An Introduction to Internet of Things (IoT) and Lifecycle Management – Visions and Concluding Remarks

 

The IoT Work Group’s initial goal was to fill gaps in the IoT standardization landscape that were identified based on numerous real applications studied and implemented in projects performed by Work Group members. The Open Group IoT standards – O-MI and O-DF – are the first published standards that address the gap and need for IoT standards that enable Systems of Systems interoperability, while also addressing the requirements for enabling true Closed-Loop PLM. IoT standards for messaging and data description both play an important part in the context of Closed-Loop PLM, fulfilling distinguishing but complementary needs.

The variety of different applications, data sources, exchange formats, and transport protocols requires a high level of flexibility and scalability. Besides the traditional approaches to data integration, a number of semantic approaches remain to be taken into account. Here are some benefits of using semantic modeling approaches in the infrastructure of IoT, taken from the discussion by [1]:

  • Semantics for Interoperability: Different stakeholders can access and interpret the data unambiguously. Things on the IoT need to exchange data among each other and with other users on the Internet. Semantic annotation of the data can provide machine-interpretable descriptions upon which the data represents where it originates from, how it can be related to its surroundings, who is providing it, and what are the quality, technical, and non-technical attributes.
  • IoT Data Integration: IoT data usually originates from a device or a human, and refers to attributes of a phenomenon or an entity in the physical world. The data can be combined with other data to create different abstractions of the environment, or it can be integrated to the data processing chain in an existing application to support context and situation awareness. Semantic descriptions can support this integration by enabling interoperability between different sources.
  • Resource/Service Search and Discovery: In IoT, a resource is referred to as a device or entity that can provide data or perform actuation (e.g., a sensor or an actuator), and a service is a software entity that exposes the functionality of its corresponding resource. The search and discovery mechanisms allow locating resources or services that provide data related to an entity of interest in the physical world. Semantically annotated data and apps can be processed by and retrieved by intelligent reasoning tools, therefore giving the possibility of integrating an e-ecosystem layer for smart search and knowledge retrieval.