The retail sector is in a phase where decisions made in-store require granular visual data. Understanding where customers dwell, how shelves get depleted, or how promotions are received depends on what can be captured and analyzed visually.
That’s why high-resolution cameras have begun to redefine how data is gathered on the shop floor. These cameras gather uncompressed, high-density data streams that form the basis for analytics tools powered by AI or edge computing. Their integration into retail robotics and fixed-rack systems opens up new paths for high-volume, real-time data capture without affecting image clarity.
In this blog, you’ll learn more about in-store analytics, why high-resolution cameras matter, and which sensor is an ideal pick for them.
What Are In-Store Analytics?
In-store analytics refers to the collection and interpretation of data captured within physical retail spaces. These insights help track operational patterns and customer interactions.
- Tracking stock levels and inventory gaps using shelf-mounted vision systems
- Validating promotion compliance across aisles and product categories
- Monitoring pricing discrepancies using cameras that capture shelf images and perform barcode decoding or OCR
- Studying customer behavior, movement, and dwell time across various zones
Typical monitoring technologies:
- Retail robots with multi-camera setups scanning shelves and promotional areas
- Fixed-position rack-mounted cameras covering endcaps and gondolas
- Handheld smartphones or camera-enabled devices, which can be useful for temporary audits but are constrained by labor costs and training needs)
Role of High-Resolution Imaging in Retail Analytics
Many in-store shelf analytics systems use periodic image capture as the primary data source. This is useful for operations that need scheduled audits of shelves or promotional zones. Mounted on a rail or a mobile robot, the cameras capture sequences that serve as input for vision-based systems trained to read barcodes, recognize products, and identify restocking requirements.
High-resolution imaging upgrades the quality of this data by increasing the detail available within a single frame. With greater pixel density, analytics tools gain access to sharper image elements such as fine-print on tags, tiny barcodes, and product identifiers, even in low ambient light. Moreover, higher resolution makes it possible to cover wider sections of shelving in each frame, reducing blind spots and improving scan coverage in fewer passes.
Why AR2020 Is the Perfect Sensor for Retail Cameras
The onsemi Hyperlux LP family includes the AR2020, a sensor engineered to handle high-resolution imaging for embedded vision use cases. With a native output of 5120 × 3840 (~20MP), this sensor captures expansive views with clarity, making it well-suited for shelf and pricing analytics.
The sensor’s 1/1.8-inch optical format helps in producing images with more visible detail, even under subdued lighting. This quality becomes critical for shelf scanning and price validation, especially in environments where lighting conditions vary across aisles. The AR2020 supports uncompressed image output, which feeds raw data to analytics platforms without distortion.
While mobile devices might feature cameras with comparable megapixel counts, the smaller pixel size in such devices leads to lower light absorption. Their compact lenses also reduce field depth and optical flexibility. These trade-offs make them less dependable for applications requiring clear images across multiple shelf layers or wide gondola views.
The AR2020’s pixel density allows systems to capture clear data points at both macro and micro levels. It supports high-fidelity barcode decoding, text extraction through OCR, and tag reading even from ESLs with fine-print fonts. With correct lighting, shelf content analysis can reach product-level granularity.
Other Advantages of the AR2020 Sensor for Retail Cameras
Focus configuration
Both fixed-focus and autofocus options are available. Fixed focus serves static installations where distance remains constant, while autofocus supports mobile units that require variable depth coverage.
Lens compatibility
The M12-based voice coil motor (VCM) setup enables flexible use of M12 lens configurations to support varying imaging distances and field-of-view requirements.
Interfaces
The AR2020 supports integration over USB and GMSL interfaces. These options help designers embed the sensor into a variety of data capture platforms, from handheld devices to retail robots and fixed installations.
Recommended High-Resolution Cameras for Retail Analytics
NileCAM200 – 20MP AR2020 GMSL2™ Camera Module
This high-resolution GMSL2 camera module by e-con Systems features the AR2020 sensor, optimized for applications that need long cable support and noise-resistant video transmission. It works great for mobile robotic deployments where the camera needs to operate far from the processing unit.
See3CAM_CU200 – 20MP USB 3.2 Gen 1 Camera
e-con Systems’ high-resolution 5K camera is ideal for plug-and-play applications with embedded platforms like NVIDIA Jetson or x86 machines. It supports high-frame-rate streaming and produces uncompressed video output.
SHELFVista (20MP Variant)
Currently under development, this upcoming camera by e-con Systems will bring more AR2020 capabilities into a ready-to-use camera for shelf analytics in retail environments.
e-con Systems’ Cameras are Powering Retail Applications Globally
Since 2003, e-con Systems has been designing, developing, and manufacturing OEM cameras. We’ve collaborated with many retail clients to meet their imaging needs across shelves, checkout counters, and store aisles. Our portfolio includes cameras with GigE, MIPI CSI-2, and USB 3.1 interfaces, enabling smooth integration into both fixed and mobile platforms.
They come equipped with onboard image signal processing, strong low-light performance, and mechanisms to suppress image noise and manage LED flicker. They support bi-directional control functions and maintain stable transmission across long distances. With built-in features for object detection and recognition, they are perfect for retail applications.
Our camera solutions are compatible with leading computing platforms such as NVIDIA, Qualcomm, NXP, Ambarella, and x86-based systems.
Learn more about our retail camera expertise.
Go to our Camera Selector Page to see our end-to-end portfolio.
Need help in deploying the right high-resolution camera for your retail application? Please write to camerasolutions@e-consystems.com
Ranjith is a camera solution architect with over 16 years of experience in embedded product development, electronics design, and product solutioning. In e-con Systems, he has been responsible for building 100+ vision solutions for customers spanning multiple areas within retail including self service kiosks, access control systems, smart checkouts and carts, retail monitoring systems, and much more.