AVT Question: Please share your insight on AI and the cloud's impact on Pro AV today and in the near future.
Thought Leader: Theresa Benson, Vice President of Product Management and Marketing at Mersive Technologies
The future of AI in AV is not just approaching; it’s here and evolving swiftly. If it’s not already obvious, AI is poised to revolutionize the AV field, making experiences more personalized, efficient, and immersive.
Imagine entering a room where an AV system recognizes a primary end-user and adjusts the lighting and sound to their preferences, compensating for the time of day, season, and location. Supervised machine learning models excel in this type of preference management, learning user behavior and then synthesizing it with larger datasets.
But AI’s role extends beyond science-fiction-sounding convenience to deliver other increasingly natural, intuitive interactions between users and technology. From assisting with acoustic adjustment based on room occupancy and purpose to offering real-time translations during interactions, AI-enabled systems can eliminate accessibility challenges and help AV teams deliver next-level experiences.
My hope is that our industry prioritizes the practical ways in which we can deliver more secure, inclusive, and human-centric experiences for our users." —Theresa Benson, Vice President of Product Management and Marketing at Mersive Technologies
The power of AI in AV comes from balancing edge AI and cloud AI. Edge AI processes data on things like IoT devices and wearables, which is crucial for applications where cloud connectivity introduces adverse latency. Cloud-based AI, on the other hand, excels in heavy-duty data analysis, like predicting behavioral and operational trends and providing a big-picture view for strategic decisions. This enables AV professionals to anticipate needs, plan for future events, and suggest upgrades—all grounded in actual data—making operations and maintenance more efficient and cost-effective.
However, with increasingly networked AV equipment, addressing new attack vectors is critical. AI can also assist here. When combined with robust security practices, AI can help protect AV systems against threats and misuse. For example, recurrent neural networks (RNNs) and anomaly detection models excel at analyzing various data types to detect irregularities and potential security threats.
As we enter this AI-enabled era of AV, the future holds incredible potential. My hope is that our industry prioritizes the practical ways in which we can deliver more secure, inclusive, and human-centric experiences for our users.
