Semantic IoT: The Key to Realizing IoT Value
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the patient and the medicos is semantically annotated and communicated in an effective way using the RDF. The SI is helping to unleash a new age of digitalization
across industries. From manufacturing to the home, the potential to increase connectivity and productivity across a range of sectors is massive. It sets to bring about new
ways in which businesses operate and engage with their products and customers.
All this is driving the fourth industrial revolution, Industry 4.0. The word “smart,”
from smart cities with smart factories, derives from this very revelation. These smart
environments encompass a variety of devices and technologies, and we’re already
seeing them today. Even in the manufacturing and industrial sectors, where automation and computerized control systems have been commonplace for many years,
digitalization is driving a massive level of change. The challenge of integrating these
legacies, mostly proprietary, systems that were not designed to communicate across
product lines and functional areas, means the journey toward Industry 4.0 should not
be underestimated. While digitalization is already well advanced in industrial environments, it is constrained by a lack of standards. To make the most of this digital
revolution, it is desired to harness the full power of Industry 4.0. It envisages capitalizing on potential savings that automation will bring, companies need to federate IoT
platforms and operating systems across multiple production lines and subsystems.
3.1 Issues of Semantic Interoperability (SI)
The followings are a few issues that need to be considered to make the SI effective.
• The words need to be used to represent a chosen set of concepts.
• A common vocabulary for IoT to tackle the semantic gaps between machines.
• The requirement to attach a multiple-level of semantics to raw data or a piece of
information.
• The possibility of interpreting different levels of meaningfulness to represent a
device or data.
• A strategic decision needs to include ontologies that facilitate the highest level of
semantic clarity and transparency, but are inexpensive both in money and time. A
trade-off has to be made between the cost and the amount of data sources while
including the ontology with SI for big and open environments.
• The addition of value on the available data or its representatives is apps or purpose
dependent. It poses difficulties for its adaptability by small IoT markets. In such
a case, city planners can usually access only restricted data without SI.
• The initial costs incurred to achieve the apps with speed may increase exponentially with the number of devices, apps, and their integrations. It will restrict the
use of available information for multiple purposes.
• With the increase in the number of IoT services, equipment, and the desire of cities
to become smarter, providing the SI service at an affordable price and flexibility
remains a challenge.
89
the patient and the medicos is semantically annotated and communicated in an effective way using the RDF. The SI is helping to unleash a new age of digitalization
across industries. From manufacturing to the home, the potential to increase connectivity and productivity across a range of sectors is massive. It sets to bring about new
ways in which businesses operate and engage with their products and customers.
All this is driving the fourth industrial revolution, Industry 4.0. The word “smart,”
from smart cities with smart factories, derives from this very revelation. These smart
environments encompass a variety of devices and technologies, and we’re already
seeing them today. Even in the manufacturing and industrial sectors, where automation and computerized control systems have been commonplace for many years,
digitalization is driving a massive level of change. The challenge of integrating these
legacies, mostly proprietary, systems that were not designed to communicate across
product lines and functional areas, means the journey toward Industry 4.0 should not
be underestimated. While digitalization is already well advanced in industrial environments, it is constrained by a lack of standards. To make the most of this digital
revolution, it is desired to harness the full power of Industry 4.0. It envisages capitalizing on potential savings that automation will bring, companies need to federate IoT
platforms and operating systems across multiple production lines and subsystems.
3.1 Issues of Semantic Interoperability (SI)
The followings are a few issues that need to be considered to make the SI effective.
• The words need to be used to represent a chosen set of concepts.
• A common vocabulary for IoT to tackle the semantic gaps between machines.
• The requirement to attach a multiple-level of semantics to raw data or a piece of
information.
• The possibility of interpreting different levels of meaningfulness to represent a
device or data.
• A strategic decision needs to include ontologies that facilitate the highest level of
semantic clarity and transparency, but are inexpensive both in money and time. A
trade-off has to be made between the cost and the amount of data sources while
including the ontology with SI for big and open environments.
• The addition of value on the available data or its representatives is apps or purpose
dependent. It poses difficulties for its adaptability by small IoT markets. In such
a case, city planners can usually access only restricted data without SI.
• The initial costs incurred to achieve the apps with speed may increase exponentially with the number of devices, apps, and their integrations. It will restrict the
use of available information for multiple purposes.
• With the increase in the number of IoT services, equipment, and the desire of cities
to become smarter, providing the SI service at an affordable price and flexibility
remains a challenge.