# An Interoperable Component-Based Architecture for Data-Driven IoT System
## 6 Conclusions  
This paper presents a component-based architecture for IoT systems that supports system interoperability and service reusability, while able to accommodate flexible data-driven feedback functions. We validated the viability of the proposed architecture by building a prototype system based on the proposed IoT architecture.  
We implemented the prototype IoT system on real-world use case scenarios, which is the Solar PV MPPT system, and conducted a series of experiments: (1) MPPT implementation experiment; and (2) system interoperability experiment. Through Experiment (1), we proved that our proposed architecture is viable to be implemented in real-world situations. The data-driven functionality is demonstrated through the implementation of the MPPT algorithms. Furthermore, it is able to deliver the same performance as existing offline MPPT systems.  
Through Experiment (2), we managed to show that our system is able to support the interoperability of different devices. The system can interoperate with different kinds of devices. In short, the system demonstrated a higher level of support for heterogeneous system and device interoperations with minimum standardization required. Moreover, the reusability of components is also demonstrated through the experiments, as we are able to easily integrate multiple devices of different OS without needing to alter the main system framework and other components of the system.  
Overall, our proposed idea is proven to be able to solve the system interoperability and reusability limitation effectively through the implementation of IoT system prototype in a real-world use case. Furthermore, we introduced the automated data-driven function approach, which increases the cognitivity of the IoT system on data analysis through the automated data-driven model selector that self-evaluates and chooses the best performing model for specific applications. The component-based design method is proven to be able to accommodate system reusability and interoperability. The current minimum standardization required for our system to realize interoperation is the communication protocol coupled with a fixed data format. To realize a greater degree of interoperability, the future research direction is to further remove the standard requirements on the data format. Since the basic communication between IoT devices that operates under different communication protocols is currently available, a cognitive system that is able to resolve data string of diverse communication protocols and a smart data decoding and identification system for non-standardized data formats are required to further enhance the system interoperability of IoT systems, which is highly achievable through machine learning and AI methods.  
Conceptualization, S.K.L. and C.S.L.; Methodology, C.S.L. and K.S.T.; Software, S.K.L.; Validation, C.S.L., K.S.T. and S.M.; Formal Analysis, S.K.L., C.S.L. and K.S.T.; Investigation, S.K.L., C.S.L. and K.S.T.; Resources, C.S.L., K.S.T. and S.M.; Data Curation, S.K.L.; Writing-Original Draft Preparation, S.K.L.; Writing-Review & Editing, C.S.L. and K.S.T. and S.M.; Visualization, S.K.L.; Supervision, C.S.L. and K.S.T.; Project Administration, S.K.L.; Funding Acquisition, K.S.T. This research received no external funding. This work was supported by UM partnership Grant (Project No: RK008-2019). The authors declare no conflict of interest.