Updates

Author: madeline-underwood

content/learning-paths/cross-platform/zenoh-multinode-ros2/2_zenoh-install.md

@@ -13,7 +13,7 @@ This section shows you how to install and build the open-source Eclipse Zenoh pr
 
 The following instructions have been verified on Raspberry Pi 4 and 5, but you can use any Arm Linux device. These steps apply to Raspberry Pi and other Arm-based Linux platforms. Before building Zenoh, make sure your system has the necessary development tools and runtime libraries.
 
-### Install the Rust development environment
+## Install the Rust development environment
 
 First, install the [Rust](https://www.rust-lang.org/) environment. The core of Zenoh is developed in Rust for performance and safety. 
 
@@ -36,13 +36,13 @@ source "$HOME/.cargo/env"
 
 For more information, see the [Rust Install Guide](/install-guides/rust/) for Arm Linux.
 
-### Install ROS 2
+## Install ROS 2
 
 [Robot Operating System](https://www.ros.org/) is a set of software libraries and tools that help you build robot applications. ROS provides everything from drivers to state-of-the-art algorithms, as well as developer tools. It is completely open-source.
 
 If you plan to use Zenoh alongside ROS 2, for example, to bridge DDS-based nodes, you should install ROS 2 before proceeding. See the [ROS2 Installation Guide](/install-guides/ros2/) to install ROS 2 on your Arm platforms.
 
-### Download and build the Zenoh source
+## Download and build the Zenoh source
 
 Clone the Zenoh repository:
 

content/learning-paths/cross-platform/zenoh-multinode-ros2/3_zenoh-multinode.md

@@ -15,9 +15,9 @@ If you’ve already installed Zenoh on an Arm Cortex-A or Neoverse platform as s
 
 To simplify and scale deployment across multiple devices, this section shows how to containerize Zenoh with Docker for streamlined distribution and consistent multi-node testing. This containerized approach enables repeatable rollouts and makes it easier to test distributed communication across Raspberry Pi, Arm cloud instances (like AWS Graviton), and Arm Virtual Hardware.
 
-In this session, you’ll use Raspberry Pi boards to simulate a scalable distributed environment. The same workflow applies to any Arm Linux system, including cloud instances and virtual hardware. This setup allows you to simulate real-world, cross-node communication scenarios, making it ideal for evaluating Zenoh’s performance in robotics and industrial IoT applications. Zenoh is ideal for robotics and industrial IoT systems that require fast, decentralized communication. It supports scalable data exchange across devices using pub/sub, storage, and query models.
+In this session, you’ll use Raspberry Pi boards to simulate a scalable distributed environment. The same workflow applies to any Arm Linux system, including cloud instances and virtual hardware. This setup allows you to simulate real-world, cross-node communication scenarios, making it ideal for evaluating Zenoh’s performance in robotics and industrial IoT applications. This setup simulates real-world, cross-node communication scenarios, making it ideal for robotics and industrial IoT applications that require fast, decentralized messaging using pub/sub, storage, and query models.
 
-### Install Docker on Raspberry Pi
+## Install Docker on Raspberry Pi
 To simplify this process and ensure consistency, you can use Docker to containerize your Zenoh and ROS 2 environment. This lets you quickly replicate the same runtime on any device without needing to rebuild from source.
 
 This enables scalable, multi-node testing in realistic distributed environments.
@@ -29,7 +29,7 @@ curl -fsSL get.docker.com -o get-docker.sh && sh get-docker.sh
 sudo usermod -aG docker $USER ; newgrp docker
 ```
 
-### Create a ROS 2 + Zenoh Docker image
+## Create a Docker image with ROS 2 and Zenoh
 
 To ensure compatibility with ROS-related tools, create a `Dockerfile` based on  `ros:galactic `, and use the official Rust installation method to build Zenoh, as shown below.
 
@@ -107,11 +107,12 @@ docker pull odinlmshen/zenoh-node
 Once built, you can reuse this Docker image across multiple Arm-based nodes, including Raspberry Pi, AWS Graviton, and Arm Virtual Hardware.
 {{% /notice %}}
 
-### Transfer the Docker image to the other Raspberry Pi
+## Transfer the Docker image to another Raspberry Pi
+
 
 There are two options to transfer the Docker image to your second device. Choose one of the following methods.
 
-Option 1: Save and copy via file 
+1. Save and copy using the file: 
 
