Edge AI Glossary
The Internet of Things (IoT) is reshaping how businesses, consumers, and devices interact—yet the terminology can often feel overwhelming. This IoT Glossary is designed to simplify that complexity by providing clear, concise definitions of key terms, technologies, and concepts. Whether you’re a business leader, developer, or simply exploring the IoT landscape, this resource will help you navigate the language of connected devices, networks, and data-driven innovation.
- A
- B
- C
- D
- E
- F
- G
- H
- I
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
A
C
E
F
N
- Neural Processing Unit (NPU)
- Neural Network
O
- Object Detection
- On-Device Training
- Overfitting
P
- Parameters
- Pose Estimation
- Postprocessing
- Precision
- Predictive Maintenance
- Pruning
- Psychological Safety
Q
- Quantization
R
- Real-time Processing
- Recall
- Regression
- Responsible Design
- Resource Constraints
- ROC (Receiver Operating Characteristic) