Connecting everything, consuming less: Building a greener IoT mesh network
The series Research in the Spotlight allows researchers from Kokkola University Consortium Chydenius to discuss their current research activities.
Xinying Kilpi-Chen works as a postdoctoral researcher in the Research Unit for Information Technology at the Kokkola University Consortium Chydenius.
In my research at the Research Unit for Information Technology at the Kokkola University Consortium Chydenius, I explore how devices can communicate efficiently over long distances without relying on existing wireless infrastructure. The most important outcome of this work is the demonstration of a self organized, low power, long range wireless network that allows devices to exchange data directly with each other—without Wi Fi, 5G, or any centralized controllers.
What makes this development especially significant is its remarkably low energy consumption. A device in this network can run for several years on a single AA battery, even while communicating across distances of several kilometres. This opens the door to long term, large scale connectivity that is both practical and sustainable.
Solving the challenge of sustainable, large scale data collection
Today, AI depends heavily on high quality data gathered from the surrounding environment. Yet collecting this data consistently, affordably, and sustainably is still a major hurdle, particularly in places lacking robust network infrastructure. My research tackles this challenge by focusing on how to connect large numbers of devices in an environmentally friendly way, keeping both costs and energy consumption low while ensuring reliable data flow.
To address this, I examined technologies such as LoRa and MIOTY, which enable long distance communication using very little power. By applying these technologies, I was able to create a network in which devices communicate directly with each other over several kilometres. This advancement makes the long discussed vision of “everything connected” not just possible, but feasible.
Impact across communities, industries and public services
The findings potentially have broad relevance for individuals, industries, and public authorities alike. The network supports detailed, collaborative monitoring of environmental conditions such as air quality, dust, and noise. Devices can share and process data together, creating a foundation for data driven and AI enabled systems.
This approach is particularly valuable in regions where traditional wireless infrastructure is unavailable or too costly to deploy. Long maintenance intervals and low operating costs mean it offers a realistic way to build independent, scalable communication networks from the ground up.
The societal and economic significance of this technology could be substantial. Cities can use it to improve citizen services through smarter monitoring and infrastructure management. Industries can adopt it for efficient machine to machine communication. Remote and underserved areas can benefit from reliable environmental monitoring. Ultimately, this research contributes to sustainable digitalization across multiple sectors by providing an efficient, economical, and scalable connectivity solution.
