Rectification of RSSI Value using Signal Filters in an Outdoor Environment

Currently, emplacement information is a critical technology that is used by many services. Given that nowadays, Received Signal Strength Indicator (RSSI)-based localization processes using Wi-Fi are less expensive and easier to implement, and research is being conducted in this field to optimize and improve localization techniques depending on when and where it is used, as well as which service it is used for. However, this approach has the disadvantage of picking up many types of interference, which reduces signal quality when sent in a contained environment with multiple devices or sensors. This is where filters come into play, allowing it to filter the received signals to produce a more optimal signal, which in turn improves the accuracy of localization techniques and other services. The motivation for the entire study is to evaluate some of the common filters that are used for filtering out noise in the signal and using the resulting data to rectify which filter produces a better signal that helps to understand which of the four filters employed here performs better in an indoor environment in the proposed scenario.