There is no doubt, that AI (Artificial Intelligence) and IoT (Internet of Things) move business further. AI helps to make better decisions and complete work faster through data analytics and automation, while IoT enables real-time monitoring and management of physical assets and systems.
The impact of these technologies on the global economy is staggering. According to a report by McKinsey, AI has the potential to create between $3.5 trillion and $5.8 trillion in annual value across nine business functions in 19 industries. For instance, in the manufacturing sector alone, predictive maintenance enabled by AI and IoT could reduce machine downtime by up to 50% and increase machine life by 20-40%, according to a study by PwC.
Moreover, the synergy between AI and IoT, often referred to as AIoT (Artificial Intelligence of Things), is creating even more powerful solutions. IDC predicts that 50% of AI investments will be linked to IoT as companies recognize the value of combining these technologies. From optimizing operations and reducing costs to enhancing customer experiences and driving innovation, the possibilities are vast and varied across industries.
In this blog post, we'll explore how combining AI and IoT is revolutionizing business processes, examine real-world case studies of successful implementations, and discuss the challenges and considerations companies must address when adopting these transformative technologies.
Understanding IoT and AI
We can bet you have heard about AI more than a dozen times in recent years. Globally, the idea of artificial intelligence is to replace human intelligence by creating smart systems that learn from the data you give to them. As a result, such software solutions draw conclusions and decisions based on the data analytics results. Systems with AI algorithms can think, solve problems, adapt to new situations, and do all this without human intervention.
In short, IoT is a network of physical objects. Data exchange between these objects takes place over the Internet and requires the integration of smart sensors, software, and other technologies. The goal of the received IoT ecosystem is simple: to connect and control IoT devices present in the network. And do it remotely if needed.
IoT with AI (or AIoT) creates smarter software systems because of deeper data analysis and autonomous solutions. IoT devices collect huge amounts of data in real time, which is then given to an AI system. AI technology processes this data using machine and deep learning algorithms to recognize trends and anomalies. This allows businesses to get predictions automatically.
To illustrate how it happens, let’s break an example of artificial intelligence of things:
- Data gathering. Connected devices collect large amounts of data. For example, a smart refrigerator can track what and when you put in it.
- Data analysis. This is where artificial intelligence comes into play. It analyzes data, looking for patterns and trends. If your refrigerator often notices that you buy milk every two weeks, it can learn to predict this.
- Decision-making. Based on data analysis, AI can make decisions and recommendations. In our example, the smart fridge might alert you when it’s time to buy more milk or even place an order automatically.
- Learning. AI algorithms can help automate certain processes. A smart thermostat will adjust the temperature according to your preferences and schedule, rather than adhering to preset programs.
That is, internet of things artificial intelligence connection is that artificial intelligence trains IoT devices to recognize better the data and requests they receive and respond to them.
Practical benefits of AI and IoT
MordorIntelligence defines the need to better process huge datasets and reduce downtime and maintenance costs as two main drivers of increased IoT and AI market size (it's predicted to reach USD 115.31 billion by 2029). How exactly do these technologies cover these challenges, and what other benefits can you get? Keep reading to find out the answers.
Improved Productivity
Probably, the most evident benefit here is automation. For example, field service automation solutions reduce the time to complete time-consuming, repetitive tasks and increase the company's productivity. Nor can they stay competitive.
AI IoT architecture performs automatically and lets your talents focus on other, more strategic business activities. Moreover, the AIoT technology integration can give you a hint on how to improve specific operations. For example, it can suggest how to adjust the cargo route to deliver goods faster or reduce harmful emissions into the atmosphere.
Better Data Processing and Analysis
Making sense of data quickly and efficiently is difficult. This is why IoT devices alone cannot bring maximum value to businesses. AI algorithms review and analyze large datasets produced by IoT.
Thus, speed is a significant advantage here. For instance, AI powered IoT devices in an automotive factory must quickly and accurately read and transfer data from IoT sensors to determine the position of the engine, and the installation location, and check that all components are in place. Artificial intelligence processes this data in real time, making decisions about correcting the position or detecting any deviations from the standards. But at the same time, your sensor data processing results remain clean and accurate.
Minimized Downtime and Costs
An hour’s downtime in the oil and gas enterprise will cost approximately $500,000. In the automotive industry, it will be more than $2 million. These stats from Siemens report show why companies are looking for a tech solution that will help avoid downtime and, thus, reduce costs. So, how do artificial intelligence and IoT solve this challenge?
The integration of IoT, artificial intelligence, and machine learning will help move toward predictive maintenance. IoT sensors embedded in equipment collect data and certain metrics, feeding this information to AI systems. These systems have machine learning algorithms to detect anomalies and predict potential failures.
