Automated Checkout

Deploy sensor fusion technology for an automated checkout that enables real-time insight about the products consumers are buying using the EdgeX Foundry* extensible framework.

Use Cases

• Authenticate and authorize different users.
• Develop add-on services and sensors.
• Recognize items, detect discrepancies, and record real-time data.

Line Monitoring

Apply the pretrained models in the Intel® Distribution of OpenVINO™ toolkit to detect and count the number of people waiting in lines in real time.

Use Cases

• Infer crowd information based on line size and historic data.
• Generate insight and provide recommendations based on historic line size information.

One Way Direction Monitor

Detect shoppers and determine their walking direction. Get alerts for shoppers walking opposite to the predefined direction.

Use Cases

• Analyze walking patterns and provide recommendations.
• Implement social distancing guidelines in retail markets.

Real-Time Sensor Fusion for Loss Detection

Detect loss at self-checkout by seamlessly connecting different sensor devices, including weight scale sensors, cameras, and RFIDs.

Use Cases

• Recognize products entering and exiting retail checkout areas.
• Develop add-on services and sensors.
• Use multiple edge sensors to accurately recognize items, detect discrepancies, and record a real-time transaction log (RTTL).

Shopper Gaze Monitor

Build a solution to analyze customer expressions and reactions to product advertising collateral that is positioned on retail shelves.

Use Cases

• Measure active versus inactive user product engagement.
• Capture analytics on shopper reactions to visual ads.

Shopper Mood Monitor

Detect the mood of shoppers as they look at a retail or kiosk display.

Use Cases

• Mall shoppers using interactive or map kiosk
• Grocery store shoppers viewing digital signage ads
• Hospitals using a kiosk to assist patients or visitors

Smart Retail Analytics

Use computer vision inference in the Intel® Distribution of OpenVINO™ toolkit to provide analytics on customer engagement, store traffic, and shelf inventory.

Use Cases

• Detect people within a designated area by displaying a green bounding box over them, count the total number of people, and the time they are in the frame.
• Use an inferencing pipeline to detect faces, emotions, and head poses.

Social Distance Detection

Build a solution that recognizes people within a specific area and measures the distance between them. Get an alert if the distance is less than a specified amount.

Use Cases

• Measure the distance between shoppers in malls and retail stores.
• Generate insight for contact tracing based on social distancing data.
• Understand retail store capacity to maintain safe social distancing.

Store Capacity

Find people who cross a virtual line and determine whether they are entering or exiting a store. Count the unique shoppers and then display the current store occupancy.

Use Cases

• Review people entering and exiting retail checkout areas.
• Ensure the store occupancy does not exceed a predefined limit.
• Infer crowd information based on history of store capacity.

Store Traffic Monitor

Monitor three different streams of video that count people inside and outside of a facility. This application also counts product inventory.

Use Cases

• Movement of people
• Foot activity in retail or warehouse spaces
• Inventory availability of products on shelves

Brain Tumor Image Segmentation

Segment brain tumors in raw MRI images by applying the U-Net architecture.

Use Cases

• Detect brain tumors in MRI images.
• Plot predictions from segmented brain tumors.
• Predict results using a pretrained model and the Sørensen–Dice coefficient.

Pneumonia Classification

Detect pneumonia in X-rays using computer vision inferencing and a pretrained model.

Use Cases

• Predict the probability of infection caused by pneumonia.
• Identify anomalies and predict results with medical imaging.
• Train models for classification using labeled X-rays from open-source datasets.

Motor Defect Detector

Predict performance issues with manufacturing equipment motors. Perform local or cloud analytics of the issues found, and then display the data on a user interface to determine when failures might arise.

Use Cases

• Machinery
• Air conditioning units
• Refrigerators

Concurrent Video

Create a concurrent video analysis pipeline featuring multistream face and human pose detection, vehicle attribute detection, and the ability to encode multiple videos to local storage in a single stream.

Use Cases

• Retail digital surveillance such as network video recorders
• Video matrix commercial multimedia applications
• Video conference multipoint control units (MCU) and terminals

Intruder Detector

Build an application that alerts you when someone enters a restricted area. Learn how to use models for multiclass object detection.

Use Cases

• Record and send alerts on activity in controlled spaces.
• Track parking lots, entrances, and property.

Network Video Recorder

Implement and use Intel® hardware platforms for video decoding, encoding, and optimization using various media stacks.

Use Cases

• Transmit video into a computer vision application for people detection.
• Use GStreamer* and the Intel® Media SDK to capture video streams and encode them into a format that can be stored on a server.

Parking Lot Tracker

Receive or post information on available parking spaces by tracking how many vehicles enter and exit a parking lot.

Use Cases

• Track and analyze vehicle activity.
• Report on parking space availability.

People Counter System

Create a smart video application using the Intel Distribution of OpenVINO toolkit. The toolkit uses models and inference to run single-class object detection.

Use Cases

• Track activity in retail.
• Observe factory work spaces and building entrances for activity.
• Capture and record information on the number of people.

Restricted Zone Notifier

Secure work areas and send alerts if someone enters the restricted space.

Use Cases

• Track worker activity in proximity to heavy machinery.
• Develop safety solutions using computer vision technologies.

Safety Gear Detector

Observe workers as they pass in front of a camera, identify them using facial recognition, and determine if they have adequate safety protection.

Use Cases

• Ensure safety in the industrial workplace.
• Detect the presence of required safety equipment.
• Monitor factories, warehouses, etc.