Top organizations like Amazon, Netflix, and Microsoft continually benefit from smart technologies like Artificial Intelligence (AI) and the Internet of Things (IoT).

AI is the ability of computer programs to perform tasks associated with humans. It involves the replication of human intelligence in systems and devices to enable them to think and behave like humans.

IoT describes a network of physical objects around us with sensors, software, processing ability, and other technologies that enable them to connect and exchange data with other devices over the internet.

While AI and IoT come with their unique contributions to digital transformation, there are more benefits for companies to enjoy with a combination of both. In this article, we'll explore some of these benefits.

What Does AI Blended with IoT Mean?

AI blended with IoT refers to the integration of AI technology with gadgets that can network or connect over the internet. This combination is called Artificial Intelligence of Things (AIoT).

AI in IoT works to improve the efficiency of IoT systems through Machine Learning (ML) and Deep Learning (DL).

Machine learning is an AI function that allows computers to analyze a series of data and learn from it to produce precise outcomes. Deep Learning is a subset of Machine Learning which trains the computer to think like the human mind and solve more complex problems.

So, with Artificial Intelligence, IoT devices can collect data, analyze it, and use the acquired information to simulate smart behavior. And, support the decision-making process with minimal human intervention.

5 Benefits of AI-enabled IoT

In today's world, many more things are being connected through the internet, and it is estimated that by 2025, over 75 billion connected devices will be in use.

AI in IoT will be beneficial to all areas of human activity, such as business, government, and health. In the business world, for instance, activities like marketing can be greatly improved by AI. You can use AI to create collateral for your SaaS marketing channel or ecommerce website. You can even use it to generate leads or in digital ad placements.

Now, let's examine some benefits of AI in IoT.

1. Improves Operational Efficiency

AI processes huge volumes of data received by interconnected devices and identifies similarities in patterns faster and more accurately than humans.

AI in IoT can be used to maximize time, resources, and effort while producing high-quality services and products.

To improve efficiency in a company, AI employs many steps, one of which includes data preparation. As IoT devices collate data, several unimportant data are also collected. So, the AI in IoT can sift through and select useful data, then present insightful information for operational efficiency.

AI in IoT also helps optimize data labeling. This involves adding tags, labels, or names to raw information so that a machine-learning program can understand and use the information. These tags describe the data type and cite the various attributes of the data point. This way, the AI in IoT learns to identify the object when it meets such data in the future.

After data labeling, the next step you should think about is data cleaning. To achieve this, your company can use tools like MATLAB to quickly clean already labeled data for input into ML models.

Here is an example of a data-cleaning process.

 

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To reduce redundancies, AI will need to import your data, remove duplicated and irrelevant data, analyze the imported data, and standardize the data to check for quality data. These functions can take humans eons to accomplish.

Additionally, going by Mellanox Technologies' prediction, networking IoTs will take clouds to new levels of efficiency. Therefore, engineers who harness AIoT can achieve higher levels of operational efficiency.

Engineers can select from various experiment managers, such as Illumina Experiment Manager, NVIDIA, Siemens' Tecnomatix Plant Simulation, and Eppendorf, to track the effectiveness of their iterations on the model.

2. Predicts a Broad Range of Risks

Business risks are uncertainties or unexpected events that may be beyond the control of the businessman, leading to a loss. According to Investopedia, entrepreneurs face multiple risks including bankruptcy, competitive risks, and economic risks. Below is an image showing possible risks companies can face.

 

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AIoT does not only enable your company to predict business risks; it also simulates and facilitates your company's response to these risks. That is to say, AI-blended IoT can enable companies to handle these risks better when they occur.

For instance, a company can use AI-blended IoT to ensure employee safety at the workplace. This is epitomized by Fujitsu, which equips its workers with wearable smart devices that are connected to a central database. These devices collect data, such as location, temperature, and wearer's vital signs, and transmit these to a central point for processing and analysis.

