Open Source Reference Implementations

Deploy your own IoT solutions by using these prebuilt open source projects.

Facial Recognition Access Control

Develop a facial detection and recognition solution using the Intel® Distribution of OpenVINO™ toolkit, C++, and MQTT to grant access to designated areas.

Use Cases

  • Control access to buildings.
  • Restrict equipment operation.
  • Enable security for authorized individuals.

Intelligent Classroom

Provide live classroom metrics, such as class attentiveness, participation, happiness index, and attendance without class disruption.

Use Cases

  • Detect the attentiveness of students in the classroom through head-pose estimation inference models.
  • Capture real-time classroom activity and determine attendance through action detection and facial re-identification.

Intelligent Digital Signage Solution

Use computer vision solutions to adjust kiosk displays in response to audience demographics.

Use Cases

  • Determine age, gender, and head pose with deep neural network (DNN) models.
  • Play a 4K ad based on audience identification.

Machine Operator Monitor

Send notifications when an employee appears to be distracted while operating machinery.

Use Cases

  • Industrial or manufacturing facilities
  • Construction sites
  • Warehouses

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

 

 

 

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.

Store Aisle Monitor

Capture video, generate a heat map, record the number of people present, and then integrate the results. The program can also create an output video and save snapshots.

Use Cases

  • Factory or warehouse activity
  • Restaurant activity
  • Hospital lobbies and floors

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.

Industrial Anomaly Detection

Run multiple independent anomaly detection workloads on a single system that runs multiple virtual machines through a Kernel-based Virtual Machine (KVM) host.

Use Cases

  • Industrial computer vision and time-series analysis
  • Virtualized environments for multiple applications

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

Object Flaw Detector

Detect various anomalies of an object that is moving on a conveyor belt within a manufacturing facility, and then run analysis on what is detected.

Use Cases

  • Identify products damaged during manufacturing.
  • Confirm product orientation is correct for labeling.
  • Detect labels for product UPC identification.

Object Size Detector

Use computer vision to detect and measure the approximate size of parts moving on an assembly line, identify irregularly sized items, and send alerts when any are detected.

Use Cases

  • Track mechanical part count and size.
  • Alert users if an irregularly sized part is detected.
  • Interpret data from either a live webcam or preexisting video.

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

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.

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.

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.