1295 Data Visualization and Dashboards for IoT
1295.1 Overview
Data visualization transforms IoTโs continuous data streams into actionable intelligence. This chapter series covers the complete visualization journey: from selecting the right chart types to building production dashboards with real-time updates.
A well-designed dashboard answers โIs everything OK?โ within 5 seconds. If users need to think before understanding system status, the design has failed. This principle guides all visualization decisions.
1295.2 Chapter Guide
This topic is organized into six focused chapters:
1295.2.1 Visualization Types for IoT Data
Learn to select appropriate chart types for different IoT data patterns:
- Time-series charts (line, area, candlestick) for trends over time
- Gauges and meters for current status monitoring
- Heatmaps for pattern discovery across dimensions
- Geographic maps for location-based device data
- Status indicators for binary and categorical states
1295.2.2 Dashboard Design Principles
Master the principles that separate effective dashboards from visual clutter:
- Information hierarchy and F-pattern layout
- The 5-second rule for critical communication
- Audience-specific design (operators vs. engineers vs. executives)
- Avoiding common pitfalls: overload, color blindness, chart junk
- Accessibility and WCAG compliance
1295.2.3 Real-Time Visualization
Implement high-performance real-time dashboards:
- Push (WebSocket) vs. pull (polling) update strategies
- Data decimation algorithms (LTTB, min-max, averaging)
- Refresh rate optimization for different data types
- Query optimization and caching
- Performance tuning for 60fps rendering
1295.2.4 Data Encoding for IoT Media
Understand codecs for IoT video and audio streams:
- Containers vs. codecs distinction
- Waveform vs. parametric encoding approaches
- Video codecs (MJPEG, H.264, H.265, VP9) for surveillance
- Audio codecs (Opus, AAC, G.711) for voice and monitoring
- Bandwidth and storage calculations
1295.2.5 Visualization Tools
Choose and configure the right tools for your needs:
- Grafana for time-series monitoring
- ThingsBoard for complete IoT platforms
- Node-RED for rapid prototyping
- Custom development with D3.js, Chart.js, Plotly
- Building Grafana dashboards: data sources, panels, variables, alerting
1295.2.6 Hands-On Labs
Build real IoT dashboards with step-by-step labs:
- Lab 1: Web dashboard with ESP32 and Chart.js
- Lab 2: Serial visualization with ASCII bar charts and sparklines
- Lab 3: Multi-sensor monitoring with threshold alerts
All labs use the Wokwi simulator - no physical hardware required.
1295.3 Learning Path
Beginners: Start with Visualization Types to understand chart selection, then try Lab 2: Serial Visualization for hands-on practice.
Intermediate: Read Dashboard Design Principles, then complete Lab 1: Web Dashboard.
Advanced: Focus on Real-Time Visualization and Visualization Tools for production deployment.
1295.4 Quick Reference
1295.4.1 Chart Type Selection
| Question to Answer | Chart Type |
|---|---|
| How does this value change over time? | Line chart |
| Whatโs the current value vs. thresholds? | Gauge |
| When are values highest/lowest? | Heatmap |
| Where are my devices located? | Point map |
| Whatโs the status of my fleet? | Status table |
1295.4.2 Refresh Rate Guidelines
| Data Type | Recommended Refresh |
|---|---|
| Safety-critical alerts | 1 second (push) |
| Operational metrics | 5-30 seconds |
| Environmental sensors | 30-60 seconds |
| Trend analysis | 5-15 minutes |
| Historical reports | On-demand |
1295.4.3 Tool Selection
| Need | Recommended Tool |
|---|---|
| Quick prototype | Node-RED |
| Time-series monitoring | Grafana |
| Full IoT platform | ThingsBoard |
| Unique requirements | Custom development |