# Performance Evaluation of LoRa Communications in Harsh Industrial Environments
## 2 Related Work
The results showed that using a single LoRa gateway can cover an indoor area of around 34,000 m\({}^{2}\) with a spreading factor of 7. When the spreading factor is increased to 12, the area covered is even larger and includes the area outside the factory. Their results also showed that a gateway can serve up to 6000 nodes in such a scenario, making it a viable solution for IoT networks in industry. In the same context, a LoRa-based sensor node was evaluated for industrial use by [30] in terms of energy consumption rate and communication reliabilityin a harsh environment. The results show that the sensor node can operate efficiently with a battery for a long period of time, up to a cut-off voltage of 3.2 V. In addition, despite the harsh environment, the signals received were sufficiently reliable. Thus, a node could be deployed for industrial use with high reliability and lower maintenance costs. Several studies have been carried out to improve the performance of LoRa technology in industrial environments. The authors of [31] have proposed a real-time LoRa protocol for industrial monitoring and control applications. This protocol is based on a real-time task scheduling algorithm, complemented by a logical slot indexing algorithm for efficient schedule generation. In addition, a node clustering method has been proposed to solve signal fading and suppression problems. The results of tests of this protocol on a platform comprising a gateway and fifteen nodes showed that, despite relatively high traffic (one packet sent every three seconds on average by each node), the transmission success rate (TPR) exceeded 94%, even in the presence of high external interference, such as each interfering node generating one erroneous packet every three seconds. In the same context, another two-hop real-time LoRa protocol has been proposed [32]. This protocol is based on two-hop tree construction, distributed slot planning, and optimal data aggregation. It makes it possible to allocate slots to terminal nodes at one or two hops to meet time constraints, overcome the problem of packet loss, and minimize the number of transmissions to save energy. The protocol can support hundreds of nodes on a single channel and achieve high reliability in data transmissions, regardless of the number of nodes deployed. In addition, the authors in [33] proposed a real-time production monitoring approach based on wireless sensor networks (WSNs) and the LoRa protocol. This approach uses multiple wireless nodes networked with temperature and vibration sensors deployed on conventional manufacturing machines to record operational data for system diagnosis and troubleshooting. It has been implemented and tested on conventional manufacturing equipment in a food production facility. The tests on the prototype system confirmed the capabilities and accuracy of this approach. Another research project focused on the application of a metric called F-QoS to the LoRa network, particularly in complex industrial environments with installations minimizing disturbances [34]. The results indicate robust LoRa performance, despite challenges such as metal obstructions and non-ideal installation conditions. Using F-QoS, the authors also suggest a sampling approach where radio transmissions should be at least three times the desired final sampling rate to ensure data reliability. Moreover, the authors in [35] evaluate LoRaWAN performance with six different ADR algorithms in an industrial context using the FLoRa framework and an Omnet++ testbed. Analyses focus on packet delivery and energy consumption according to gateway position and data traffic. The results reveal that minimizing the link budget under unfavorable channel conditions improves performance, while overestimating channel behavior is detrimental to packet delivery.