IoT Insider editor Kristian McCann speaks with Houman Zarrinkoub, Principal Product Manager at MathWorks, on the pivotal role AI wields within the realm of wireless communication as a triad of techniques, notably within wireless communications, and how machine learning, deep learning, and reinforcement learning can be harnessed to tackle the intricate design challenges wireless communication systems present.
“The role of AI in advancing wireless technology isn’t limited to analytics,” Zarrinkoub said. “it’s fundamentally redefining how networks learn and adapt.”
The integration of AI into wireless communications heralds a transformative era for the industry, enabling smarter, more efficient networks that can learn, adapt, and make decisions autonomously. AI-driven wireless systems are poised to revolutionise how data is managed and transmitted, facilitating rapid, real-time processing and enhancing the reliability of connections. Yet the benefit, Zarrinkoub highlights, AI is the ‘linchpin’ of next-gen wireless systems. By leveraging AI’s capabilities, wireless networks can anticipate user behaviour, allocate resources more effectively, and introduce higher degrees of customisation and security, thereby optimising the overall user experience. This synergy between AI and wireless communications can therefore reshape the very fabric of connectivity for the burgeoning IoT, industrial automation, and beyond.
When applying to IoT, Zarrinkoub goes on to say how AI in wireless communications may not just be a benefit but is almost necessary for the implementation of ideas integral to the IoT story – like smart cities. “Incorporating AI into wireless systems is no longer optional but a prerequisite,” says Zarrinkoub. “as achieving the level of sophistication demanded by future IoT ecosystems will require it.”
In smart cities, AI can optimise traffic flows in real-time by processing data from a myriad of sensors, reducing congestion and pollution. Furthermore, energy consumption can be intelligently managed in real-time across grids, with AI harmonising demand and supply, leading to more sustainable living. These examples underscore the profound impact AI is likely to have on the operational efficiency, reliability, and advancement of IoT applications.
In the podcast, Zarrinkoub goes on to discuss which industries AI wireless and IoT could come to be most effected, the challenges AI faces in implementation into wireless networks, and how AI is transforming wireless networks now.
To hear more about the AI in wireless communications and its potential benefits for IoT, you can listen to IoT Insider’s podcast with Houman Zarrinkoub on IoT Unplugged – available below, on Spotify or Apple Podcasts.
AI in wireless communications and its effects on IoT – IoT Unplugged
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