The spaces we live in go through many transformations over the course of a year, a month, or a day; My room has seen tremendous clutter and pristine order within the span of a few hours. My goal is to discover patterns within my space and formulate an understanding of the changes that occur. This insight will provide actionable direction for maintaining a cleaner environment, as well as provide some information about the optimal times for productivity and energy preservation.
Using a Raspberry Pi, I will set up automated image capture in a room in my home. These images will automatically be sent to Google's Vision AI to be analyzed using their pre-trained models for detecting visually defined insights, such as clutter, messiness, and target objects (cups, electric technology, etc) from the images. Data from the visual analysis will be formatted for and sent to the Google BigQuery cloud database.
The aim of this project is to design and develop an automated pipeline for the streaming of spatial data from an Internet of Things (IoT) device to the Google Cloud Platform for analysis and storage and to determine whether this data could be used to identify a messy room.