To deploy the trained algorithm in the real world, a smart device app is required. MAI simplifies this task. The algorithm should be embedded in any type of apps. The deployment steps are shown in Figure 10. The deployment process consists of two main parts: client side and server side. The client side is the smart device app. This app should at least contain four different modules. The first module is the timer module which will record sensor reading over preconfigured periods. Moreover, the time stamp of sensor data harvesting has been utilized as a feature in different algorithms as was shown. The second module is sensor modules. What type of sensor data has been utilized in the training process should be harvested in this step. All sensors, except for the fingerprint sensor, are implemented in MAI. The third module is the data saving module. This module is required to reduce network usage, and any data processing modules required in the smart device app. MAI allows the programmer to save the app data in an internal unique database. The final step is data transmission over the Internet module. The HTTP protocol can be adopted for this step.
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