# A Resilient LoRa-Based Solution to Support Pervasive Sensing
## 3 Related Work
Finally, although it is generally true that having a higher value is better, chip manufacturers often use different scales for RSSI making it complicated to compare values obtained from other devices. [PERSON] and [PERSON]'s work offers a comprehensive review and classification of LoRaWAN mesh networks, focusing on multi-hop communication [19]. The study examines various approaches, protocols, and architectures employed in LoRaWAN mesh networks and categorizes them based on different characteristics. By providing insights into the LoRaWAN mesh networks' current state of the art, the review aids in understanding their advantages and limitations. However, the review primarily focuses on LoRaWAN-based mesh networks, which may have constraints and limitations imposed by the LoRaWAN standard. These limitations include restrictions on the number of gateways and limited support for multi-hop communication. Furthermore, as the field of LoRa mesh networks continues to evolve and new solutions emerge, the classification provided in the review may only cover some possible variations and approaches. The work by [PERSON] et al. presents a hybrid low-power wide-area mesh network for IoT applications [20]. The network combines LoRa and BLE technologies to achieve effective and dependable communication. It also provides improved energy efficiency, expanded coverage, and support for a range of IoT devices. The effectiveness of the network in terms of coverage, power usage, and data transmission reliability is demonstrated by experimental results. However, there are limitations, such as the need for thorough scalability analysis, a lack of evaluation and comparison with alternative solutions, and a brief discussion of security and privacy issues. [PERSON] et al. introduce a mesh network architecture that leverages LoRa technology to enable long-range peer-to-peer communication [21]. The study focuses on establishing direct connections between nodes using LoRa devices, enabling efficient and low-power communication over extended distances. The proposed mesh network architecture offers scalability and flexibility for various IoT applications. However, we have to consider that the peer-to-peer communication approach may face limitations in terms of scalability, particularly as the network size and the number of interconnected nodes increase. Additionally, while direct communication between nodes provides benefits such as reduced latency and efficient data exchange, it may require additional routing and network coordination mechanisms to ensure reliable and optimal communication. [PERSON] et al. present a hierarchical routing protocol to optimize energy consumption in LoRa mesh networks [22]. The protocol considers the nodes' hierarchy and their roles in the network to enhance energy efficiency. By focusing on routing protocols, the study addresses the goal of extending the battery life of LoRa devices. However, we must note that the proposed hierarchical routing protocol introduces additional complexity regarding network management and node coordination, necessitating efficient implementation and control mechanisms. Furthermore, the effectiveness of the protocol's energy efficiency gains may vary depending on specific network conditions and application scenarios, requiring evaluation in different deployment scenarios. [PERSON] et al. present an adaptive spreading factor selection mechanism to allow a LoRa network to have nodes that use different spreading factors. In their solution, each message has a preamble that is used by receiver nodes in order to perform activity detection [23]. When a node is listening for messages, it will cycle through all available spreading factors in the search for a node that is transmitting. When a node transmits a preamble using a particular spreading factor, the receiver will eventually receive it and temporarily set the same spreading factor to receive even the subsequent message right after the preamble ends.