Design and Implementation for Indoor Navigation System Using LoRa

Abstract

Navigation system help users access unfamiliar environments. Current technological advancements enable users to encapsulate these systems in handheld devices, which effectively increases the popularity of navigation systems and the number of users. Internet of Things (IoT) is a new period of computing technology. Applications of IoT in different fields such as health, farming, industrial internet and so on. In indoor environments, lack of Global Positioning System (GPS) signals and line of sight makes navigation more challenging compared to outdoor environments. Indoor Positioning System (IPS) enable locating the position of objects or people within buildings. In this paper major aim is to design an indoor navigation design using LoRa technology. LoRa is a long-range, low power wireless technology platform. For indoor localization, many techniques are employed, among these techniques RSSI (Received Signal Strength Indicator) fingerprinting provides several favourable features for indoor environments. RSSI is one of the most widely used method as it is cost-effective and easily implemented. RSSI indicators from the different LoRa nodes are collected to create fingerprint database. LoRa network has been created using LoRa modules, Arduino Uno and LoRa receiver for creating localization system for indoor positioning. Nevertheless, RSSI performance is limited by indoor noise. K-nearest neighbor (KNN) filtering algorithm is an accurate filter algorithm that can enhance RSSI performance in indoors. KNN is one of the most popularly used algorithms for indoor positioning systems. Based on the RSSI indicators the users can locate the estimated position.