Sustainable Agriculture Monitoring: Energy and Carbon Footprint Analysis of LoRa-Based Wireless Sensor Networks

The integration of LoRa (Long Range) technology in Wireless Sensor Networks (WSNs) provides a promising solution for sustainable agriculture by enabling low-power, long-range environmental monitoring. This study evaluates the energy consumption and carbon footprint of LoRa-based WSNs deployed in agricultural settings, aiming to identify optimal configurations that support sustainable development goals. Through systematic experimentation, we examined the impact of key parameters, including transmission frequency, duty cycle, and node density, on network energy efficiency and environmental impact. By adjusting these parameters, we identified configurations that achieved up to a 90% reduction in energy consumption, significantly lowering carbon emissions while ensuring reliable data transmission. Furthermore, environmental attenuation was simulated to assess the network's resilience under challenging conditions. The results demonstrate that precise calibration of the duty cycle and transmission frequency plays a crucial role in reducing the carbon footprint of LoRa networks, highlighting LoRa's potential to support sustainable agricultural practices. This research emphasizes the importance of optimized LoRa-based WSNs in creating low-impact, resilient agricultural systems and offers valuable insights for the deployment of eco-friendly technologies in precision farming.