Abstract: Indoor localization remains a challenging problem, as conventional GPS technologies often fail in enclosed spaces due to signal attenuation, multipath effects, and signal blockage caused by walls and other obstacles. This limitation poses significant hurdles in locations such as factories, hospitals, and warehouses, where accurate indoor tracking is essential. Overcoming these barriers is crucial for the advancement of numerous applications that depend on precise positioning, such as autonomous robotics, asset tracking, and navigation assistance within large facilities. In this project, we implement our solution within a controlled indoor lab setup that replicates real-world use cases, ensuring practical validation of our methodology.This research addresses these challenges by introducing a novel, cost-effective indoor positioning system (IPS) designed specifically for environments where traditional GPS cannot deliver reliable or accurate localization. The proposed IPS utilizes an array of ultrasonic sensors (HC-SR04) in conjunction with Time-of-Flight (ToF) measurements to calculate short-range distances with centimeter-level precision. The core system is built around an Arduino Mega microcontroller, which orchestrates real-time data acquisition and processing. The system architecture includes multiple anchor nodes and a mobile tag, coordinated to triangulate the tag’s position accurately. The integration of these off-the-shelf components ensures that the system remains scalable and affordable, making it accessible for widespread deployment in settings such as warehouses, hospitals, and smart buildings. Synchronization protocols and data filtering techniques are implemented to minimize measurement noise and environmental interferences, thereby enhancing the robustness and accuracy of position estimates.A Python-based visualization interface complements the hardware setup by providing a user-friendly platform for monitoring and managing localization data in real-time. Central to the software is a Python-implemented can , which calculates the two-dimensional position of the mobile node based on the distance measurements from multiple fixed anchor nodes. This algorithm processes the ToF data to derive accurate spatial coordinates, enabling real-time tracking of mobile agents. The novelty of our work lies in combining low-cost ultrasonic modules with custom-built synchronization, filtering mechanisms, and algorithmic positioning, achieving high precision without expensive hardware or complex infrastructure. The seamless coupling between hardware sensing and software visualization establishes the system as a practical and efficient solution for indoor navigation, offering a flexible foundation for further research and application development in the burgeoning field of smart environments.
Keywords: Indoor Positioning System (IPS), Ultrasonic Sensors, Time-of-Flight (ToF), Arduino Mega, Real-time Localization, Robotics, Automation, Smart Buildings, Asset Tracking, Trilateration Algorithm, Python.
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DOI:
10.17148/IJARCCE.2025.14690
