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Use of IoT in Digital Business

1929 words (8 pages) Essay in Information Technology

08/02/20 Information Technology Reference this

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Our entire lifestyle is now revolving around data. Smartphone, watches, wearables track each step of us and monitor our heart, our interests, and hobbies. Some of these insights not only benefit the customer, and some manufacturers also. Eventually, we are all stepping into an Internet of Things (IoT) world which benefits everyone.

The use of IoT in the business world to enhance data monitoring and important processes to be more thoughtful and increase efficiency and allow organizations to make better decisions. They tell the organizations what’s happening, rather what executives assume to home is happening. The IoT market is expected to grow $520 billion by 2021 which is more than a 100% rise in 2017.

Let’s see the keyways that IoT transforms the business in the digital world.

1.      Improved Business and Customer experience:

Connected network on equipment in various fields such as health care, manufacturing, aviation, supply chain, agriculture, and many more organizations is generating lots of data streams and analytics, meaning organizations are getting much more insights into their business operations and their services.

Cloud platforms such as Microsoft Azure, AWS, IBM and Google firebase, and many more private vendors are providing a way to incorporate the connectivity. In recent times Edge computing getting its traction in some organizations to reduce the latency in the systems. When a company understands how its consumers are using the products, they can provide a better experience for their users.

2.      Reduced Cost and Downtime:

The rapid expansion of new digital technologies is resulting in digital modeling of physical assets built from real-time data to visualize the data. The other technologies, such as big data, AR, AI, enterprise asset management, etc promise an emerging world of predictive maintenance and proactive operations. Imagine a small failure in the mission-critical components that can result in hours of downtime. Now, imagine every part of the equipment is being stored in the digital world, which informs the engineers or technicians ahead of time on the failure of the parts and its behavior. This type of technology will help cutting cost and operational downtimes of the systems and also helping the people to learn more about its apparatus which allows to better maintenance.

3.      Increased Efficiency and Productivity:

By connecting the key processes of the organization, people can predict the ways to enhance productivity such as making less physical stressful and safer workstations to enhance the manufacturing capabilities. The low cost and pervasive nature of IoT allow inventory control, data acquisition to be accomplished with a less human workforce which results in a reduced error and better handling of information.

4.      Better business models:

Most of the IoT deals with efficiency, productivity, and enhanced product monitoring, organizations quickly realizing the benefits of the IoT in order to enhance their customer experience. IoT and data analytics can work in parallel to provide business with predictive planning and can help organizations to manage their resource allocations.

IoT solutions are very complex because of the complex nature of inter-connected devices and IT services which open new challenges in communication, high volumes of data, security and real-time data analysis. To overcome these challenges IT organizations must adhere to:

  • Develop a technical strategy.
  • Define a reference architecture.
  • Develop the required skills to implement and deploy IoT solutions.
  • Define IoT governance processes and policies.

IoT governance can be described as an extension to IT governance, where IoT governance focuses on the life cycle of IoT devices, IoT applications, and data associated with it. IoT governance principles define some changes in IT governance to deliver business goals.

Figure 1 IoT Solution Model

Develop an IoT Technical Strategy

Successful IoT engagements require that IT organizations define a technical strategy that on board reference architecture, platforms, design processes, development and operations of IoT solutions. A skilled motivated team is required to build and deploy IoT solutions. The technical strategy is a step by step process which defines roles and activities in each phase. 

Figure 2 Phases of IoT Technical Strategy

The technical strategy must address all the business needs, technical and operational requirements, impediments. It must also assess and forecast the current and future business needs and adapt accordingly.

IoT reference Architecture

IoT architecture plays a key role in maintaining the integrity of multiple applications. IoT framework should meet multiple organizational needs and technology standards for all IoT projects to use. It provides design patterns, best practices in developing IoT enterprise solutions. It will help reduce project risk and lower costs. IoT ecosystem interacts with multiple components such as devices, networks, software layer, security, and data.

IoT solutions alone are not enough without security. All layers must be protected from outside vulnerabilities. Let’s look at a sample IoT architecture as described below.

Figure 3 IoT Architecture

Application Layer:

It manages large amounts of real-time data gathering and processing it. It supports a very high data rate which is significantly higher than regular IT infrastructure. This layer needs to have extreme data security and access restrictions.

