At the ISC West 2026 exhibition, Qualcomm systematically showcased the latest progress of its AI Camera Platform. As the industry transitions from "video capture" to "intelligent perception and decision-making," cameras are becoming one of the most important AI sensors in the physical world and are gradually integrating into broader intelligent systems, including core scenarios such as autonomous driving, industrial vision, and smart cities.
Traditional security focuses on the performance of a single device, while the competitive focus in the AI era is shifting towards "scalable intelligent capabilities." Companies are no longer solely concerned with camera resolution or night vision capabilities; they are paying more attention to whether AI capabilities can be rapidly replicated and continuously evolved across tens of thousands of devices.
Qualcomm's proposed solution is to achieve system-level scaling of AI capabilities through a "chip + software + platform" collaborative architecture:
The core value of this architecture lies in transforming AI from a "point capability" into "scalable productivity."
Three Technical Pillars: Building a Complete AI Vision Ecosystem
Centered on the large-scale deployment of AI cameras, Qualcomm has built a system of three core capabilities:
Through a SoC product line covering different performance tiers, it achieves comprehensive coverage from entry-level cameras to high-end multi-sensor systems, balancing performance, power consumption, and cost.
An integrated AI development toolchain allows developers to quickly complete model training, deployment, and optimization, significantly lowering the barrier to AI application development and accelerating time-to-market.
Through local inference and edge computing, it enables low-latency, privacy-protecting intelligent video analytics. It also supports collaborative capabilities from device to cloud, promoting a business model upgrade from "hardware sales" to "service operations."
The capabilities of AI cameras are rapidly expanding into more scenarios, with autonomous driving being the most representative.
An autonomous driving system is essentially a complex system of "multi-sensor fusion + real-time decision-making," and its core capabilities are highly similar to those of AI cameras:
As technological integration accelerates, AI cameras and in-vehicle vision systems are sharing the same technological foundation. In this process, a critical issue is becoming increasingly prominent: connectivity.
Key Infrastructure: Wireless Connectivity Becomes a Core Capability
Whether for intelligent security or autonomous driving, system requirements for communication capabilities are significantly increasing:
This makes "high-bandwidth, low-latency, high-reliability" wireless connectivity transform from a supplementary function into the fundamental infrastructure for system operation.
QOGRISYS Accelerates the Deployment of AI Vision and Autonomous Driving
Amid this industry trend, QOGRISYS leveraging its mature overall product solution capabilities, has launched the 02072PB Wi-Fi 7 module for AI vision and autonomous driving scenarios.
This module not only meets the demands for high-throughput data transmission but also excels in stability and low latency. It can be widely used in AI cameras, intelligent cockpits, autonomous driving systems, and industrial vision equipment, helping customers bridge the "last mile" from chip capability to end products and accelerating the process from solution verification to large-scale deployment.
From AI cameras to autonomous driving, from single-device intelligence to system-level collaboration, the industry is moving towards a new stage of "high computing power + strong connectivity." With chips as the foundation, modules as the carrier, and solutions as the bridge, communication capabilities will become the key engine driving the large-scale deployment of intelligent systems.
Related Video: ISC West 2026 Exhibit Hall Tour
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