If one parameter of a worker's vital signs, such as heartbeat or blood pressure, is getting to a dangerous level, AI-enabled virtual assistants can alert the worker ahead of time. If an accident occurs at the workspace, responding doctors can easily look at a screen, which monitors vital signs, and know exactly what treatments to administer.

AIoT can provide insight and reliability to help predict a broad range of risks with continuous synthetic testing on cloud-based applications such as Kubernetes.

3. Creates New Products and Enhances Existing Ones

AI can assist in creating new products and in enhancing existing ones. For instance, AIoT can help UI/UX design companies in automating tasks and speeding up prototype development.

Also, product designers have turned to AI in a bid to streamline their company's production line and monitor how their audience will interact with their product.

The graph below shows that 51% of executives use AI to enhance the features of their products, and 32% of the surveyed executives use AI to develop new products. This amounts to 84% of modern executives using AI in creating and enhancing the functionality of their products.

 

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According to TechCrunch, AI-powered IoT is impacting DevOps software remarkably. While AI doesn't write codes, it reduces the number of keystrokes developers need to type by half. AI can also catch bugs even before code testing and automatically generate half of the tests needed for quality assurance.

Forbes also reveals that 40% of DevOps will be using application and infrastructure monitoring apps that have integrated AI by 2023. This use of AI Machine Learning has helped accelerate the Software Development Life Cycle (SDLC) and the quality of end products.

Additionally, Oracle has released the VirtualBox 7 to help developers increase productivity and reduce operational costs and complexity, thereby enabling the creation of new products at a cheaper rate.

4. Predicts Equipment Failure

AI-enabled IoT transmits data that have specific benchmarks about how much stress or pressure a piece of equipment is built to withstand. This can enable companies that are operating on reactive maintenance to better detect equipment failure and switch to predictive maintenance.

Below is a flowchart from MaintainX showing the procedure for AI in IoT to predict equipment failure.

 

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According to a study by Deloitte, equipment with sensors can monitor certain metrics constantly and send real-time alerts as soon as potential problems and specific thresholds are crossed. If a human is meant to check for such data, there can be up to 24 hours of time lag before an issue is detected.

Finally, at an advanced level, AI in IoT can use previous data to generate failure predictions. With AI, organizations can run regular diagnoses on the equipment they use. Management and engineers can then use these analyses to implement preventive maintenance of machines before a piece of equipment fails.

5. Helps Schedule Orderly Maintenance

For a large-scale manufacturer operating numerous machines, AI can help you schedule your maintenance in an orderly manner by using historical data.

Below is a chart showing the effect of AI on project schedule management.

 

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It can be seen from the chart that 52% of surveyed managers reported AI as having both a high effect and a very high effect when developing a schedule. We can say the same when it comes to developing a maintenance schedule.

For instance, AI scheduling software can help create a fair share of shifts among workers to reduce burnout while also considering staffing responsibility.

Maintenance teams can also benefit from AI in numerous ways. Some of these ways include using collaborative robots (cobots) to manage your company spreadsheets and other administrative work.

In Closing

AIoT can offer innumerable benefits to companies. Together AI and ML deliver numerous benefits for a wide range of companies.

AI in IoT can help companies improve how they operate while predicting a broad range of risks. While enabling product designers to create new products, it also enhances older products that are already in use. Also, scheduling orderly maintenance of equipment can be made easier by engaging AIoT.

These benefits can help companies compete favorably in the real world. Data collection and analysis can be an uphill task for humans with billions of data to sift through. AI with ML can carry out these tasks at a more efficient and cost-effective rate. It can be safely inferred that companies that engage in AI-enabled IoT will see better performance across all their functions, thereby resulting in a better ROI.

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ABOUT THE AUTHOR

Nico is the founder of Crunch Marketing. The company works with enterprise SaaS clients, helping them scale lead generation globally across EMEA, APAC, and other regions.