Workshop on Middleware for Digital Twin, Midd4DT 2023
Y2 - 11 December 2023 through 15 December 2023
ER -