 ```bash
 docker save zenoh-node > zenoh-node.tar
@@ -124,14 +125,11 @@ On the target device:
 docker load < zenoh-node.tar
 ```
 
-Option 2: Push the image to a container registry such as Docker Hub
+2. Push the image to a container registry such as Docker Hub:
 
 You can also push the image to Docker Hub or GitHub Container Registry and pull it on the second device.
 
-
-
-
-### Run the Docker image
+## Run the Docker image
 
 Once the image is successfully loaded on the second device, you can run the container to start the Zenoh environment.
 
@@ -154,3 +152,4 @@ The following sections illustrate the procedures to run the Zenoh examples so as
 - Queryable – for enabling on-demand remote computation  
 - Dynamic queryable with computation – for executing dynamic logic across nodes
 
+With your Zenoh examples running across containers, you’re now ready to build and benchmark real-time communication flows across nodes, which is ideal for simulating robotic fleets or industrial systems.

content/learning-paths/cross-platform/zenoh-multinode-ros2/4_zenoh-ex1-pubsub.md

@@ -8,11 +8,11 @@ layout: learningpathall
 
 ## Test Zenoh pub/sub across two devices
 
-This example demonstrates Zenoh's real-time publish/subscribe model across two Raspberry Pi devices.
+This example demonstrates how to use Zenoh’s real-time publish/subscribe model to exchange messages between two Raspberry Pi devices over a local network.
 
-The subscriber listens for all data published under the key expression `demo/example/**`, which matches any topic beginning with `demo/example/`.
+Pub/sub is a core Zenoh communication pattern where data producers (publishers) send values to a key, and data consumers (subscribers) receive updates for matching key expressions. In this case, the subscriber listens for all messages published under the key expression `demo/example/**`, which matches any topic that begins with `demo/example/`. This enables flexible topic filtering and lightweight data dissemination across distributed systems.
 
-### Start the subscriber node
+## Start the subscriber node
 
 Run the subscriber example on one of the Raspberry Pi systems:
 
@@ -21,7 +21,7 @@ cd ~/zenoh/target/release/examples
 ./z_sub
 ```
 
-### Start the publisher node
+## Start the publisher node
 
 Then, log in to the other Raspberry Pi and run the publisher:
 
@@ -34,7 +34,7 @@ cd ~/zenoh/target/release/examples
 You can run both `z_sub` and `z_pub` on the same device for testing, but running them on separate Raspberry Pis demonstrates Zenoh’s distributed discovery and cross-node communication.
 {{% /notice %}}
 
-### Observe the pub/sub data flow
+## Observe the pub/sub data flow
 
 The results are shown below:
 

content/learning-paths/cross-platform/zenoh-multinode-ros2/5_zenoh-ex2-storagequery.md

@@ -25,7 +25,7 @@ In this example, you’ll run the `zenohd` daemon with in-memory storage and use
 
 This is especially useful for distributed systems where nodes may intermittently connect or request snapshots of state from peers.
 
-### Start the Zenoh daemon with in-memory storage
+## Start the Zenoh daemon with in-memory storage
 
 On one Raspberry Pi, launch the Zenoh daemon with a configuration that enables in-memory storage for keys in the `demo/example/**` directory.
 
@@ -40,7 +40,7 @@ You should see log messages indicating that the storage_manager plugin is loaded
 
 If port 7447 is already in use, either stop any previous Zenoh processes or configure a custom port using the `listen.endpoints.router` setting.
 
-### Publish a value
+## Publish a value
 
 On 2nd Raspberry Pi device, use `z_put` to send a key-value pair that will be handled by the `zenohd` storage.
 
@@ -51,7 +51,7 @@ cd ~/zenoh/target/release/examples
 
 This command stores the string `Hello from storage!` under the key demo/example/test1.
 
-### Query the stored value
+## Query the stored value
 
 Back on first Raspberry Pi, you can now query the stored data from any Zenoh connected node.
 

content/learning-paths/cross-platform/zenoh-multinode-ros2/6_zenoh-ex3-queryable.md

@@ -9,17 +9,17 @@ layout: learningpathall
 
 ## Computation on query 
 
-This example demonstrates Zenoh's queryable capability, which lets a node respond to incoming data requests by computing results in real time, rather than returning previously stored values.
+This example shows how to use Zenoh’s queryable feature to return computed results in real time, instead of serving pre-stored values.
 
-Unlike `zenohd` which simply returns stored data, a queryable node can register to handle a specific key expression and generate responses at runtime. This is ideal for distributed computing at the edge, where lightweight devices, such as Raspberry Pi nodes, can respond to requests with calculated values. This enables sensor fusion, AI inference results, and diagnostics.
+Unlike `zenohd` which simply returns stored data, a queryable node can register to handle a specific key expression and generate responses at runtime. This is ideal for distributed computing at the edge, where lightweight devices, such as Raspberry Pi nodes, can respond to requests with calculated values. This pattern is ideal for sensor fusion, lightweight AI inference, and dynamic system diagnostics on resource-constrained edge devices.
 
-### Use case: estimate battery health on demand
+## Use case: estimate battery health on demand
 
 Imagine a robot fleet management system where the central planner queries each robot for its latest battery health score, which is not published continuously but calculated only when queried.
 
 This reduces bandwidth usage and enables edge-side optimization using Zenoh's queryable feature.
 
-### Launch a queryable node
+## Launch a queryable node
 
 On one Raspberry Pi device, run the `z_queryable` Zenoh example to register a queryable handler.
 
@@ -38,7 +38,7 @@ Press CTRL-C to quit...
 
 The node is now ready to accept queries on the key `demo/example/zenoh-rs-queryable` and respond with a predefined message.
 
-### Trigger a query from another node
+## Trigger a query from another node
 
 On the other Raspberry Pi device, run the `z_get` example.
 
@@ -59,10 +59,9 @@ The result is shown below:
 
 ![img3 Zenoh queryable node responding to on-demand queries from a remote device#center](zenoh_ex3.gif "Figure 3: Computation on Query using Queryable")
 
-The value you receive is generated in real time by the function defined in the queryable handler, not from pre-stored data.
+The response is generated dynamically by the queryable handler, and not fetched from stored data.
 
-
-### Real-world application: distributed inference and computation
+## Real-world use cases
 
 This model enables edge-based intelligence, such as:
 - Executing custom logic in response to a query such as “calculate load average”