Exploration of IoT Nodes Communication Using LoRaWAN in Forest Environment

The simultaneous advances in the Internet of Things (IoT), Artificial intelligence (AI) and Robotics is going to revolutionize our world in the near future. In recent years, LoRa (Long Range) wireless powered by LoRaWAN (LoRa Wide Area Network) protocol has attracted the attention of researchers for numerous applications in the IoT domain. LoRa is a low power, unlicensed Industrial, Scientific, and Medical (ISM) band-equipped wireless technology that utilizes a wide area network protocol, i.e., LoRaWAN, to incorporate itself into the network infrastructure. In this paper, we have evaluated the LoRaWAN communication protocol for the implementation of the IoT (Internet of Things) nodes' communication in a forest scenario. The outdoor performance of LoRa wireless in LoRaWAN, i.e., the physical layer, has been evaluated in the forest area of Kashirampur Uttarakhand, India. Hence, the present paper aims towards analyzing the performance level of the LoRaWAN technology by observing the changes in Signal to Noise Ratio (SNR), Packet Reception Ratio (PRR) and Received Signal Strength Indicator (RSSI), with respect to the distance between IoT nodes. The article focuses on estimating network lifetime for a specific set of LoRa configuration parameters, hardware selection and power constraints. From the experimental results, it has been observed that transmissions can propagate to a distance of 300 m in the forest environment, while consuming approx. 63% less energy for spreading factor 7 at 2 dBm, without incurring significant packet loss with PRR greater than 80%.

Automated summary

The evaluation of LoRaWAN protocol in forest environment for IoT communication shows that transmission can reach up to 300 meters with significantly reduced energy consumption and high packet reception rate. The study focuses on analyzing the relationship between distance, SNR, PRR and RSSI in LoRa wireless communication, aiming to estimate network lifetime and performance level under specific parameters.