# Industrial IoT Monitoring: Technologies and Architecture Proposal
## 7 Conclusions  
The need for more dynamic and capable solutions in the Industry 4.0 field has contributed to an increase in the use of IWSN technologies in industrial applications over the last few years. As is widely recognised, WSN technologies have a considerable number of advantages over traditional solutions, although they are not free from drawbacks, namely in what concerns reliability, due to their resource-constrained nature. Nevertheless, hardware and firmware of sensor nodes are becoming more mature and capable. On one hand, the hardware is becoming more efficient and, at the same time, hardware manufactures are introducing new features in their architectures that allow the collection of state metrics. On the other hand, the adoption of operating systems in WSNs is also growing, enabling the development of firmware architectures and tools capable of collecting firmware state metrics. In a broader context, at the same time, ICS networks are shifting from networks disconnected from public infrastructures to systems connected to the Internet. This transformation is also exposing these systems to a new set of security threats, and new types of IDS systems are needed. To keep up with all of these changes and, at the same time, improve IWSN reliability, new network monitoring architectures are needed, more specifically, architectures that are not only capable of monitoring IWSNs from a network perspective, but also from the hardware and firmware perspective. Such a multi-domain IWSN monitoring architecture was proposed in this paper, considering the main process automation IWSN standards. In order to back up the proposal, a comprehensive revision of the state of the art was needed, in order to introduce the different concepts in each domain. This was done in Sections 2 and 3, by surveying WSN diagnostic tools and the relevant industrial technologies, and by presenting several network, hardware and firmware metrics as well as the techniques used to collect and transport them over wireless networks. Additionally, being a multi-network monitoring architecture, several management models were also presented. Lastly, the architecture was presented in Section 4, and validated in a real testbed scenario, in Section 5. In Section 4, when the architectural components were described, some possible solutions were presented in order to provide some guidelines for implementation. Nevertheless, as shown by our proof-of-concept implementation, the architecture can be used to perform the monitoring of a variety of sensor and network-wide parameters, in a way that does not increase the cost of node manufacturing, does not have a significant impact on sensor node resources, and does not steal network bandwidth from the main application. By proposing such architecture and by analysing relevant techniques and technologies, more questions and future research directions arose. Thus, as future work, we plan to further explore the proposed monitoring architecture by extending and refining the existing implementation. In the firmware domain, we aim at extending the architecture in order to provide support to more advanced instrumentation techniques, such as those proposed in [52,53,74]. On the other hand, in what concerns hardware monitoring, we would like to extend the compatibility to the ARM architecture,by supporting some of the metrics available in the CoreSight technology. From the network perspective, we would like explore new ways of reducing the overhead created over the network. Lastly, we plan to extend the implementation to other technologies (e.g., ZigBee, WIA-PA and ISA100.11a). Finally, by using the proposed architecture, we also plan to explore the architecture's data collection potential for building a diagnostic tool, and to share the acquired datasets with the community.