## 3 Description of the Maritime Sensor Network in the Gulf of Guinea  
Full description of the observed maritime sensor network where IoT OTH maritime surveillance service is deployed can be found in [15]. In this section, only a brief description is given in order to introduce a reader with the details needed for the IoT OTH maritime surveillance service analysis, which is the paper's main topic. The HFSWRs are deployed at two remote locations on the coast of the Gulf of Guinea that are 100 km apart. Both locations are more than 500 km away from C2 center (central location) where the data fusion is performed. All three locations are connected via the satellite links, as shown in Figure 4, representing a generic communication architecture. The data flow for the IoT OTH maritime surveillance service starts with collecting of the raw data by the sensors at two remote locations. The initial processing of the collected data during which the detection files are created is performed on local servers, situated at remote locations. Then the implemented script on local servers starts sending the detection files to central server at Command and Control Center via satellite link using TCP protocol. The algorithm for data fusion, implemented on the central server, uses successfully transferred detection files to produce the final result in the form of accurately detected targets that are being tracked. Time, and thus transmission via the mentioned satellite link, is a key  
Figure 3: Mobile telephony penetration in the Gulf of Guinea (based on data available from [27]). factor in successful pairing of detection files from different remote locations that should participate in the fusion process. It can be seen in Figure 4 that there are other sensors in the maritime sensor network as well as HFSWRs, such as microwave radars or electro-optical devices. However, the emphasis of this paper is on the IoT OTH maritime surveillance service based on the OTH part of the maritime sensor network and HFSWRs. This is because in the given system architecture, shown in Figure 4, only HFSWRs are capable of detecting uncooperative vessels beyond the line of horizon. The detection process starts with the data collection during the so called the Coherent Integration Time (CIT). After the data are collected, they need to be processed in order to extract vessel detections. Both processes are time consuming since the first step (data collection) lasts 33 s. The time needed for the completion of the second step (collected data processing) depends on the amount of data collected during the first step. The end result is a so called cfar_reg file (detection file) which contains possible detections of the vessels in the HFSWR coverage area. Detection files are having a time stamp in their name, written in the form of yyyydddhhmmss (four digits for year, three for day of the year and two for hour, minute and second, respectively), which is actually the time when the first step (data collection and integration) started. Complete time needed for creation of the file may be seen in Figure 5.  
The created cfar_reg file is accessed by a script for sending data. The file is sent via a satellite link as shown in Figure 4. From both remote locations, new files are sent to the central location in equal periodical intervals in order to make the vessel tracking process smooth. The client side, located at a remote location, initiates the sending of files to the  
Figure 4: Complete maritime surveillance solution architecture. Figure 5: Log file showing the times relevant for cfar_reg files. server side at the central location. The server side receives the files and writes them on the disk of the central server where implemented algorithms perform target tracking and multi-sensor data fusion [14; 15; 16]. As it can be seen from Figure 5, data collection started at 21:45:38, while the cfar_reg file was created (modify time) at 22:47:04.