Smart Retail Solution
Enhancing an Extraordinary In-Store Shopping Experience by Adopting New Technologies
Introduction
Combining the disruptive technologies to provide an immersive shopping experience for the customers, while keeping the merchandise in a competitive position to stay ahead in the curve. Using the camera solutions, algorithms and analytics provided by Thundercomm to improve the customer satisfaction while increasing the profit of the retail store.
Camera Solution
Artificial Intelligence for Retail
Customer Service
Using the AI and analytics to learn more about your customer to serve them better.
- People Counting: Measure the conversion rate and arrange the staff accordingly
- VIP Recognition: Provide a personalized service to increase the loyalty
- Heat Map: Learn which area is attractive to your customer and optimize the floor layout
- Purchasing Behavior Analysis: Identify your target audience accurately
Product Monitoring
- Object Recognition: Ensure the shelf is stocked with the right product
- Object Detection: Remind when the shelf is empty
- Electronic Tag: Update the price whenever you need
- AGV: Fulfill the stock in a timely manner to let the staff focusing on the customer service
Store Management
Digitizing the brick-and-mortar store to improve the operational efficiency.
- Smart POS: Manage the sales and inventory efficiently
- Digital Signage: Display digital ads to maximize in-store product marketing
- Kiosk: Free up your staff and leave a place for relaxing
- VR: Create an interesting shopping experience and give fun to your customers
Retail Platform
SOM | C2290/CM2290 | C450/CM450 | C6125/CM6125 | D845 | C5165 |
---|---|---|---|---|---|
Platform | Qualcomm® Snapdragon™ QCS2290 Qualcomm® Snapdragon™ QCM2290 | Qualcomm® Snapdragon™ SDA450 Qualcomm® Snapdragon™ SDM 450 | Qualcomm® Snapdragon™ QCM6125 Qualcomm® Snapdragon™ QCM6125 | Qualcomm® Snapdragon™ SDA845 | Qualcomm® Snapdragon™ QRB5165 |
Quad-core Arm Cortex-A53 ,64-bit, 2.0GHz | Octa-Core, 64-bit, 1.8GHz | Kryo260 CPU: 4xGold @ 2.0GHz + 4xSilver @ 1.8GHz | Kryo Octa-core, 64-bit, 2.6GHz | Kryo 585 Qualcomm® Adreno™ 650 GPU, Adreno™ 665 VPU, Adreno™ 995 DPU | |
Qualcomm® Adreno™ 702 GPU | Qualcomm® Adreno™ 506 GPU | Qualcomm® Adreno™ 610 GPU, Adreno™ DPU 851 | Qualcomm® Adreno™ 630 GPU | Qualcomm® Hexagon™ DSP with quad HVX | |
Qualcomm® Hexagon™ QDSP6 v66 | Qualcomm® Hexagon™ QDSPv56 | Qualcomm® Compute DSP with Hexagon™ Vector eXtensions (dual-HVX512), Audio DSP | Qualcomm® Hexagon™ 685 DSP | Qualcomm® Spectra™ 480 image processing | |
Memory | LPDDR4x 3GB/2GB + eMMC 16GB | LPDDR3 2GB+eMMC 16GB | LPDDR4x 2GB + eMMC 5.1 32GB | LPDDR4 4GB+UFS 64GB | 8GB +128G UFS |
OS | Android R(2021), Android S(2022), Linux(C2290 Only) | Android 10 | Android 10 | Android 10, Linux | Linux |
Others |
Case Study
- High Accuracy: Hundreds of billions of data provide massive data support for deep learning model training, and continuously improve the recognition ability in customer scenarios
- Integrated Analytics:Intelligent analysis of multi-dimensional image information of people, goods, and stores through the “device-edge-cloud” synergy model. Also supports cross-system integration
- Better Experience: Snapshot recognition based on non-cooperative face recognition technology to avoid interference with customers and therefore improve user experience
- Improve customer experience
- Optimize store staff allocation
- Increase store operation efficiency
- Digitized store management