In this episode of IoT Unplugged, host Caitlin Gittins speaks with Eric Mazzoleni, Vice President, Industrial and Embedded IOT Sales Europe at Qualcomm Germany.
The podcast aims to explore Qualcomm’s approach to simplifying Edge AI for customers and empowering a wide spectrum of IoT-driven applications across industries.
Mazzoleni provides a contextual overview of Qualcomm, highlighting its 40-year legacy as an innovator in mobile technology and its strategic expansion into diverse markets such as automotive, extended reality (XR), and especially Industrial IoT. Mazzoleni underscored Qualcomm’s technological leadership, notably in compute, connectivity, and artificial intelligence (AI), which collectively powers both consumer solutions (via the Snapdragon brand) and industrial offerings (under the Dragonwing brand).
The discussion shifts towards the concept of intelligence at the Edge. Mazzoleni explains the evolving technical landscape, where the necessity for decentralised compute power is increasing. He breaks down the hierarchy from Cloud computing to near-Edge infrastructure (like factory networks) and finally to devices at the far Edge. With more data generated by ubiquitous sensors and IoT devices, he describes how “intelligence at the Edge” facilitates real-time, localised analysis and decision-making, which is critical for applications such as predictive maintenance, machine-to-machine communication, and gradually, Generative AI. This evolution, Mazzoleni suggests, will empower autonomous workflows and adaptive systems – ranging from robotics in manufacturing to smart homes and energy grids.
The opportunities arising from Edge AI are explored. Mazzoleni cites the accelerating digital transformation across industries, including manufacturing, energy, retail, logistics, and home automation. He points out emerging use cases: from automated inventory management in retail to energy grid optimisation for smart homes, and the integration of AI into daily devices like fridges that can manage food inventories. He illustrates how Edge AI supports enhanced customer experiences and operational efficiency through automation and personalisation.
Mazzoleni also acknowledges significant challenges, notably the complexity and fragmentation of the Edge AI marketplace. Successful deployment, he stresses, relies on simplifying architectures and offering integrated, use-case-specific solutions. Qualcomm’s approach includes ready-made ‘curated’ solutions for sectors like oil and gas and deployment tools like AI Hub and Edge Impulse, which enable clients to build, optimise, and deploy customised AI models at scale.
Technical hurdles such as balancing compute performance, energy efficiency, and rapid inference times are also discussed. Mazzoleni highlights Qualcomm’s processors, which are designed to deliver scalable, energy-efficient AI from simple to highly complex devices.
Security and privacy emerge as foundational concerns. Mazzoleni describes Qualcomm’s Trusted Execution Environment, which ensures secure and private AI processing at the Edge – vital for sensitive applications in sectors like healthcare and industrial automation.
In closing, Mazzoleni advises companies to base their build-or-buy AI decisions on use case requirements, internal expertise, and time-to-market needs, emphasising the flexibility and scalability of Qualcomm’s industrial AI solutions.
To hear more about what Mazzoleni had to say about Edge AI, listen on Spotify, Apple Podcasts, and at the link below.
