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Embedded Intelligence for (IoT) smart process and services

Embedded Intelligence

‘Embedded Intelligence’ refers to the capability of a certain product, service, or process to evaluate and contemplate its performance. As well as the ability to handle the workload or its own working environment. This in turn leads to performance enhancement further resulting in the ultimate user satisfaction.

Thus, while designing a certain product or service, the concept of self-evaluation of the product through information received from sensors of the embedded system should be considered a priority.

The Integrative approach of launching a product or service must have the foundation of a business intelligence system at its core.

Accordingly, they forecast a significant growth for embedded systems ( CAGR of 18% from 2011 to 2016). – Source – Microsoft 

The utility of Embedded Intelligence:

The advantage is having an inbuilt embedded intelligent system along with a machine learning algorithm. That can evaluate through the functions performed by it in the following fields:

  1. Launching smart product systems:- 

This smart edge infrastructure aids in analyzing and predicting the changing business patterns and trends. Accordingly, something in which human analysts often fail. Thus, these embedded sensors in modern devices and products have become necessary machine intelligence solutions in the modern business world.

  1. Establishing smart business services:- 

The embedded BI differs from traditional BI on the basic ground that the former. Unlike the latter draws the best abilities of the business application directly into the application currently in use. 

This benefits the process of creating smart services as:

  1. It increases the adoption rates of the application in question
  2. The time spent on the application increases substantially, 
  3. The application receives an added value
  4. Visible improvement in user satisfaction
  5. The subsequent increase in the revenue earned.
Embedded Intelligence uses

Utilizing in implementing IoT:

This process has subsequently evolved due to the confluence of various forms of technologies and machine intelligence solutions. 

The trends of implementing IoT through embedded intelligence:

  1. Artificial Intelligence – This refers to the fusion of human and machine intelligence. In a certain device or service to make the same, capable of taking decisions like the human mind.
  2. Blockchain – It is a business intelligence tool or technology that is available for tracking the history of devices.
  3. IoT in healthcare – Implementing IoT in the hospital industry may prove to be profitable. Consequently, healthcare would be more accessible and development could grow by the minute.
  4. Retail privatization– Improving the implementation of IoT would bring about a revolution in the retail industry too.
  5. Predicting Maintenance – With the evolution of IoT has evolved the concept of predictive maintenance. This implies the process of fitting household gadgets with sensors that provide alerts when the specific gadgets need maintenance or repair.

Pervasive Intelligence: A brief account

Today, it is all about the use of pervasive intelligence systems to aid companies and organizations. This aids in achieving greater capacities and unparalleled efficiency. Utilizing the pervasive intelligence pattern alongside artificial intelligence will create an efficient building operation. That will hold unexpected benefits as well as improve the existing relationship between the employees of an organization and their data.

This era of penetrating data is an mark of augmentation of smart devices enforce by artificial intelligence. Besides, this will enable to react to sound, light, and any other pattern. We can expect that a wide variety of businesses, areas will benefit from the introduction of these smart devices. These include healthcare, production, construction, and logistical evaluation. 

As these devices will be embedded with artificial intelligence, rather than solely depending on cloud computing. These will be independent of the internet connectivity.

Power BI Embedded solution for Embedded Intelligence

The term ‘Embedded’ refers to being firmly grounded. When an organization embeds a certain piece of information for its customers or clients. It implies that such customers or clients will be able to access that certain piece of information or data. That too from the organization’s collection of authorized data.

The Power BI Embedded is a service of Microsoft Azure that provides for embedding services to the user organizations. Also, Embedding procedure for a customer implies the method of extending the services of the Power BI account. The one that is held by the instant organization to the customer in question.

Power BI Embedded Architecture with Microsoft Azure

This process of embedding information can be done for two categories of customers namely:

  1. Customers with a Power BI license
  2. Customers without a Power BI license.

Certain instances of embedding information by organizations include the SharePoint Online, Microsoft Teams Integration, Microsoft Dynamics, and others. Through Microsoft BI Embedded, the user organization can embed dashboards and reports for its customers to gain access to. 

This service enables independent software developers to embed visuals, reports, or dashboards to a certain application fast. Additionally, to complete the process a model that is capacity-based and metered on an hourly basis is implemented

Influence on Industry

The massive influence of immersive intelligence upon the industry in the modern era has its basis in the issues presented by cloud computing in the previous years. The expense of transferring data to the cloud and the subsequent delay in the transfer had created enough hurdles in the way of the potential growth of organizations. 

Consequently, this is the reason why companies in recent years have shifted towards the use of immersive intelligence. Embedded intelligence has had influence on the industry to a great extent. We can understand this through the analysis of its utilization in various spheres of life namely –

  1. Building and Construction – The usage of Artificial Intelligence through the installation of sensors in various parts of the building both inside and outside have removed all the hassle and fuss about security, temperature, lighting, and others.
  2. Oil Stations and Gas Platforms – Certain devices fitted with artificial intelligence sensors are capable of increasing the efficiency of work. As well as the performance of drilling and building platforms. The maintenance of such oil stations can also be taken care of through sensors fitted in and around the platforms. Screens with facial recognition features can also compel the fulfillment of certain rules like wearing helmets and others.
  3. Factories – The use of smart machinery in the factories, and installing sensors in various devices help the engineers in factories. Furthermore, this aids them to analyze and improve the production performance of the factory as a whole.
  4. Supply Chains – Running a successful yet sustainable supply chain involves a range of locations over a large area. Utilizing an improved level of operating system based on artificial intelligence. Will aid in tracking and delivering the required goods on time which subsequently will result in increasing business.

Predictive Analysis using embedded intelligence :

While traditional business intelligence creates a hassle for customers to switch through various dashboards to obtain information. The improved embedded intelligence patterns aid in providing the customers direct access to the required information without any extra trouble or fuss. 

This is the reason why organizations all over the world are now implementing the latter to improve their performance capabilities. The term ‘predictive analysis’ refers to a collection of techniques. In order to analyze data, to find existing defaults, and subsequently find solutions to the existing problems. 

The organizations that intend to utilize this improved business intelligence can do so through the following steps –

  1. Focussing on the decision making criteria. Predictive analysis can improve the decision-making capacity of an organization.
  2. Developing an analytical pattern. Companies must essentially develop the pattern of analyzing or predicting future patterns and possibilities.
  3. Embedding in various stages: Organisations should embed information for their customers at various levels of their services.
  4. Create a model of predicting future patterns. Developing an efficient model for predicting future trends. And, patterns aids an organization to prepare for any crisis that may arise shortly.
  5. Checking on the validity of the model. Timely evaluation of the validity of the analysis model can aid in monitoring the productivity of the organization.

Conclusion :

As the Power BI embedded provides the above-mentioned features, in recent years. Hence, it is considered one of the most helpful and effective embedding services in the business arena.

Therefore, Microsoft BI Embedded to improve your organization’s performance and achieve the long-awaited success.

Errin OConnor

Errin OConnor

With over 25 years of experience in Information Technology and Management Consulting, Errin O’Connor has led hundreds of large-scale enterprise implementations from Business Intelligence, Power BI, Office 365, SharePoint, Exchange, IT Security, Azure and Hybrid Cloud efforts for over 165 Fortune 500 companies.

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