Indoor navigation with dynamic tracking guidance using low-cost wearable devices and beacon technologies

Abstract

With today’s advancing technology, the amount of people making use of navigation devices has increased. Many different systems exist for outdoor navigation but the same cannot be said for indoors. While past research has proposed viable indoor navigation technologies, improvements in accuracy and response time would make the technology more attractive. This research proposes a novel technology for both indoor location as well as user friendly navigation built on cheap IoT which can help users navigate through a building with the use of voice prompts. Users are given simple instructions to get their respective position to their desired destination in a confident manner. The first step of the proposed technology is accurate indoor location detection. This is detected based on how far away the user is from the beacon devices strategically distributed in the area. A limit is set to ignore beacons which have a low signal strength to keep as high of an accuracy as possible. A map of the building is developed using the provided web interface on which indoor navigation and obstacle avoidance is performed. Low latency indoor location technology, based on Wireless Ethernet beacon signals, is proposed. The beacon technology allows the indoor location mechanism to have a very low latency, configurable down to well under 1 second. The microcontroller found on the wearable device receives packets from beacon devices, which are used to calculate the user’s position and then devises the route based on the onboard location map. The map of the building is split into a grid form with smaller subregions, which can be configured by making use of a web-based interface, depicting important environment locations such as doors, stairs, lifts and obstacle, using an easy-to-read colour map. For the course of this study, a prototype implementation of the proposed technology has been built using off the shelf ESP32 devices programmed in C++ using the Arduino IDE. The prototype was evaluated in terms of its Indoor location accuracy (resulting in 1.2m), navigation algorithm efficiency (always found to give the shortest route in under 1 second), and user experience (overall satisfactory for a prototype).