final

Author: madeline-underwood

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

@@ -16,8 +16,8 @@ Building on the previous pub/sub example, you’ll now run a lightweight Zenoh d
 This pattern is ideal for robotics and IIoT scenarios where devices intermittently connect or request snapshots of remote state.
 
 For example, in a warehouse or factory:
-- Robots can periodically publish position, temperature, or battery level
-- A central system or peer node can later query these values on demand
+- Robots can periodically publish position, temperature, or battery level.
+- A central system or peer node can later query these values on demand.
 
 Unlike Pub/Sub, which requires live, real-time message exchange, Zenoh's storage and query model enables asynchronous access to data that was published earlier, even if the original publisher is no longer online.
 
@@ -77,7 +77,7 @@ If you have more than two Raspberry Pi devices, you can run the `z_get` command
 
 This example shows how Zenoh's storage with query model supports asynchronous data access and resilient state-sharing—critical capabilities in robotics and industrial IoT systems where network connectivity may be intermittent or system components loosely coupled.
 
-## What's next
+## What's next?
 
 Now that you've seen how Zenoh handles pub/sub and storage-based queries, you're ready to build reactive and intelligent edge nodes.
 

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

@@ -70,7 +70,7 @@ This model enables edge-based intelligence, such as:
 
 Queryable is a key feature for data-in-use scenarios, allowing fine-grained, on-demand compute inside your Zenoh-powered architecture.
 
-## What's next
+## What's next?
 
 In the next example, you'll extend this queryable pattern to support **runtime parameters**, such as battery level and temperature, allowing each node to return a calculated health score on demand.
 

content/learning-paths/cross-platform/zenoh-multinode-ros2/7_zenoh-querycomp.md

@@ -22,7 +22,7 @@ Instead of streaming data continuously, robots expose a queryable endpoint that
 
 This saves bandwidth and enables lightweight edge-side decision-making.
 
-### Create a new Zenoh rust project
+## Create a new Zenoh rust project
 
 On any Raspberry Pi:
 
@@ -40,7 +40,7 @@ tokio = { version = "1", features = ["full"] }
 url = "2"
 ```
 
-### Implement the queryable node
+## Implement the queryable node
 
 Next, log in to the other Raspberry Pi.
 
@@ -109,7 +109,7 @@ You can extend this queryable pattern to respond to other real-time diagnostics,
 
 This design pattern enables efficient, on-demand data exchange with minimal bandwidth usage. This is ideal for edge computing scenarios where resources and connectivity are constrained.
 
-### Battery health estimation formula
+## Battery health estimation formula
 
 The health score is calculated using the following logic:
 
@@ -129,7 +129,7 @@ For example, if `battery = 88` and `temp = 32`, then:
 - Temperature offset = (32 - 25) / 2 = 3
 - Health = 88 - 3 = 85%
 
-### Build and run
+## Build and run
 
 ```bash
 cd $HOME/zenoh/zenoh_battery_estimator
@@ -143,7 +143,7 @@ After the build process, you will see:
     Finished `release` profile [optimized] target(s) in 1m 22s
 ```
 
-### Query it with parameters
+## Query it with parameters
 
 Run it on the Raspberry Pi you used for the build run: