Πλοήγηση ανά Συγγραφέας "Savvas, Charilaos"

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  • Μικρογραφία εικόνας
    Τεκμήριο
    WiFi-based indoor positioning.
    (ΕΛ.ΜΕ.ΠΑ., Σχολή Μηχανικών (ΣΜΗΧ), ΠΜΣ Πληροφορική και Πολυμέσα, 2024-01-23) Savvas, Charilaos; Σάββας, Χαρίλαος
    In this dissertation, the primary focus is the development of an indoor positioning system predicated on WiFi technology, harnessing both Round Trip Time (RTT) and Received Signal Strength Indication (RSSI) methodologies. RTT serves as a mechanism to quantify the duration required for WiFi signals to traverse between a specific device and its corresponding access point, thus facilitating the extrapolation of the distance between any Wireless Local Area Network (WLAN) device and said access point. Conversely, RSSI operates on the premise of ascertaining the triangulated coordinates of a designated target, achieved by a meticulous analysis of signal amplitude at diverse receiver locales. Within the framework of this research endeavor, an ESP32 microcontroller has been employed as the pivotal access point, purposed to approximate the spatial positioning of any WiFi-integrated device within a delineated architectural space or chamber. We use the ping method to collect RTT and RSSI values of different APs in this project. We gather different RTT values from different esp32 microcontroller access points placed in the building and use them to locate the position for our device. Similarly, we gather RSSI values from different locations’ access points, and compare them to get more accurate and closer to real values results. Then we compare the final values of both RSSI and RTT to the original positioning value to evaluate which method is more accurate for indoor positioning. This thesis can be useful for object tracing or object detection projects using WLAN network. For example, we can use it to locate our laptop or smartphone inside our house or office, or to detect any unauthorized devices in a restricted area. The main findings of this thesis are that RTT method is more accurate than RSSI method for indoor positioning, and that combining both methods can improve accuracy even further. We also discuss the limitations and challenges of this project, such as the interference of other Wi-Fi signals and the calibration of different devices.