Dense Indoor Sensor Networks: Towards passively sensing human presence with LoRaWAN

Sensors have become ubiquitous in buildings but are rarely connected to a network, and their potential analyse the performance, use, interaction with building is not yet fully realised. In coming years, we expect sensors part of Internet Things (IoT) grow numbers form Dense Indoor Sensor Network (DISN) that allows for unprecedented analysis buildings. Multiple technologies vie leading this transformation. We explore Long Range Wide Area (LoRaWAN) as an alternative creating indoor sensor networks extends beyond its original long-distance communication purpose. For present paper, developed DISN 390 nodes four gateways empirically evaluated performance two years. Our more than 86 million transmissions revealed DISNs achieve much lower distance coverage compared estimations from previous research indicating required. addition, deployment multiple decreased loss due environmental network factors. Given complexity our system, received few colliding concurrent messages, which demonstrates gap between projected requirements LoRaWAN systems actual real-world applications given sufficient gateways. also contribute modelling comparison attenuation models derived methodologies. Across all models, find robust environment can be maintained by placing gateway every 30 m 5 floors. Finally, investigate application passive sensing visualisation human presence using Digital Twin (DT) Fused Twins (FT) representation Augmented Reality (AR). A approach us gather relevant data on use while still preserving privacy via aggregation process. Immersive situ visualisations FT allow new interactions forms participation. conclude already technologically feasible today basing them Low Power (LPWAN) offers intriguing possibilities reduce energy consumption, maintenance cost, bandwidth enabling human-building interaction.