Bluetooth-Tracing RSSI Sampling Method as Basic Technology of Indoor Localization for Smart Homes

Abstract

In recent years, smart homes have become the center of interest for IT companies and construction companies and various types of smart homes have been made currently available on the market. Yet, these equipment are costly and it is not easy to convert existing equipment for smart home application as they may require additional resources which could also inflict much costs. The extra costs involving the remodeling of existing housing structure and installment of new equipments can be avoided by using advanced wireless technologies. As an example, this paper proposes an indoor localization system that adopts Bluetooth technology and uses RSSI values for localization. Researchers have configured a system where the central control device will recognize all other devices or equipments in the system, communicate with each other, and respond to the commands or the information provided. However, despite the efforts of many researchers, existing RSSI-based indoor localization systems do not show a satisfactory level of accuracy such that we have devised a system that traces the trend in the RSSI samples. The RSSI sampling algorithm uses Delta values obtained from the Delta sampling process to improve system accuracy and to lower the costs. The analysis results led us to believe that our algorithm has a reduced localization error rate by 12%-point compared to the algorithm that used raw sampling method.