**Figure 4.**

*Global network architecture [30].*

#### **Figure 5.**

*Fragmentation in a ZigBee-to-LoraWAN communication.*

LoRaWAN subnet is responsible for communications that require greater immediacy, and the NB-IoT network forms the gateway to the IP network of all sensor data. The architecture used is based on three layers: sensor nodes layer, forwarding layer, and cloud layer. The end-to-end communication of the network is carried out using the MQTT messaging protocol [34], based on the publish/subscribe philosophy, which is supported by all nodes in the network.

### **3.2 Distributed interoperability**

An example of the philosophy presented in **Figure 3**. b of distributed interoperability is presented in [35], where a multi-RAT architecture is proposed for each node using two LPWA technologies: LoRa and NB-IoT. The latter allows greater BR, in addition to direct connection to IP technology through the mobile network. Therefore, the use of this technology implies the existence of coverage by a mobile operator to be able to implement the network. In the uplink, the use of NB-IoT

#### *Internet of Things – New Insights*

may require higher power consumption due to the need to implement the entire IP protocol stack. In this case, the use of LoRa may be less energetically costly. The authors propose a series of possible functionalities thanks to these multi-RAT nodes, such as:


Precisely on this last point is based the use case proposed in the next section of this chapter.

## **4. Proposed use case**

In coastal maritime environments, there is a need to monitor parameters such as currents, salinity, winds, temperature, water oxygenation, etc. The sensors responsible for these measurements can be assembled in buoys or, in some cases, in ships that usually sail on certain routes in the area. These ships can act as mobile nodes of the network collecting information from their own sensors or those of fixed buoys at a point and act as repeaters. An appropriate LPWAN technology for the interconnection of these nodes to the gateway could be LoRa, which also has great advantages due to its characteristics in this environment. There are multiple studies analyzing the propagation of radium in this ecosystem [36, 37].

On the other hand, in many archipelagos, there are certain areas in which there is mobile network coverage since operators provide it on routes transited by habitual maritime traffic, such as car and passenger ferries. These vessels are likely to be used as mobile nodes that would act as a gateway between technology, such as LoRa and NB-IoT. The use of nodes that combine these two technologies as proposed in the previous section is very useful giving greater versatility to the network and choosing one or the other always depending on the conditions. Not only offering a path to the cloud through land but also using the vessels themselves as mobile sink nodes agglutinating a cluster of sensor nodes in their route. **Figure 6** shows this use case.

The implementation of hybrid LoRa/NB-IoT nodes allows the right technology to be chosen in each case to reach the final application in the cloud. The nodes have a memory that stores data from sensors that could not be sent during times of absence of connection. In this particular case, non-proactive protocols could be contemplated because the appearance and disappearance of nodes in the network are not so fast, so the updating of routes does not have to be so continuous and the number of nodes in the network at each moment is not as large as in urban or suburban environments.

*Hybrid Architectures to Improve Coverage in Remote Areas and Incorporate Long-Range LPWAN… DOI: http://dx.doi.org/10.5772/intechopen.113328*

#### **Figure 6.**

*Proposed use case. a) LoRa multi-hop network with a central gateway, b) connection loss, and c) recovered path and retransmission of the saved data. Incorporation of mobile sink node with 4G/5G connection and interoperability.*

#### **Figure 7.**

*Main frame structure.*


#### **Figure 8.**

*Routing table entry.*

The protocol used by our group in this case, for the multi-hop LoRa network is based on the Ad-hoc On-Demand Distance Vector (AODV), with some small variations that allow the forwarding of sensor data accumulated in the queues implemented by the nodes. In addition, a field appears in the routing tables of each node that contains a pointer to a list of precursors to store the path of the packet to reach the node in question. So far, its operation has been proven in different types of links (aquatic and suburban). It is currently at the stage of action. **Figure 7** shows the format of the data package used, and **Figure 8** shows the routing table entry.

**Figure 9** shows the pseudocode of the main algorithm responsible for finding a route to the gateway directly or through another node to transmit sensor data and the level of power used. That allows the measurements to be carried out in the end.

Simulations have been carried out with Matlab using the Longley-Rice model. This has been done to see the behavior in the marine environment from real points between the gateway on land and an isolated node. **Figure 10** shows the results obtained on a sea route between the islands of Gran Canaria and Tenerife.

The system has been implemented using Libelium Waspmote with a LoRa communications module based on Semantech's SX1272. Depending on the manufacturer and depending on the SF and BW, it has different operating modes. The worst sensitivity for the lower SF case is −114 dBm and − 134 dBm for the maximum SF (12).

```
Figure 9.
```
*Main algorithm pseudocode.*

**Figure 11** shows the RSSI measurements in a coastal environment with a gateway and in different locations of a mixed coastal environment.
