How IoT is embracing the potential of artificial intelligence

Over the past decade, the Internet of Things has seen steady adoption in the business world. Enterprises are already building or optimizing using IoT devices and their data capabilities, ushering in a new era of business and consumer technology. Now the next wave is coming, as advances in artificial intelligence and machine learning unlock the possibility of IoT devices leveraging "artificial intelligence," or AIoT.

Consumers, businesses, economies and industries that adopt and invest in AIoT can harness its power and gain a competitive advantage. IoT collects data and AI analyzes it to simulate intelligent behavior and support the decision-making process with minimal human intervention.

Why the Internet of Things Needs Artificial Intelligence

The Internet of Things allows devices to communicate with each other and take action based on these insights. These devices are only as good as the data they provide. To be useful for decision making, data needs to be collected, stored, processed and analyzed.

This creates challenges for organizations. As IoT adoption increases, businesses are struggling to efficiently process data and use it for real-world decisions and insights.

This is due to two issues: cloud and data transmission. The cloud cannot scale to handle all data from IoT devices, and transferring data from IoT devices to the cloud is bandwidth limited. Regardless of the size and complexity of the communication network, the vast amounts of data collected by IoT devices can lead to delays and congestion.

Some IoT applications rely on fast, real-time decision-making, such as self-driving cars. To be effective and safe, self-driving cars need to process data and make instant decisions (just like humans). They are not limited by latency, unreliable connections and low bandwidth.

Self-driving cars are far from the only IoT applications that rely on such rapid decision-making. Manufacturing already incorporates IoT devices, and delays or delays can impact processes or limit capacity during emergencies.

In terms of security, biometrics are often used to restrict or allow access to specific areas. Without fast data processing, there can be delays that impact speed and performance, not to mention risks in emergency situations. These applications require ultra-low latency and high security. Therefore, processing must be done at the edge. Transferring data to the cloud and back is simply not feasible.

Benefits of AIoT

Every day, IoT devices generate approximately 1 billion GB of data. By 2025, the global number of IoT connected devices is forecast to be 42 billion. As the network grows, so does the data.

As needs and expectations change, IoT is not enough. Data is growing, creating more challenges than opportunities. Barriers limit the insights and possibilities of all data, but smart devices can change this and allow organizations to unlock the true potential of their organizational data.

With artificial intelligence, IoT networks and devices can learn from past decisions, predict future activities, and continuously improve performance and decision-making capabilities. AI allows devices to “think on their own,” interpret data and make real-time decisions without the delays and congestion caused by data transmission.

AIoT brings a wide range of benefits to organizations and provides powerful solutions for intelligent automation.

(1) Avoid downtime

Some industries are hampered by downtime, such as the offshore oil and gas industry. Unexpected equipment failure can lead to costly downtime. To prevent this, AIoT can predict equipment failures in advance and schedule maintenance before serious problems occur on the equipment.

(2) Improve operational efficiency

Artificial intelligence processes the large amounts of data coming into IoT devices and detects underlying patterns more effectively than humans. Artificial intelligence with machine learning can enhance this capability by predicting operating conditions and modifications needed to improve outcomes.

(3) Enabling new and improved products and services

Natural language processing continues to improve, allowing devices and humans to communicate more effectively. AIoT can enhance new or existing products and services by allowing better data processing and analysis.

(4) Improve risk management

Risk management is necessary to adapt to the rapidly changing market environment. AI and IoT can use data to predict risks and prioritize ideal responses, improving employee safety, mitigating cyber threats, and minimizing financial losses.

Key Industrial Applications of AIoT

AIoT has revolutionized many industries, including manufacturing, automotive, and retail. Below are some common applications of AIoT in different industries.

(1) Manufacturing

Manufacturers have been using the Internet of Things for equipment monitoring. Going one step further, AIoT combines data insights from IoT devices with artificial intelligence capabilities to provide predictive analytics. With AIoT, manufacturers can take an active role in warehouse inventory, maintenance, and production.

Robotics technology in manufacturing can significantly improve operations. The robots are equipped with implanted sensors for data transmission and artificial intelligence, so they can continuously learn from data and save time and reduce costs during the manufacturing process.

(2) Sales and Marketing

Retail analytics takes data points from cameras and sensors to track customers’ movements and predict their behavior in brick-and-mortar stores, such as how long it takes to reach the checkout. This can be used to recommend staffing levels and improve cashier productivity, thereby increasing overall customer satisfaction.

Major retailers can use AIoT solutions to increase sales through customer insights. Data such as mobile-based user behavior and proximity detection provide valuable insights that can be used to deliver personalized marketing campaigns to customers as they shop, thereby increasing foot traffic to brick-and-mortar stores.

(3) Automobile

AIoT has many applications in the automotive industry, including maintenance and recalls. AIoT can predict malfunctioning or defective parts and can combine data from recall, warranty and safety agencies to see which parts may need to be replaced and provide customers with service checks. The vehicle ultimately gains a better reputation for reliability, and the manufacturer gains the trust and loyalty of its customers.

One of the most famous and probably the most exciting applications of AIoT is self-driving cars. With artificial intelligence powering the Internet of Things, self-driving cars can predict driver and pedestrian behavior in a variety of situations, making driving safer and more efficient.

(4) Health Care

One of the primary goals of quality health care is to extend it to all communities. Regardless of the size and complexity of the healthcare system, physicians are facing increasing time and workload pressures and spending less time with patients. The challenge of delivering high-quality health care while meeting the administrative burden is enormous.

Healthcare organizations also generate large amounts of data and record vast amounts of patient information, including imaging and test results. This information is valuable and necessary to improve the quality of patient care, but only if healthcare organizations can quickly access this information to inform diagnostic and treatment decisions.

Combining IoT with artificial intelligence has many benefits for these disorders, including improving diagnostic accuracy, enabling telemedicine and remote patient care, and reducing the administrative burden of tracking patient health in facilities. Perhaps most importantly, AIoT can identify critically ill patients faster than humans by processing patient information, ensuring efficient patient triage. ​

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