## 2 Related Work  
Research work related to WSN implementation for WARM applications are studied for this paper. WSN coverage can be improved by using multiple hops, long-range wireless links, or by introducing mobility to the WSN elements, such as SNs or a DS. Multiple hops in a WSN require network-specific routing protocols. For a WARM application such as WQM, various underwater routing protocols [19] have been proposed that use multiple transmission paths, a layered network, the creation pf a cylindrical path, the fragmentation of the packet to multiple forwarder nodes, multiple mobile data sinks, and mobile repeater nodes. However, because of the underwater noise, multipath delay, low bandwidth, and the limited mobility of the nodes, these routing protocols are not suitable for above surface WARM applications which require wide-area coverage. In another study, the lifetime of the WSN is improved by event-driven data transmission [20]. This type of WSN is ideal for a static WSN with clustering, but lacks coverage. Compressed sensing is proposed in [21] to reduce the total energy consumption of the WSN where most of the sensors are used to measure very similar parameters. This may suffer spatial relations of the data for a WARM application where different types of parameters need to be acquired. In [22] base-station relocation using various local or global optimization algorithms are used to achieve wider coverage and energy balance in a densely populated WSN, which is not capable of continuous relocation to cover large geographical areas required for WARM. An analysis of the relocation or positioning of a mobile DS in a pre-clustered WSN using various optimization algorithms is presented in [23]; however, it is only suitable for static and densely populated clustered WSN. LoRaWAN (LoRa Wide Area Network) is a MAC (Media Access Control) layer protocol [24] on the LoRa physical (LoRa-PHY) layer used to control channel access and reduce collision and channel congestion. The LoRaWAN protocol stack is described in Section 4.1. A secure device-to-device communication using the LoRaWAN-IP (Internet Protocol) gateway is proposed in [25] to increase security, but it also increases energy consumption by 5%. Therefore, it is not efficient for WARM applications in terms of power consumption and bandwidth requirement, since the data travels inefficiently over the node to the gateway link. The LoRaWAN-based ADR (Adaptive Data Rate) scheme in [26] is implemented with link-check and acknowledgment features. This algorithm is dependent on criteria that may cause an unnecessary delay while establishing the links, and may also cause unseen data loss for a densely populated mesh network. Another option with the LoRa-PHY-based multi-hop routing [27] to the LoRa-IoT gateway also may suffer a time delay for a long TOA (Time On Air). It may not support topology-independent routing that is essential for a WSN in WARM applications. In [28], a WSN with the LoRa interface is implemented using a random-number-based clustering algorithm, which is suitable for static star topology. In [29], allocation of a specific spreading factor for each subnet is used for a LoRa static mesh WSN to improve coverage efficiency. Both these algorithms [28; 29], may not be suitable for a mobile DS, because they cause topological changes in the network. A low-power data reduction technique is implemented in [30], using dynamic sub-sampling to reduce LoRa traffic for an environmental monitoring application. Given the above drawbacks of LoRaWAN and multi-hop transmission using LoRa-PHY, only a single-hop LoRa link was considered for WARM applications for the proposed LDAP. UAVs are also used to provide mobility for remote data acquisition, in which dedicated SNs are mounted on the UAV, or UAV-based networking is implemented. However, UAV-based network communication suffers connection disruption, causing data loss due to its frequent mobility and dynamic routing [31].