A Cost-Effective and Scalable LoRa Sensor Network for Real-Time Hyperlocal Microclimate Monitoring

Urban microclimate monitoring is often limited by the high cost of weather stations, restricting the spatial density needed to capture fine-scale temperature variations. This study presents an alternative low-cost LoRaWAN-based heat sensor, developed for real-time, hyperlocal monitoring. The battery-powered system utilizes an existing LoRaWAN network infrastructure and a community-based LoRaWAN platform, enabling flexible, wireless deployment on existing infrastructure such as lamp posts, without the need for charging cables, Wi-Fi or Ethernet connections. To ensure low setup complexity and minimal maintenance, the sensor employs Over-the-Air Transmission (OATT), allowing automatic network connection and re-connection without manual configuration. With a typical accuracy of ±0.2°C, the system is designed to provide long-term, high-spatial, and high-temporal resolution data for urban climate research.

The paper explores a one-year deployment in East London, involving eight bespoke sensors alongside twenty-four commercial systems with the aim of determining their accuracy, agreement and communication. Results demonstrated a high level of measurement accuracy (Pearson R² = 0.999, mean temperature difference of 0.13°C, within ±0.5°C propagation error well within the combined quoted uncertainties of ±0.4°C). The real-time transmission capability mitigates data loss risks from hardware failures or extreme weather events, a key limitation of traditional data loggers. However, the commercial system’s longer battery life makes it a useful supplementary tool in areas with limited network coverage.

The deployment looks to validates the sensor devices as a cost-effective alternative to conventional weather stations, supporting the development of London’s first low-cost, real-time microclimate monitoring network. By addressing critical data gaps in urban heat island research, the findings highlight the feasibility of affordable, scalable sensor networks for high-resolution urban climate studies, sensor-based model validation, climate adaptation planning, and heat mitigation strategies. The study advances the role of low-cost, city-wide sensor networks in urban climate research, demonstrating their potential for real-time environmental monitoring at scale.