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How to maximize your business automation with enterprise IoT?

(Image credit: Image source: Shutterstock/everything possible)

Internet of Things or IoT has powered several enterprises and businesses over the past few years to enhance business operations. IoT has brought more connective options for enterprises and it is the sole reason enterprise IoT has become the flag bearer of business automation.

According to Gartner.inc, the enterprise and automotive IoT will reach 5.8 billion end-point units by the end of 2020 at a rate of 21 per cent growth rate from 4.8 billion in 2019. Automated lighting devices will be the top segment among enterprise and automotive IoT with a 42 per cent share.

Hyperconnectivity is actually a bliss for businesses as it helps the automation of several key business activities. But the problem lies with the accuracy of physical sensors or nodes that record data and transmit them to cloud servers for storage, computation, and retrieval of data.

What is business automation?

Business activities are planned and structured. Automation of these activities needs a proper workflow and excellent infrastructure to support the technology. With business automation, high volume repeatable task can be automated for employees to focus on other high-value activities.

Another essential part of business automation is the capture, recognition, and processing of data from several business processes. It is the sole reason why nodes or sensors are important to any business automation.

How to leverage enterprise IoT for business automation?

Enterprise IoT (Internet of Things) can be leveraged for business automation through the effective restructuring of sensors or nodes for smarter automated systems. Smart nodes can render data in adversarial conditions and reduce power consumption.

Enterprise IoT is actually an integration of physical devices with computer devices to power them with computational powers for several business processes. Here, the focus is on physical devices or sensors.

A smart IoT system by restructuring nodes

A smart enterprise IoT system based on the restructuring of nodes can automate the process in case of downtime or maintenance that can ultimately lead to loss of production. An IoT environment can be created that can employ a reconfiguration script for nodes, whenever there is downtime.

Employing the reconfiguration script will keep the nodes reconfigured for integration with the system to automate the process. The script will monitor the activities of the nodes/sensor. The script will check whether the node is transmitting data or not.

If the node is still transmitting data, in spite of downtime/maintenance, then the route information of the node is stored in a state table of the gateway node. Further, the current data on the state table is replaced by the earlier state table and becomes the current state table of the gateway node.

In simpler terms, the data transmitted during the normal workflow is replaced by data transmitted during the downtime. But, if the node is unable to transmit data, then the node is monitored through a monitor script that checks on the node. If the node seems to be working then the state table is updated at the node itself to insert a mobile node and update its route information.

Here, we are inserting a mobile node/sensor to help the business process keep running, in case of any node/sensor is under maintenance.

Software and network restructuring for business automation:

Software restructuring includes provisioning, maintaining and updating the operating systems of these nodes to ensure better data capture. Further, network capabilities remain to be the prime concern in an enterprise IoT. We already know that IoT devices are connected through the cloud servers by the hyperconnected network.

Network restructuring involves a centralised client-server to be the authoritative body to authorise, control and connect with several nodes. Software restructuring, on the other hand, needs technological and innovative prowess.

What can we achieve with the restructuring of enterprise IoT?

Restructuring of enterprise IoT can give an adaptive network with fail-proof connectivity to provide robust IoT systems. Businesses can leverage such a “node-level self-adaptive network path restructuring technique” to ensure complete automation of the business process, even in a state of breakdown.

Load balancing in business processes with automation can manage data loss in IoT networks and works wonder for routing of data. Here, replacing the nodes and inclusion of mobile nodes paves the way to lesser human intervention. With this approach, businesses can create a robust fail-proof network.

Machine learning and enterprise IoT:

Machine learning is an Artificial intelligence technology that gains knowledge on a particular domain and extends the same without programming paradigm. We already know that in order to make enterprise IoT, to be totally autonomous, we need to make smarter nodes, which can restructure themselves.

Machine learning algorithms can help businesses by employing learning methods such as supervised learning where algorithms are mentored for learning, unsupervised learning where algorithms are trained through self-learning and reinforced learning where algorithms are trained for definitive scenarios. These algorithms can induce self-restructuration into the nodes. As the nodes can restructure itself to create total business automation, they need enough computational power.

Benefits of Enterprise IoT for business automation:

  • Better connectivity between business processes.
  • Complete automation of business activities.
  • Data security and low data loss.
  • Effective management of data storage and retrieval.
  • Accuracy of data received and computational precision.
  • Authentication of users and newer nodes becomes easy.
  • Higher productivity, low costing, and greater revenues.

Limitations of enterprise IoT:

  • IoT devices have limited processing power.
  • Network connectivity and capabilities are still evolving.
  • Machine Learning technologies have been phenomenal, but, limited.
  • The infrastructure capabilities of the enterprise to cope up with BigData has been limited.

Parth Bari, Blogger, Kunsh Technologies