Implementing AI as Cyber IoT Devices: The House Valuation Example

Abstract

Internet of Things (IoT) has been widely utilized with artificial intelligence (AI). However, it requires substantial effort to integrate AI and big data with IoT. To mitigate this problem, AItalk was proposed. By treating AI as a cyber IoT device, we do not need to write code of the AI mechanism in the network applications, as traditional AI-based IoT applications did. This article describes how the AI tools such as scikit-learn and TensorLayer are accommodated as cyber IoT devices in AItalk, and extends AItalk for non-IoT applications. We use house valuation as an example to show how AItalk can flexibly include the factors that have significant impact on the house price. We show that by adding extra features other than housing profile features, the accuracy for the prediction (valuation) can be improved by 38 & x0025;. We also investigated the communication overhead of the distributed AItalk structure, which is 3.7 & x0025; for the computation of one house price valuation.