Abstract

Purpose: The Internet of Things (IoT) has changed how we interact with technology, allowing us to control and monitor devices remotely from our smartphones or other devices. One of the most popular ways of interacting with IoT devices is through voice assistants like Amazon Alexa. To integrate an IoT device with Alexa, developers must create a custom Alexa skill to understand voice commands and communicate with the IoT device. This research paper presents a practical guide for developers interested in creating custom Alexa skills for their IoT devices. It covers the essential steps in setting up the AWS IoT platform, designing the Alexa skill's interaction model, and testing the Skill. Design/Methodology/Approach: We decided which load or equipment would be operated using the Alexa voice command. Then we thought about quickly consuming minimal words for each device operation. We prepared the command list in the Excel sheet and a command prototype for Alexa utterances. We created an AWS account in the AWS cloud server and started to create the new Skill. Finally, we must add the AWS lambda function ARN to the Alexa default Endpoint to update the IoT Device shadow for connected devices. Findings/Result: This research demonstrates that the development of an Alexa skill for IoT devices in the AWS Cloud is a reliable, efficient, and flexible approach that has the potential to revolutionize the way we interact with IoT devices in our daily lives. Originality/value: The novelty of this research lies in the fact that it provides a step-by-step guide to developing an Alexa skill for IoT devices in the AWS Cloud. It will also help researchers and developers understand the complexities of developing Alexa skills for IoT devices in the AWS Cloud and how these skills can be used to control IoT devices anywhere. This research will add value to the field by providing developers with the necessary tools and techniques to develop sophisticated and reliable Alexa skills for IoT devices in the AWS Cloud. Paper Type: Experimental-based Research.

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