Using Middleware and Digital Twin to Enable Agronomic Produce Tracking on Mobile Devices.

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.