Platform Layer:

It provides data management and integration, data dispatching, security management, operations management.

Communication Layer:

It provides a reliable network to capture real-time data from various platforms and devices.

Physical Layer:

It supports various devices and gateways, supports multiple monitoring systems like re-booting, firmware migrations, threat detection, maintaining logging of security events.

IoT Governance processes

IoT governance processes are followed and applied to manage all IoT models and solutions. Below show the major components of the IoT governance Model.

Figure 4 IoT Governance Model

Since IoT data is generated from various sources, It’s very crucial to protect information such as PII, sensitive records, bank information, health records, etc. To accomplish the security it’s very important to set up a very secure data storing mechanisms and restricting sharing of information across multiple networks. Failure to maintain data integrity and security of key information, sensor data may result in a potential threat to the entire organization. Let’s discuss the challenges and issues that the organization may face:

1.      Lack of enterprise standardization view:

The information in IoT network is generated from multiple resources such as devices, sensors and other sources that lack a holistic view of the data which provides an overall view on the data.

2.      Lack of IT Governance:

Because of the complexity of IoT solutions in data sharing across multiple devices and networks, the organization may face information accountability issues.

3.      Lack of Secure Access restrictions:

One of the crucial challenges in managing IoT solutions is to provide role-based restricted access because of the interaction of multiple networks. It’s very important to maintain a secure authentication across various vendors and IoT ecosystem.

4.      Maintaining Compliance:

As IoT advances it imposes new security compliances and regulatory challenges to the organizations. It’s very important to adhere to compliance with multiple organizations, intra-organizational, governmental compliances on data transactions.

5.      Lack of standard data format:

IoT architecture should have standard protocol and format but because of advancements in IoT maintaining standard guidelines is very challenging.

6.      Restricted Database management:

IoT deals with both structured and unstructured data so organizations should consider Big Data, No SQL database technologies which have its own security issues.

In order to address the above-mentioned issues, the organization should maintain effective data governance principles. IoT data lifecycle management strategy should comprise the below mentioned:

IoT data lifecycle management strategy

1.       Data Creation:

Data creation should be aligned with the business mission to control unwanted data creation. Selecting the right devices and vendors is very important in generating data.

2.       Data Collation:

The organization should identify the required and useful information which is relevant to the business needs.

3.       Data Storage:

Data security is a mission-critical item. The organization should forecast the data growth (Velocity, volume, and variety of data) and availability of infrastructure to accommodate that.

4.       Data Cleansing:

Applying the required data cleansing rules to get access to the relevant data. The cleansing process should be lightweight.

5.       Data Processing:

Data processing should be business mission and customer-centric. It should also allow for parallel processing with minimal cost.

6.       Data Retention:

It should comply with business requirements and IT regulations. The organization should focus on identifying useful information to ensure minimal data loss.

7.       Data Archiving:

It should happen with the regulatory requirements of the business and various organizations. It should be cost effective and efficient.

8.       Data Purging:

This process should be done with most care to avoid data loss, the organization must clearly define which information is useful and discard irrelevant information.

Conclusion

Many enterprises wanted to reap the benefits of IoT solutions. Nevertheless, without having a proper IoT Governance model, it’s very likely to failure of the mission. The IoT model needs to develop with a technical strategy and EA to maintain the standards. Security and data privacy are a key reason for the failure of an IoT solution, so IoT governance models and the process should be within the security concerns of the organization.

References

  • Andrew Hobbs. (n.d.). Retrieved from https://internetofbusiness.com/5-ways-the-internet-of-things-is-transforming-businesses-today/
  • Andrew Hobbs. (n.d.). Retrieved from https://internetofbusiness.com/10-steps-to-a-successful-business-case-for-iot/
  • IBM Developers. (n.d.). Retrieved from https://developer.ibm.com/articles/iot-governance-01/#define-your-iot-governance-processes-and-policies
  • Karyan Murphy. (n.d.). Retrieved from https://www.sas.com/en_us/insights/articles/data-management/iot-success-depends-on-data-governance-security-privacy.html
  • Rahul Kode. (n.d.). Retrieved from https://www.saviantconsulting.com/blog/5-ways-how-iot-and-analytics-help-enterprises.aspx
  • US Department of Defense. (n.d.). DoD Policy Recommendations for IoT.
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