Massive Internet of Things (IoT) is a vast network interconnecting an unparalleled number of low-cost and battery-operated smart sensors and actuators, playing a pivotal role in the Fourth Industrial Revolution. In his doctoral dissertation, MSc Tiago Troccoli advanced the field by developing fast, cost-effective and energy-efficient Direction-of-Arrival (DOA) methods specifically designed for resource-constrained IoT devices, thereby enabling efficient indoor localization in massive IoT networks.
Imagine you are in a big indoor space, such as a shopping mall or a large office building, and you want to know exactly where you are within that space using your smartphone. DOA-based indoor localization works by determining your precise location within a building using small electronic devices equipped with antenna arrays called anchor nodes.
These anchor nodes are placed at known locations and receive radio signals emitted by your smartphone. By measuring the angles at which these radio signals arrive at the anchor nodes, the system calculates your position.
In his research, MSc Tiago Troccoli developed fast, cost-effective and energy-efficient DOA methods.
Indoor localization benefits across diverse industries
IoT-based indoor localization is increasingly important due to its wide range of applications in various industries. In industries such as manufacturing, healthcare, and logistics, indoor localization allows for real-time tracking of assets, equipment, and inventory.
– This improves operational efficiency, reduces loss, and enhances resource management. It can improve safety by monitoring the location of individuals in hazardous environments, enabling quick responses in emergencies, and ensuring compliance with safety protocols, Tiago explains.
In smart buildings, indoor localization is crucial for automating systems like lighting, heating, and access control based on the presence and movement of occupants. This contributes to energy efficiency and convenience.
New methods for resource-constrained IoT devices
Incorporating DOA methods into IoT devices poses a significant challenge due to their limited computational resources and reliance on battery power. Conversely, DOA methods involve complex numerical algorithms that require substantial resources and are time-consuming, leading to rapid battery drain, long execution time, and resource starvation.
Additionally, IoT devices typically operate on simple operating systems where they concurrently handle small tasks such as sensor data acquisition and communication with other devices.
– The new DOA methods developed in this study are specifically designed for battery-operated and resource-constrained IoT devices, thereby enabling energy-efficient and time-effective indoor localization in massive IoT networks, Tiago says.
Public defence on Friday 27 September
The doctoral dissertation of MSc Tiago Troccoli in the field of Communications Engineering titled Direction-of-Arrival-based Indoor Localization Systems for Massive IoT Networks: An Embedded Implementation Perspective will be publicly examined at the Faculty of Information Technology and Communications Sciences of Tampere University at 12.15 on Friday 27.9.2024 at Hervanta Campus, Tietotalo building, auditorium TB109 (Naulakatu 2, Tampere). The Opponent will be Professor Sergiy Vorobyov from Aalto University. The Custos will be Professor Jari Nurmi from Tampere University.