Solution Overview

Retailers face a complex challenge: maintaining accurate and consistent inventory information across multiple channels while managing vast amounts of data. Traditional methods struggle to keep pace with the demands of today's dynamic market.

RFID technology offers a transformative solution. By automatically tracking tagged items using electromagnetic fields, retailers gain unprecedented real-time visibility into inventory levels. This empowers them to optimize stock management, reduce labor costs, and elevate customer satisfaction.

Harnessing the full potential of RFID requires a robust data layer. MongoDB Atlas provides the ideal solution for capturing, processing, and analyzing the massive datasets generated by RFID technology.

Key benefits:

• Inventory accuracy: Eliminate stock discrepancies and reduce out-of-stocks, ensuring products are where customers expect them to be.
• Operational efficiency: Streamline processes like receiving, picking, and packing, leading to faster turnaround times and cost savings.
• Enhanced customer experience: Fulfill orders accurately and quickly, boosting customer satisfaction and loyalty.
• Data-driven insights: Leverage detailed product and sales data to make informed business decisions and optimize product assortment.

By adopting RFID and complementing it with a powerful database solution, retailers can overcome the challenges of product information management and achieve a competitive advantage.

Reference Architectures

By attaching RFID tags to products and utilizing a network of readers, businesses can accurately track items from the manufacturing floor to the end consumer. Below, we'll explain the general architecture of an RFID system and then provide a specific example using Zebra Technologies.

1. End-to-end supply chain tracking with RFID

This architecture outlines a comprehensive system for monitoring product movement throughout the supply chain using RFID technology. MongoDB Atlas serves as the underlying data layer for managing and analyzing RFID data.

Key components and functions:

• RFID data collection: Information is captured from RFID tags attached to products using RFID readers.
• Data management: MongoDB Atlas stores and processes collected RFID data.
• Data analysis: The system utilizes MongoDB Atlas to extract valuable insights from the data through data cleaning, transformation, and analysis.
• Workflow optimization: The architecture visualizes the data flow from initial collection to the generation of actionable insights.

2. RFID product tracking implementation

With the help of an RFID product tracking architecture, we aim to showcase an example that integrates the Zebra Technologies 123RFID app with the Atlas developer data platform using an API gateway.

Key components and functionalities:

• RFID data capture: The Zebra Technologies 123RFID app collects product information via RFID tags.
• Data integration: An API gateway seamlessly transfers RFID data from the app to MongoDB Atlas.
• Data storage and analysis: MongoDB Atlas serves as the central repository for RFID data, enabling comprehensive data analysis.

Building the Solution

In this guide, we will explore how a retail RFID product tracking application can integrate with MongoDB Atlas and how to use it to efficiently handle inventory checks.

• Step 1: Setting up MongoDB Atlas
  • Cluster setup
    • Select a cloud provider
    • Choose a region
    • Configure cluster specifications (e.g., instance size, storage)
  • Network security
    • Configure network access
    • Identify IP access list for edge devices and application servers
    • User authentication
    • Create a database user with read and write permissions for the inventory database
  • Connection
    • Obtain connection string from MongoDB Atlas
    • Use connection string to connect your application to the cluster
• Step 2: Configuring your project in XCode
  • Project setup
    • Open the 123RFID (or the name you’ve given it) project in Xcode
    • Configure project settings (deployment target)
    • Add necessary frameworks and libraries from Zebra SDK
    • Configure build settings (library search paths, framework search paths)
  • Device pairing
    • Enable Bluetooth on iOS device
    • Pair RFID reader using 123RFID app
  • Running the application
    • Connect iOS device to Mac
    • Select device as target in Xcode
    • Run the application
• Step 3: Matching inventory tags The getMatchingTagList method in Objective-C compares RFID tags from the current physical inventory with a predefined list of tags and updates the user interface accordingly.
  • How it works:
    • Retrieves current inventory and predefined tag list
    • Compares inventory tags with the tag list to find matches
    • Removes matched tags from the missing tags list
    • Updates UI with counts of unique and total tags
    • Stops inventory operation and confirms a complete match if all tags are accounted for
• Step 4: Sending match confirmation The sendUrlRequestToFlag method sends a POST request to a specified URL to indicate the result of the inventory check.
  • How it works:
    • Initializes POST request to the target URL
    • Sets JSON content type header
    • Prepares JSON payload with inventory check result
    • Sends POST request and logs the result
    • Displays a warning message based on the inventory check outcome
• Step 5: Display your inventory checks in real time We'll leverage MongoDB's Change Streams for instant notifications and visualize the data using MongoDB Atlas Charts.The code sets up a change stream to monitor new inventory checks in the inventoryCheck collection.
  • Endpoint setup:
    • Use MongoDB's Change Streams to monitor changes in the inventoryCheck collection

The following code sets up a change stream to monitor new inventory checks in the inventoryCheck collection.

Code Snippet

• Embed the dashboard:
  • Use MongoDB Charts embedding SDK to integrate the dashboard into your web application
  • Import necessary libraries and context
  • Create an instance of ChartsEmbedSDK with your base URL
  • Define and render the dashboard properties into a designated div
  • Start the change stream and handle real-time updates with alerts
• Implement real-time alerts:
  • Display success or error alerts based on the inventory check results using pushToast
• Ensure integration:
  • Verify that real-time notifications and dashboard updates work seamlessly
  • Maintain accurate inventory data and respond quickly to discrepancies

By following this guide, you can effectively integrate the Zebra 123RFID app with MongoDB Atlas, enabling real-time inventory management and ensuring data accuracy.

Key Learnings

By combining RFID technology with the power of MongoDB Atlas, retailers can significantly enhance their inventory management capabilities. This integration offers several key advantages:

• Real-time inventory management: Leverage RFID technology and MongoDB Atlas to achieve accurate and up-to-date inventory data.
• Improved efficiency: Streamline inventory processes, reduce stockouts, and optimize operations through data-driven insights.
• Data-driven decision making: Utilize MongoDB Atlas Charts for real-time visualizations, enabling informed business decisions.

Technologies and Products Used

MongoDB database services:

• MongoDB Atlas

Additional:

• Zebra Technologies 123RFID app
• Zebra RFID readers/scanners

Authors

• Francesco Baldissera, MongoDB
• Pedro Bereilh, MongoDB
• Rami Pinto, MongoDB
• Sebastian Rojas Arbulu, MongoDB
• Mehar Grewal, MongoDB
• Prashant Juttukonda, MongoDB