Towards A Systematic Literature Review for Evaluating Smart Home Environments using light bulb sensors

As more homes become digitally connected the use of assistive technologies to support the operation in the home environment especially when one thinks of the elderly and the sick, our research shows that there is a gap in the literature with respect to the measure of the effectiveness of the use of these assistive technologies to support the home as a smart home. We conduct quantitative usability experiments supported by a conceptual human interaction framework to assess this effectiveness. We conduct as proof of concept these experiments with the use of a Google mini automated assistant and an internet ready light bulb sensor, to determine the responsiveness to the human voice, at different location proximities around the home, and the correctness to these responses to qualify the effectiveness argument. In this study the authors use their primary residence amidst the COVID19 pandemic to demonstrate the type of concerns. Our explicit contributions in this study are (i) A systematic review of the literature in this area (ii) the design of the smart home network environment with the google mini assistant and light ulb sensor that supports the human voice interactions (iii) Identify a suitable conceptual human interaction framework to support the use of the smart devices connected within the home users environment to support our experiments (iv) Provide critical case evaluation of the measure of effectiveness of the usability experiments supported by this conceptual framework.