Home automation and personalization through individual location determination

The focus of this project is to develop a prototype to demonstrate the utility of individualized location determination for home automation. While current home automation systems provide localization at a GPS level, they do not identify users' locations within a building. The smart home technology market is growing rapidly and this feature can differentiate a product line by adding unique capabilities for the consumer. The objective for this system is to use individualized location determination to improve lifestyle areas in the home in passive and non-intrusive ways. Being passive is important in that users should not have to take extra steps (e.g., pushing a button when they enter a room) as they move throughout their house. Being non-intrusive is important because users should not have to wear anything extra (e.g., a special armband) or have personal information scanned (e.g., facial recognition camera). The system will use Bluetooth Low Energy (BLE) to identify and track users' movements throughout a house, where the BLE signal of an individual will be associated with a smartphone or fitness wearable that they normally carry with them. A unique aspect of this project is the implementation of a flipped BLE architecture, which is implemented with a Texas Instruments development board that acts as a beacon to identify users based on their BLE signals from their smartphones and wearables. This architecture is “flipped” because most BLE beacons rely on a smartphone to “see” the beacons whereas the beacons in this system are “seeing” the smartphones. After identifying BLE devices in proximity to the beacon, the prototype system will record readings on the beacon locally, store data in an SQL database, and clean and process data through a PHP script. Different use cases for the BLE system within a house were considered. The final prototype will focus on a Smart Thermostat application which automatically adjusts where a thermostat reads the indoor temperature based on the location of the users. Results include a fully functioning prototype that can be used to demonstrate feasibility of the home automation use cases. Test results from the prototype include using a factorial experiment to measure the effect of distance and obstacles on the signal strength readings as well as performance on the system through a range of scenarios.