diff --git a/source/includes/images/industry-solutions/rfid-product-architecture-2.svg b/source/includes/images/industry-solutions/rfid-product-architecture-2.svg new file mode 100644 index 00000000..8e277bc7 --- /dev/null +++ b/source/includes/images/industry-solutions/rfid-product-architecture-2.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/source/includes/images/industry-solutions/rfid-product-architecture.svg b/source/includes/images/industry-solutions/rfid-product-architecture.svg new file mode 100644 index 00000000..ba644b5b --- /dev/null +++ b/source/includes/images/industry-solutions/rfid-product-architecture.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/source/solutions-library.txt b/source/solutions-library.txt index 82483d71..dd4f1201 100644 --- a/source/solutions-library.txt +++ b/source/solutions-library.txt @@ -313,6 +313,15 @@ kick-start their projects. Enable real-time order tracking and management across all retail channels using MongoDB Atlas. + .. card:: + :headline: Real-Time Product Tracking + :url: https://deploy-preview-236--docs-atlas-architecture.netlify.app/solutions-library/retail-asset-rfid-retail/ + :icon: mdb_custom_aggregation + :icon-alt: Atlas mdb_custom_aggregation icon + + Learn how to build a real-time inventory management system + with RFID and MongoDB Atlas. + Gen AI ------ diff --git a/source/solutions-library/manufacturing-asset-fleet-management.txt b/source/solutions-library/manufacturing-asset-fleet-management.txt index 17ea3f34..b2ade46f 100644 --- a/source/solutions-library/manufacturing-asset-fleet-management.txt +++ b/source/solutions-library/manufacturing-asset-fleet-management.txt @@ -96,6 +96,8 @@ OpenAI LLM. :alt: Basic Components of an AI Agent Figure 1: Basic components of an AI agent + +.. video:: https://www.youtube.com/watch?v=_CAOb7BR-Rg Reference Architecture ---------------------- @@ -371,7 +373,7 @@ Feel free to adjust the prompt in main.py or update the telemetry data in the te Running the solution ~~~~~~~~~~~~~~~~~~~~ -**Starting a new diagnosis** +**Starting a New Diagnosis** - Open the frontend and choose “New Diagnosis”. @@ -397,7 +399,7 @@ Running the solution - Click the “Run Agent” button and wait for a minute or two as the agent finishes its run. -**Viewing workflow** +**Viewing Workflow** - The workflow, chain-of-thought output, and the final recommendation is shown in the left column. @@ -405,7 +407,7 @@ Running the solution - The workflow is generated in real time, giving transparency into the agent's decision-making process. -**Reviewing MongoDB documents** +**Reviewing MongoDB Documents** - In the right column, the documents shown are the records inserted during the current agent run: @@ -423,7 +425,7 @@ Running the solution - **checkpoints:** (From the checkpointing database) Shows the last saved state for potential recovery. -**Resume functionality** +**Resume Functionality** - Optionally, we can demonstrate the "Resume Diagnosis" feature by entering a thread ID and showing how the system retrieves the diff --git a/source/solutions-library/retail-asset-rfid-retail.txt b/source/solutions-library/retail-asset-rfid-retail.txt new file mode 100644 index 00000000..03eb12d3 --- /dev/null +++ b/source/solutions-library/retail-asset-rfid-retail.txt @@ -0,0 +1,349 @@ +.. _arch-center-is-rfid-retail: + +================================ +RFID: Real-Time Product Tracking +================================ + +.. facet:: + :name: genre + :values: tutorial + +.. meta:: + :keywords: document model, retail, tracking, analytics, catalog + :description: Learn how to build a real-time inventory management system with RFID and MongoDB Atlas. + +.. contents:: On this page + :local: + :backlinks: none + :depth: 1 + :class: singlecol + +Enhance retail inventory management with Radio Frequency Identification +(RFID) Technology and MongoDB Atlas for real-time tracking, improved +accuracy, and data-driven insights across your supply chain. + +**Use cases:** `Catalog `__, +`Personalization `__ + +**Industries:** `Retail `__ + +**Products:** `MongoDB Atlas `__ + +Solution Overview +----------------- + +Retailers must ensure accurate and consistent inventory information +across multiple channels while handling vast amounts of data. However, +traditional methods struggle to keep pace with the demands of today's +dynamic market. + +In this scenario, RFID Technology offers a transformative solution. By +automatically tracking tagged items using electromagnetic fields, +retailers gain unprecedented real-time visibility into inventory levels. +This implementation optimize stock management, reduce labor +costs, and elevate customer satisfaction. + +Harnessing RFID's potential requires a robust data layer. MongoDB Atlas +provides the solution for capturing, processing, and analyzing these +massive datasets. + +RFID Technology Benefits +~~~~~~~~~~~~~~~~~~~~~~~~ + +By integrating RFID Technology with a powerful database solution, +retailers can efficiently address product information