The Artificial intelligence of things thrives in environments where tasks are repetitive, and risk levels are hard to manage. For companies, this is crucial because any errors have minimal impact. This synergy transmits data from IoT devices to make accurate predictions, assuming that future conditions will sense real world conditions and mirror historical data.
AIoT applications across industries
In a nutshell, there are two primary methods for businesses to benefit from integrating AI and the Internet of Things. The first is to develop solutions that enhance product and service offerings, leveraging real-time data transmission and automation. The second is to create custom systems aimed at addressing specific internal challenges and improving operational efficiency. In this section, we will explore four examples where AI and IoT development services illustrate these potential advantages.
Manufacturing
Like many other industries, manufacturing benefits from IoT AI through the acceleration of industrial tasks and, thus, better operational efficiency. For example, a smart chocolate factory utilizes Siemens' AI capabilities to oversee humidity, temperature, and machinery conditions. This helps promptly identify and fix malfunctions.
The artificial intelligence of things, along with transparent data storage, real-time analytics, and industrial automation, enables hardware independence for smart factories. This allows manufacturers to save time and costs while enhancing employee safety.
Logistics
The AI for logistics can help monitor traffic flow, shipments, and transport equipment during transit. For this, IoT devices such as sensors, activity trackers, and programmable gadgets are installed in the trucks carrying goods. These devices transmit accurate GPS data to the business' cloud system. As a result, logistic companies can determine the location of cargo in real-time.
For instance, Maersk (a container transportation and shipping operator) has teamed up with Microsoft's Azure services to upgrade its offerings and make the customer experience better. By implementing IoT artificial intelligence solutions, the company has integrated multiple devices and accessed extensive datasets for better service and IoT data management and analytics. This tech solution provides real-time updates on shipments and monitors weather conditions, while cloud computing simplifies obtaining the data.
Healthcare
With IoT and AI in healthcare, medical institutions can better monitor people's health and make preventive recommendations. AIoT medical devices can be used for both physical and remote healthcare.
For example, Fitbit fitness trackers incorporate artificial intelligence algorithms to analyze biometric data and extract valuable insights. They monitor various patient data (such as heart rate, sleep patterns, and physical activity) to make it easier for doctors to track health conditions. The data generated from wearable devices helps doctors determine when to intervene and prescribe specific treatments.
Retail
You can add IoT artificial intelligence cameras with computer vision capabilities to your store. This will identify customers as they walk in. The artificial intelligence system can recognize customers, classify their characteristics, and collect key signals of their behavior in the retail space. Based on the insights gathered, it will be easier for your marketing department to draw conclusions on how to improve the shopping experience for different demographic groups.
An example from Amazon demonstrates another option for implementing AI and Internet of Things in smart retail. Its stores use AI cameras and sensors to detect what items shoppers take from shelves. Customers simply walk out with their items, and their accounts are automatically charged. This eliminates the need for traditional checkout lines.
These AIoT applications serve as inspirations to get your IoT journey with AI development solutions started. But, to build what your business wants and needs, you'll likely need to experiment with various ideas, assess their effectiveness, and adjust your goals accordingly.
Challenges and security concerns
Consider this: the cost of cybercrime is projected to attain $10.5 trillion by 2025, according to the “2022 Cybersecurity Almanac.” Implementing cybersecurity practices now will safeguard your artificial intelligence of things integration project from these significant future financial losses.
Here are three AIoT security issues you may face and ways to address them:
#1. Data Privacy and Protection
As we said earlier, IoT devices collect vast amounts of sensitive data used by AI algorithms to make valuable conclusions. However, this information is a prime target for cyberattacks. Unapproved access can result in data breaches, revealing personal information and compromising user privacy.
Solutions:in
- Use strong encryption protocols both for data at rest and in transit.
- Implement end-to-end encryption to make sure that data generated by AI in IoT devices is protected from the point of collection to its storage and processing.
#2. Device Authentication and Authorization
IoT networks consist of different devices connected to each other. You need to ensure that all of them have secure authentication and authorization controls. Failure to do so could allow attackers to gain unauthorized access or tamper with IoT networks.
Solutions:
- Adopt robust authentication methods (e.g. MFA) and digital certificates to authenticate user identities.
- Implement granular access controls and regularly review and update device permissions.
#3. Vulnerability Management
IoT devices are likely to be deployed with embedded software that may contain vulnerabilities. When integrated with AI systems, these weaknesses can be exploited to inject malicious commands or tamper with the data used by machine learning models. This will lead to erroneous outcomes or system failures.
