1329 Edge Data Acquisition
1329.1 Overview
Edge data acquisition is the process of collecting, processing, and transmitting sensor data at the network periphery - where physical devices meet the digital infrastructure. This section covers the fundamental concepts and techniques for efficient data collection at the IoT edge.
Collect raw data at the edge, but only transmit what’s needed - 90% of IoT data is never analyzed. Edge processing reduces latency, saves bandwidth, extends battery life, and protects privacy.
1329.2 Chapter Contents
This topic is organized into three focused chapters:
1329.2.1 1. Architecture and Device Types
Understanding the foundation of edge data acquisition:
- IoT Device Categories: Big Things, Small IP Things, and Non-IP Things
- Connectivity Paths: Direct connection vs. gateway-mediated access
- Data Generation Patterns: How different device types produce vastly different data volumes
- Power Budget Framework: Decision tree for selecting acquisition strategies
Key takeaway: Match your acquisition strategy to device capabilities - cameras need compression, temperature sensors need aggregation, non-IP devices need protocol translation.
1329.2.2 2. Sampling and Compression
Technical foundations for efficient data handling:
- Nyquist Theorem: Calculate appropriate sampling rates to avoid aliasing
- Data Reduction Techniques: Aggregation, compression, event-based reporting, delta encoding
- Compression Algorithms: Lossless (GZIP), lossy statistical (window aggregation), FFT-based, and semantic compression
- Algorithm Selection: Decision tree for choosing compression based on analytics requirements
Key takeaway: Apply the 90% rule - aggregate “normal” readings locally, transmit only summaries and anomalies. This extends battery life from days to years.
1329.2.3 3. Power Management and Gateways
Practical constraints and integration:
- Duty Cycling: Formulas for calculating battery life based on active/transmit/sleep patterns
- Power Optimization: How to achieve 5x battery life improvement through optimized duty cycles
- Gateway Functions: Protocol translation, store-and-forward buffering, security
- Missing Data Handling: Imputation strategies and health monitoring
Key takeaway: Transmission dominates power budget - batch data and maximize sleep time to extend battery life from months to years.
1329.3 Learning Path
| If you want to… | Start with… |
|---|---|
| Understand device categories and architecture | Architecture and Device Types |
| Learn sampling rates and compression algorithms | Sampling and Compression |
| Calculate battery life and understand gateways | Power Management and Gateways |
| Quick reference for a specific topic | Use the chapter links above |
1329.4 Prerequisites
Before starting this section, you should be familiar with:
- Edge, Fog, and Cloud Overview: Three-tier IoT architecture context
- Sensor Fundamentals: Sensor types and characteristics
- Basic electrical concepts: Current, voltage, and power calculations for battery life analysis
1329.5 What’s Next
After completing this section, continue to:
- Multi-Sensor Data Fusion: Combining data from multiple sources
- Edge Compute Patterns: Processing patterns at the edge
- Data Storage and Databases: Storage options for IoT data