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Related Experiment Video

Updated: Mar 20, 2026

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

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VLC-Based Positioning System for an Indoor Environment Using an Image Sensor and an Accelerometer Sensor.

Phat Huynh¹, Myungsik Yoo²

¹School of Electrical Engineering, Soongsil University, Dongjak Gu, Seoul 06978, Korea. phathuynh@ssu.ac.kr.

Sensors (Basel, Switzerland)

|May 31, 2016

Summary

This study introduces a novel indoor positioning system using visible light communication (VLC) with LEDs and mobile sensors. The system achieves high precision by leveraging LED coordinates and image data, enhanced by an accelerometer sensor.

Keywords:

LED accelerometer sensor image sensor indoor positioning photodiode (PD)visible light communication

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Area of Science:

Optoelectronics
Indoor Positioning Systems
Wireless Communication

Background:

High power Light Emitting Diodes (LEDs) are increasingly central to visible light communication (VLC) systems.
Existing indoor positioning systems often have limitations in accuracy or hardware requirements.

Purpose of the Study:

To propose a novel, high-precision indoor positioning system design utilizing VLC technology.
To integrate mobile device sensors, specifically an image sensor (IS) and an accelerometer sensor (AS), for enhanced positioning capabilities.

Main Methods:

The system employs four ceiling-mounted LEDs transmitting their 3D world coordinates.
An image sensor (IS) on a mobile device receives and demodulates these signals.
The mobile device's position is calculated using the 3D LED coordinates and the 2D image coordinates, with an accelerometer sensor (AS) allowing for arbitrary orientation and noise reduction techniques implemented.

Main Results:

The proposed algorithm achieves high-precision indoor positioning.
It requires only a single image sensor (IS) from the mobile device.
The integration of an accelerometer sensor (AS) accommodates arbitrary device orientations, and noise reduction mechanisms further improve accuracy.

Conclusions:

The developed algorithm offers a robust and accurate solution for indoor positioning using visible light communication.
The system's reliance on a single image sensor and its ability to handle various device orientations make it a practical and versatile solution.