Maritime Internet of Things meets LoRaWAN:a Container Testbed, Measurement Campaign and Dataset Analysis

Internet of Things improved the decision making processes related to ship and maritime environment and brought the software and hardware data acquisition, transmission and processing platforms and knowledge closer to the users through the so-called Maritime IoT (MIoT), enabling maritime services such as cargo, containers and ship monitoring. Recently, commercial solutions employing LoRa/LoRaWAN as a communication technology for containers monitoring were announced, but in the literature no experimental testbed and associate experiments were identified to assess the performance of such solutions, even though the maritime environment is very challenging and different communication technologies and topologies are proposed to meet its requirements. The contribution of the current paper is three-fold: i) proposing a practical implementation of a LoRaWAN-based container monitoring system, ii) analysing the collected dataset, solving a machine learning problem, i.e classifying LoRaWAN packets origin location based on k-best selected features algorithm and algorithms such as k-Neighbours, Gradient Boosting a.s.o iii) assessing the performance of the communication in multiple containers scenarios. The results shown that LoRaWAN has a huge potential to ensure communication between containers and outdoor gateways.