management +challenges and unlock key advantages: + +- **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. + +.. video:: https://www.youtube.com/watch?v=xK2RHBcpZXc + +Reference Architectures +----------------------- + +Businesses can track items from the manufacturing floor to the end +consumer by attaching RFID tags to products and using a network of +readers. Below, we explain the general architecture of a RFID system +and provide a specific example with Zebra Technologies. + +Supply Chain Tracking with RFID +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +This architecture shows a comprehensive system with RFID Technology to +monitor product movement through the supply chain. MongoDB Atlas serves +as the underlying data layer to manage and analyze 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. + +.. figure:: /includes/images/industry-solutions/rfid-product-architecture.svg + :figwidth: 1200px + :alt: End-to-end supply chain RFID tracking architecture + + Figure 1. End-to-end supply chain RFID tracking architecture + +RFID Product Tracking Implementation +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Using a RFID product tracking architecture, we show an example that +integrates the Zebra Technologies 123RFID app with MongoDB Atlas through +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. + +.. figure:: /includes/images/industry-solutions/rag-chatbot-architecture.svg + :figwidth: 1200px + :alt: Example of a RFID product architecture with Atlas and Zebra Technologies + + Figure 2. Example of a RFID product tracking architecture based on the integration of Zebra Technologies with MongoDB Atlas + +Building the Solution +--------------------- + +This guide explains how a retail RFID product tracking application +integrates with MongoDB Atlas and demonstrates how to use it for +efficient inventory checks. + +.. procedure:: + :style: normal + + .. step:: Set 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:: Configure 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:: Match 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. This procedure works + as follows: + + - 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. + + .. step:: Send Match Confirmation + + The *sendUrlRequestToFlag* method sends a POST request to a + specified URL to indicate the result of the inventory check. This + process works as follows: + + - Initializes POST request to the target URL. + + - Sets JSON content type header. + + - Prepares JSON payload with inventory check results. + + - Sends POST request and logs the results. + + - Displays a warning message based on the inventory check outcome. + + .. step:: Display Your Inventory Checks in Real Time + + We leverage `MongoDB 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 Change Streams to monitor changes in the + inventoryCheck collection. + + .. code-block:: javascript + :copyable: true + + const startWatchInventoryCheck = async (dashboard, addAlert, utils) => { + console.log("Start watching stream"); + + const runs = await getMongoCollection(utils.dbInfo.dbName, "inventoryCheck"); + const filter = { + filter: { + operationType: "insert" + } + }; + + const stream = runs.watch(filter); + + const closeStreamInventoryCheck = () => { + console.log("Closing stream"); + stream.return(); + }; + + try { + for await (const change of stream) { + console.log(change.fullDocument); + addAlert(change.fullDocument.checkResult); + dashboard.refresh(); + } + } catch (error) { + console.error("Error watching stream:", error); + } + }; + + **Embed the dashboard** + + - Use MongoDB Charts embedding SDK to integrate the dashboard into + your web application. + + - Import the 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. + +Follow this guide to effectively integrate the Zebra 123RFID app with +MongoDB Atlas, enabling real-time inventory management and data +accuracy. + +Key Learnings +------------- + +By combining RFID Technology and MongoDB Atlas, retailers can enhance +their inventory management capabilities. This integration provides 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:** Use MongoDB Atlas Charts for real-time + visualizations, enabling informed business decisions. + +Technologies and Products Used +------------------------------ + +MongoDB Developer Data Platform +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +- `MongoDB Atlas `__ + +Additional Technologies +~~~~~~~~~~~~~~~~~~~~~~~ + +- `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 \ No newline at end of file diff --git a/source/solutions-library/retail-catalog.txt b/source/solutions-library/retail-catalog.txt index 59117025..bae4d25a 100644 --- a/source/solutions-library/retail-catalog.txt +++ b/source/solutions-library/retail-catalog.txt @@ -7,4 +7,5 @@ Retail Catalog As-You-Type Suggestions Building Inventory Management System - Building Omnichannel Ordering Solution \ No newline at end of file + Building Omnichannel Ordering Solution + Real-Time Product Tracking \ No newline at end of file