Solutions:
- Establish a comprehensive vulnerability management process that includes regular software updates and patching for IoT devices.
- Implement real-time monitoring and threat detection systems.
- Employ cybersecurity measures to protect your Infrastructure from flaws.
#4. Scalability and Interoperability
Scalability refers to the ability of a system to increase or decrease its resources in response to changes in workload. In the context of AIoT, this means that your solution must be able to add new devices, process larger amounts of data, and execute more complex algorithms. And do it without significant crashes or performance degradation.
Interoperability, in turn, means that various systems, devices, or software can communicate and exchange data accurately. This is important since your IoT devices can be produced by different manufacturers.
Ignoring scalability issues can lead to fragmented systems with inconsistent security measures, making them more vulnerable to attacks.
Solutions:
- Remember about designing a scalable IoT infrastructure from the ground up.
- Adopt standardized protocols to ensure interoperability between different IoT devices and platforms.
The security of artificial intelligence of things is critical for both system integrity and user confidence. With robust security measures, you’ll mitigate risks and protect sensitive data streams from potential breaches, or ensure that your systems operate smoothly without vulnerabilities.
The future of AI and IoT
Statista predicts that the number of IoT devices will reach 32.1 billion by 2030, which is twice as many as in 2023. It's worth noting that this figure includes more than just computers and smartphones. Today, everything from razors to industrial machines can be connected to the Internet.
While companies will benefit from AI for IoT, general users will gradually become accustomed to a wider range of connected devices. Below, we explain which technologies will develop in the near future and how they will affect the spread of IoT.
- Edge Computing
It’s a method of processing data directly on or near the device, instead of sending the data to remote servers for processing. Besides speeding up data processing, this technology also reduces network load. With edge analytics, IoT devices will respond more quickly to changes in the environment.
- 5G Integration
5G is a new standard of mobile communication. It provides ultra-fast data exchange, low latency and higher bandwidth compared to previous generations of networks. How does it affect AI and IoT systems?
Well, it makes it easier to connect a large number of IoT devices simultaneously. This is especially important for the expansion of IoT in areas such as smart buildings or manufacturing. High data transfer speed, in turn, enables real time data analysis by artificial intelligence.
- Smart Cities
AI and IoT can transform urban environments into smart cities. These cities will have interconnected systems for energy management, transportation, and public services. AI-driven IoT solutions can enhance the efficiency of public transport, reduce energy consumption, and improve overall quality of life.
Now, the big question: what’s the future of IoT and AI for businesses?
If you work in the agriculture sector, it will help you measure soil moisture, temperature, and other parameters. Armed with this data, you can train AI algorithms to calculate the optimal time to water and fertilize, as well as predict yields.
No matter which industry your business refers to, you will benefit from Robotic Process Automation (RPA). This is the automation of routine tasks with the help of software bots that perform the same functions as humans. This includes automatic form filling, data processing, and integration between different systems.
With IoT and AI, RPA is becoming more intelligent and adaptive. IoT devices provide accurate data that AI analyzes to create recommendations and automated rules. RPA uses these recommendations to perform tasks better.
Automobile manufacturers are turning to vehicle-to-vehicle (v2v) communications to reduce accidents, lower maintenance costs, and decrease the carbon footprint of journeys. Cars can share their position, speed, direction of travel, and detect hazards with nearby vehicles. This data exchange helps optimize driving, reducing wear and tear, emissions, and journey times.
For autonomous vehicles, this network of shared data is more effective than relying on a single car's vision. Additionally, vehicle-to-infrastructure communication, where cars connect with smart environmental sensors like traffic lights and pedestrian crossings, is becoming a significant investment area. Integrating IoT and AI, these systems enhance safety, efficiency, and user preferences, minimizing the need for human interaction.
Final thoughts
IoT and AI impact on business sectors is notable. Industries ranging from healthcare to manufacturing are already taking benefits from AI-enabled IoT applications.
For instance, predictive maintenance in manufacturing minimizes downtime and reduces costs by using AI to analyze data from IoT sensors. Similarly, artificial intelligence of things enhances human machine interactions, creating more responsive and adaptive systems in sectors such as smart homes and healthcare.
The pace at which AI and the Internet of Things are evolving means that those who delay integration risk falling behind. Understanding the intersection of IoT and AI and how they can be applied is essential for staying competitive.
Starting this journey may seem daunting, but fear not. When considering the integration of IoT and AI, consult with an experienced IoT/AI development company. At ElifTech, our teams have the skills to guide you through the complexities of AIoT development, as well as to provide consultation on AI development costs for your specific project.