What is AI and IIoT? What is required to start AI IIoT project successfully?

By 2020, approximately 50% of commercial assets in factories are going to be connected. As we head into a new decade, the clear lines between the five layers of industrial connectivity architecture have become more blurred than ever before. 

Early adopters of new industrial connectivity technologies and protocols are creating new data collection architectures that challenge the five-layer architecture.

Recent research reveals the six key industrial connectivity trends shaking up the industry.

Read this exclusive analyst report from IoT Analytics to learn

Market projections – Which of the fastest-growing segments will take an increasing share of the spend by 2024?

The battle between industrial connectivity vendors fighting for market share escalates 

3 new technologies are upsetting the traditional five-layer stack 

Will software-based solutions enable SME’s to surpass traditional industrial incumbents?

What are the new and emerging industrial connectivity protocols? 

Private 5G networks for industrial environments are on the rise 

Case study – A bin with a brain: The smart biowaste management solution powered by IoT.

Let me explain here what is AI and IIoT.

What is AI?

The Encyclopedia Britannica states

“Artificial Intelligence (AI), the power of a computer or computer-controlled robot to perform tasks commonly related to intelligent beings”.

AI refers to computational tools that can substitute for human intelligence in the performance of certain tasks. AI makes it possible for machines to find out from experience, suit new inputs and perform human-like tasks. AI lives everywhere now from researches labs to your front room. AI has taken jobs from humans already and can still do so because it becomes more widely adopted and effective.

Every industry features a high demand for AI capabilities. AI is being used in:

Health care — To provide personalized medicine and X-ray readings, Personal health care assistants

Retail — To provide virtual shopping capabilities that offer personalized recommendations and discuss purchase options with the consumer

Manufacturing — To analyze factory data as it streams from connected equipment to forecast expected load and demand using recurrent networks

Banking — To identify which transactions are likely to be fraudulent, adopt fast and accurate credit scoring and automate manually intense data management tasks.

AI can think logically without emotions, making rational decisions with less or no mistakes. It needs no sleep, rest, take breaks or get entertained as AI does not get bored or tired.

What is the Industrial Internet of Things (IIoT)?

An IIoT platform may be a set of hardware and software facilities that support applications for industrial companies using the web to billions of commercial devices. All of this data received from the connected devices can then be collected and analyzed to make business processes more efficient.

This use of the web is now commonly called the economic Internet of Things (IIoT)

Today, the Industrial Internet of Things (IIoT) is one rapidly growing and evolving version of IoT. IIoT enables high-end interconnection within many industries. 

Below are 4 points as efficiency. 

1. Better management 

Managing a large number of assets involved in manufacturing, including fleets of highly specialized machines.

2. Time savings

Reducing the time it takes to make products, in the face of the ever-changing market and consumer variables. 

3. Cost reduction

Improving internal business efficiency, while also helping to reduce operational costs and maintenance costs

4. Customer experience

Solving customer pain points and transforming the customer experience, while also helping customers contain costs

What are IIoT's business benefits?

In manufacturing, 63% of companies see IoT as a “strategic” path for competing more effectively with products and services, enabling companies to: 

1. Improve the business

IoT drives efficiencies within manufacturing organizations, boosting quality, throughput, yield, and constraint management. 

2. Make big data meaningful

IIoT is the foundation for enabling advanced analytics that will drive real-time decisions, both on the spot and across the organization.

3. Thrive in the digital economy

IIoT is a key enabler of innovation, digital transformation, and the development of new digital, customer-centric business models. 

What's a common IIoT project funding approach?

3 recommendations for successful IIoT project funding 

Understanding who initiates IoT projects — and, perhaps more importantly, who funds IoT projects — helps identify how to launch an ultimately successful project in your company. Here are some recommendations: 

1. Strategically budget projects

Increasingly, the majority of IIoT projects are budgeted, indicating that they are indeed part of the strategic planning process.

2. Scale your long-term investments

It is critical to consider the longer-term budget requirements of managing as well, maintaining, and expanding to include other endpoints and connected "things” over time.

3. Align IT and the lines of business 

Creating the link between the business needs and IT requirements early in the process will alleviate issues in the long term. 

To maximize its potential and deliver the greatest value to an organization, and AI IIoT initiative needs to incorporate an effective set of analytics services, with AI as a core component.

Below are a few requirements when starting AI IIoT Project.

1. Predictive maintenance is that the brightest showcase of AI utilized in IIoT. Predictive or perspective maintenance means a system powered by the machine learning algorithms can predict a requirement for maintenance on a plant floor. On top of that, AI can help in creating self-healing and self-calibrating IoT devices like sensors, inductors or transmitters. The biggest benefits that AI adds to the IIoT thanks to the described capacities are the reduction of maintenance costs
2. Manufacturing organizations are continuously looking for ways to increase productivity and operational efficiency. Looking at the new growing technology, the Industrial Internet of Things (IIoT), manufacturers are realizing that AI technologies are becoming a fundamental enabler of IIoT. AI provides factories not only with the ability to enable automation of tedious mechanical tasks but also the means to enable machines to “learn” and autonomously alert, improve, advise, and sometimes even make decisions regarding their own operation.
3. Ensure your company or the top user is committed to using the info. AI IIoT projects connect several devices to sensors and monitoring systems, collecting copious amounts of data. Making sense of the info and determining its value can take time. By finding end-users who are committed to using the info, willing to help with funding, implementing procedures to use the info, and informing management of the results, ensure your AI IIoT project will succeed
4. Having a stable and secure network is essential to having a successful AI IIoT system. Due to the massive amount of knowledge being collected and therefore the increased number of users on your network, having an outdated system can hamper your growth.
5. Do not get distracted with the numerous buzzwords and hype created by the AI IIoT community. There are tools being developed all of the time, like fog computing or edge analytics, and it is often overwhelming. Focus first on developing basic systems (e.g., network connections) and implementing sensors before using cloud-based servers or fog computing
6. Reach out to your existing vendors for AI IIoT solutions. AI IIoT is an increasing business and there are several options for implementation methods, and technologies, which can make choosing one overwhelming.
7. The convergence of IT (information technology) and OT (operations technology) is fundamental to AI IIoT systems. This convergence will enable the secure and reliable movement of knowledge to users and applications beyond the plant floor. 

Ending the AI IIoT Project:

The end goal of any AI IIoT system is to identify the improvements resulting from your system. Work with your users to demonstrate to the company how the AI IIoT is improving the bottom line. Calculate the financial benefits and share this information with people who supported your initial project funding to demonstrate how initial investments didn't attend waste. This also helps to secure financial investments for developing your AI IIoT system in the future.