Towards sustainable indoor sensing and localization with battery-free light-based internet of things
Thesis event information
Date and time of the thesis defence
Place of the thesis defence
Wetteri-Auditorium (IT115)
Topic of the dissertation
Towards sustainable indoor sensing and localization with battery-free light-based internet of things
Doctoral candidate
Master of Science Malalgodage Amila Nilantha Perera
Faculty and unit
University of Oulu Graduate School, Faculty of Information Technology and Electrical Engineering, Centre for Wireless Communications - Networks and Systems
Subject of study
Communications Engineering
Opponent
Professor Geoff Merrett, University of Southampton, UK
Custos
Professor Marcos Katz, University of Oulu
Towards sustainable indoor sensing and localization with battery-free light-based internet of things
The emergence of 6G and beyond Internet of Things (IoT) technologies is expected to drive large-scale indoor IoT deployments, which present several challenges. Congestion in the radio frequency (RF) spectrum, coupled with the e-waste and maintenance demands associated with electrochemical batteries, necessitate a sustainable, battery-free, and recyclable IoT architecture specifically designed for indoor applications, complementing existing RF-based IoT solutions. In response, this research proposes a Light-based IoT (LIoT) that utilizes indoor illumination as a unified medium for energy harvesting (EH) and optical wireless communication (OWC), enabling sustainable battery-free operation.
The LIoT system repurposes LED luminaires as access points that simultaneously provide illumination and support OWC. The proposed node integrates photovoltaic (PV)-based energy harvesting, sustainable materials, and intermittent operation to enable zero-energy IoT (ZE-IoT) functionality. Communication is established through visible light and infrared links, and a proof-of-concept (PoC) prototype demonstrates energy-autonomous operation under typical indoor conditions.
Beyond sensing and communication, the same LIoT hardware can be reused for indoor localization. Features derived from optical detectors and PV harvesters estimate the spatial context, eliminating dedicated localization infrastructure. Results from the ML-assisted PoC system show 80% positioning accuracy within a 12.5 cm margin and 68% orientation classification accuracy.
To address non-uniform indoor illumination, the LIoT framework introduces Data-Energy Networking (DE-LIoT). In this approach, energy-rich nodes collaborate with the data network to intermittently share surplus energy with nearby constrained nodes via Optical Wireless Power Transfer (OWPT), forming a cooperative data-energy network. Evaluation using the PoC DE-LIoT system demonstrates a 50% increase in illumination at the target node and an extension of battery-free operation from 8 hours to over 40 hours.
Overall, this research validates the LIoT concept through PoC implementations, establishing a framework for sustainable, battery-free indoor IoT.
The LIoT system repurposes LED luminaires as access points that simultaneously provide illumination and support OWC. The proposed node integrates photovoltaic (PV)-based energy harvesting, sustainable materials, and intermittent operation to enable zero-energy IoT (ZE-IoT) functionality. Communication is established through visible light and infrared links, and a proof-of-concept (PoC) prototype demonstrates energy-autonomous operation under typical indoor conditions.
Beyond sensing and communication, the same LIoT hardware can be reused for indoor localization. Features derived from optical detectors and PV harvesters estimate the spatial context, eliminating dedicated localization infrastructure. Results from the ML-assisted PoC system show 80% positioning accuracy within a 12.5 cm margin and 68% orientation classification accuracy.
To address non-uniform indoor illumination, the LIoT framework introduces Data-Energy Networking (DE-LIoT). In this approach, energy-rich nodes collaborate with the data network to intermittently share surplus energy with nearby constrained nodes via Optical Wireless Power Transfer (OWPT), forming a cooperative data-energy network. Evaluation using the PoC DE-LIoT system demonstrates a 50% increase in illumination at the target node and an extension of battery-free operation from 8 hours to over 40 hours.
Overall, this research validates the LIoT concept through PoC implementations, establishing a framework for sustainable, battery-free indoor IoT.
Created 2.12.2025 | Updated 3.12.2025