Data visualization

In this lab, we will focus on data visualization within Home Assistant, transforming raw IoT data (like trash can fill percentage) into insightful charts and gauges. Effective visualization helps you identify trends, gain insights, and make informed decisions about your IoT environment.

Last year, we worked with OpenRemote’s Insights page for dashboards. This year, we’ll leverage Home Assistant’s native capabilities, as well as consider external integrations if desired. By doing so, you will understand how Home Assistant can become a powerful tool for monitoring and analyzing historical data from your Smart Trash Can project.

Importance of Visualization in IoT

As with any IoT application, the raw data from sensors (in our case, fill percentage, motion events, etc.) is more meaningful when displayed visually. With proper visualization you can:

• Recognize patterns and trends in how quickly the trash can fills up.
• Understand usage patterns (e.g., time of day when trash is disposed).
• Quickly identify anomalies (e.g., unexpected spikes in fill percentage).
• Improve decision-making (e.g., scheduling more frequent emptying if needed).

In short, visuals help turn numbers into actionable insights.

Home Assistant Visualization Options

Home Assistant provides several built-in options for visualizing your sensor data:

1. History & Logbook:
   Home Assistant stores recent data for your sensors. You can view historical charts by clicking on entities from the Overview or using the History tab. Although basic, this view provides a quick timeline of changes.

2. Lovelace Dashboards:
   Home Assistant’s frontend, Lovelace, allows you to build custom dashboards using cards. Common relevant cards include:

   • History Graph Card: Show historical data for one or more entities as a line chart.
   • Sensor Card: Display the current state of an entity; can show a sparkline of recent activity.
   • Gauge Card: Present the current fill percentage against min/max thresholds.
   • Statistics Graph Card: Visualize long-term statistics for numeric sensors (available if using recorder and statistics integration).

   By mixing and matching these cards, you can create a dashboard that shows both current values (like a gauge) and historical trends (like line charts).

3. Custom and Community Cards:
   Through the Home Assistant Community Store (HACS), you can install custom cards that provide advanced visualization features. Some popular ones include:

   • Mini Graph Card: A compact but highly customizable line chart for your sensors.
   • ApexCharts Card: Offers a rich feature set for complex and interactive charts.

4. External Integrations (Optional Advanced Setup):
   If you need long-term storage and advanced analytics, consider integrating with external tools:

   • InfluxDB Add-on + Grafana Add-on: InfluxDB stores time-series data, and Grafana provides powerful dashboards and advanced querying features. You can then embed Grafana panels into Home Assistant dashboards.

   While this is more advanced and not required, it’s an excellent step if you want to go beyond basic visualization (again not required for this lab).

Creating a Dashboard in Home Assistant

Step-by-Step Example: History Graph for Fill Percentage

1. Ensure Your Sensor Is Updating:
   Confirm that your sensor.smart_trash_can_fill_percentage is receiving data (either via MQTT or any other setup from previous labs).

2. Open the Lovelace Dashboard Editor:
   In Home Assistant, go to Overview > Edit Dashboard or create a new view (it is better to create a new view!).

3. Add a History Graph Card:
   Click Add Card and select History Graph.
   Configure it as follows:

   type: history-graph
   entities:
     - entity: sensor.smart_trash_can_fill_percentage
   hours_to_show: 24
   refresh_interval: 60
   

4. Add a Gauge Card for Current Status:
   Add another card of type Gauge:

   type: gauge
   entity: sensor.smart_trash_can_fill_percentage
   min: 0
   max: 100
   name: Fill Percentage
   

Experimenting with Additional Visualizations

• Statistics Graph Card (if using statistics):
  If you’ve enabled long-term statistics for your sensor, the Statistics Graph card can show aggregated data (e.g., average or max fill percentage over a time period).

• InfluxDB + Grafana (Advanced):
  If you integrate InfluxDB and Grafana, you can create complex dashboards with multiple queries, alerts, and advanced panels. You can embed Grafana panels into Home Assistant using an iframe card, allowing you to view advanced visualizations without leaving the Home Assistant UI.

Encouraging Students to Explore

As part of your learning experience:

• Try Different Time Ranges:
  Show only the last 2 hours or the last week of data. Observe how patterns emerge over longer periods.

• Add Multiple Entities:
  Compare fill percentage over time with other data, like motion detection or volume readings. This can help you correlate when motions occur and how quickly the bin fills.

• Experiment with Custom Cards:
  Adjust colors, line thickness, and thresholds to create more intuitive visualizations.

• Integrate Other Data Points:
  If you have other IoT data (you can create new virutal sensors) (like temperature or humidity in the room), add them to the dashboard. This can help you see if environmental conditions influence how often trash is disposed of.

Conclusion

By completing this lab, you’ve learned how to visualize historical and current IoT data within Home Assistant. You transformed raw numbers into interactive and meaningful graphs, gauges, and charts. This process is essential in IoT, where understanding historical trends is often as important as knowing the current status. By experimenting with different cards, timescales, and integrations, you can create a user-friendly, informative, and adaptable dashboard for your Smart Trash Can project.

Remember: The best visualization is the one that provides clear insights at a glance. Keep exploring and refining your dashboards as your IoT ecosystem grows and evolves.