A Low-Cost Low-Power LoRa Mesh Network for Large-Scale Environmental Sensing

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Abstract
Sustainability and climate monitoring efforts create a need for long-term in-situ sensing of large geographic areas. However, environmental monitoring in remote areas of developing countries remains impeded by a lack of low-cost, scalable Internet of Things (IoT) solutions. Whereas IoT systems for in-situ sensing abound, they mostly are either low-cost or suitable for large areas, but not both. In this article, we present a low-cost low-power network solution for in-situ sensing of areas up to hundreds of square kilometers. Taking advantage of LoRa technology, we develop a self-organizing mesh network that can be scaled to a hundred and more nodes. Scalability is achieved by developing methods that mitigate packet collisions during data collection. We present a protocol, called CottonCandy, with which nodes self-organize in a spanning-tree network topology in a distributed fashion. A power profile on a custom-built circuit board shows that CottonCandy nodes can run thousands of duty cycles on 2 AA batteries, sufficient to operate for years in many applications. Using off-the-shelf components, the cost of a CottonCandy node is less than U.S. $\$ $ 15. Evaluations by simulation show that CottonCandy networks with 100 nodes achieve a packet delivery ratio (PDR) of >90%. Measurements of an outdoor deployment with 15 nodes corroborate the high PDR in a real-life setting.
Funding Information
  • University of Toronto Centre for Global Engineering

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