The Internet of Things (IoT) and 5G network technology have become ubiquitous, and the next frontier is the integration of artificial intelligence (AI) into these connected devices. This combination of AI, IoT, and 5G will bring about real-time capabilities and new possibilities. For example, imagine wearing an extended reality (XR) headset that not only provides a 3D view of an aircraft engine but also has on-board intelligence to identify and address any issues or anomalies in real-time. This is just one example of how AI running on edge devices can revolutionize various industries.
Chipmakers are already developing powerful yet energy-efficient processors, known as “systems on a chip,” that can handle AI processing within small devices. Qualcomm, for instance, recently announced AI-capable Snapdragon chips for smartphones and PCs. Additionally, researchers at the University of California San Diego are working on NeuRRAM chips, which can run substantial AI algorithms on smaller devices. These advancements in hardware will enable AI to be integrated into a wide range of IoT devices.
According to a recent analysis by zScaler, the global number of connected IoT devices is projected to exceed 29 billion by 2027, up from the current 16.7 billion. While consumer devices are the most common, the report highlights that business process-oriented IoT devices generate the highest number of transactions. Manufacturing and retail devices account for more than 50% of these transactions, indicating their widespread adoption and critical role in these sectors. Enterprise, home automation, and entertainment devices, on the other hand, generate the highest counts of plaintext transactions.
The convergence of 5G, IoT, and AI opens up new avenues for innovation. Arun Santhanam, Vice President and Head of Telecommunications at Capgemini Americas, emphasizes the importance of local-level decision-making and real-time data for AI to be effective. He believes that 5G’s low latency innovation will play a crucial role in enabling real-time data from inexpensive IoT solutions.
Most of the successful use cases for AI and edge computing have been in the enterprise and IoT space, particularly in healthcare and manufacturing. Haifa El Ashkar, Director of Strategy of the Telecommunications Market and Solutions at CSG, explains that these industries require faster data transmission and real-time communication. The lower latency and faster processing capabilities of 5G, coupled with edge architectures, are essential for applications that demand quick decision-making and responsiveness. In healthcare, for example, AI-edge-supported medical devices like laparoscopes enable surgeons to leverage real-time insights and make faster decisions, potentially saving lives. Such critical IoT use cases rely on 5G and edge networks to provide the necessary services.
AI-powered applications and services are also enhancing the capabilities of 5G edge applications. El Ashkar notes that the combination of 5G’s low latency and AI capabilities at the edge enables enterprises to access real-time decision-making. With reduced data travel time between devices and data centers, AI algorithms running on edge devices can provide real-time insights and actions, improving response time and increasing valuable data availability for businesses.
AI not only improves connectivity but also has a significant impact on the reliability and efficiency of wireless networks. Milind Kulkarni, Vice President and Head of InterDigital’s Wireless Lab, highlights the role of AI in empowering immersive experiences on new devices and enabling connected ecosystems like the metaverse. The combination of 5G, cloud, and edge computing is crucial for making these experiences a reality. While centralized environments like the cloud and data centers provide computing power for immersive experiences, they may be too far from low-latency resources. Edge computing, on the other hand, offers smaller amounts of storage and computation closer to the device, enabling ultra-low latency and customized support for specific use cases.
XR is an area where the capabilities of 5G are being pushed to their limits. Ongoing work within 3GPP is focused on enhancing current networks to better support XR traffic. XR applications require low latency, high data rates, efficient video coding, and network architecture, all of which can be achieved through the benefits of edge computing.
In conclusion, 5G and IoT technologies are paving the way for AI integration, while AI enhances the capabilities of these technologies. The combination of AI, IoT, and 5G will be crucial for industries to transition into the next stage of digital transformation. Supply chain, healthcare, and manufacturing industries, in particular, will benefit from the increasing adoption of AI-infused and connected devices in their daily operations. The future of AI and IoT is promising, and it is only a matter of time before we witness the full potential of this convergence.