We are cruising into a machine-led world, where data generated needs to be understood, interpreted and converted into actionable insights. An intelligent IoT network system has the capability to help organizations leverage data and build meaningful connections between trillions of bits of data. To create an intelligent network system companies need to install the required infrastructure and firmware to run everything smoothly.
In this article, we will explore what is IoT network intelligence along with its levels and benefits to an organization.
IoT network intelligence is about optimizing resource utilization, minimizing manual approaches to a network, and ensuring the successful implementation of IoT programs.
One example of an intelligent network is the service delivery system we interact with today. Companies like Amazon and Uber have deployed an intelligent network to manage and handle the service requests while automating the tasks to increase the delivery of services.
Another example would be a company using the IoT network to ideate, define, and build new products after analyzing the customer's feedback, response, and experiences.
The trait of an intelligent system is that it seeks to understand the current state of the events and takes suitable actions to enhance performance. This further assists humans in recommending further actions and optimizing the IoT networks and systems further.
Today our discussion will focus on IoT network intelligence and its different levels.
The deployment of an intelligent IoT network is akin to the progression of things on six levels. So from observability to autonomy, all levels are connected rather sequentially, and their successful implementation is crucial to leveraging the power of an intelligent network.
Let’s understand these six levels;
In an IoT system, data is the basis of all learning and understanding of the machines. Any type of system cannot work intellectually if it cannot generate and deliver data. Plus, if that data is not interpreted correctly, the network can fail.
Observability refers to high-quality telemetry data or system performance information identification and building connections between humans and machines.
We need a network intelligence system that makes the human and machine connection possible for good observability. Plus, it needs a high level of processing; otherwise, extensive human labor is required to leverage the data.
In the next level, the intelligent network aggregates data into reports and then supplies the same to the central system. The type of reporting required can vary according to the requirements.
It can be historic versus real-time and raw versus aggregated. In all data sets and sequences, humans will benefit from the reports and can draw conclusions based on the data to take the required actions.
If not for drawing the conclusions themselves, an intelligent system is powerful enough to process the data to create actionable insights on the same. This will help save the time required by a person to understand the data, draw conclusions, and take actions.
The purpose here is to provide the right context created from business data. So things like replacing machines, changing a service delivery model, adding new items to the portfolio, etc., can be channelized with an IoT intelligent system.
While in the Description stage, the IoT network suggests the changes, it recommends business-level actions and the future course of action in the Prescription stage.
Here the human interaction with the machines is further reduced to the level that humans are required to double-check the recommendations & assumptions simply. They check the triggered course of action and ensure correct implementation.
The next level in the intelligent IoT network helps improve prediction accuracy and implementation of actions based on the intelligence provided. This further assists businesses in drawing the right conclusions, but with an added advantage of speed. Here humans are able to make decisions quickly and accurately.
This is the ultimate realization of an intelligent IoT network to the extent that humans have developed today. In this stage, the machines and data collaborate, understand the events, suggest and recommend solutions, take actions, and trigger the responses of followers by recording them.
The stage of complete autonomy is something that every organization today must aim for, especially the ones which work with a huge amount of data.
The core premise of an intelligent IoT system is that it works on your behalf and that, too, continuously.
One of the key benefits you will experience with such a system is avoiding unplanned downtime, which costs companies dearly. Unplanned downtime can cost companies losses of up to $50 billion in a year.
But with an intelligent system implemented in the organization, it can not only be avoided, but you will also benefit from predictive maintenance. Predictive maintenance is using analytics to predict equipment downtime and schedule corrective maintenance procedures beforehand.
An IoT-enabled system can analyze the machine patterns and detect anomalies, which helps with implementing corrective actions.
Secondly, organizations can also experience operational efficiency. This is possible due to the speedy and accurate predictions made by the system and deep insights provided by it to automate tasks.
Google is using the IoT network intelligence to manage its data center cooling system. It has resulted in reducing the overall costs as the system is trained to fetch data from the IoT sensors and predict temperatures plus pressure in the next hour. This data is then used to guide the actions of the cooling system and optimize the power consumption.
Organizations dealing in consumer products can use the system to ideate and create new products and services. As the network is trained to understand consumer behavior and market dynamics, the data here can be used to create predictions about services and suggest actions for better results.
As a result, an IoT-enabled intelligent network helps with cost reduction, enhancing performance, and identifying market opportunities easily. When combined together, these three aspects are crucial for a company’s success.
In other words, we can say that an IoT network intelligence system plays an important role in identifying new opportunities in the market and building a credible action game plan.
In the future, the importance, utility, and deployment of an IoT-enabled network intelligence system will increase. This is because the amount of data generated will increase, and with it, the need to interpret the same.
Today, we are at the beginning of automated vehicles and its associated system. These vehicles generate tremendous amounts of data every hour, be it about the location, situational awareness, or image data, among others.
All these aspects require effective data processing on a granular level to identify several types of intent, including behavioral.
Other than the automotive vehicles industry, IoT network intelligence can also be used in healthcare, logistics, transportation, fleet management, banking, and government services.
In the future, our machines, systems, and operations will become more data-intensive. Hence it is essential to build an intelligent network of connections and transactions that companies can leverage to create high-performance systems achieving cost reduction, operational efficiency, and high productivity.
The core principle of an IoT system is that it works on your behalf without compromising the security aspect. Plus, it works seamlessly to provide a reliable action plan and work to improve organizational performance.
About Guest Writer:
Kamal Rupareliya is the Director of Products at Intuz, focusing on innovation through technologies such as IoT, JAMStack, and Serverless Computing. He is an expert in IoT, Mobile Design, and Product Strategy, and he loves applying inventive ways to utilize technology and empathy towards creating remarkable digital software products.
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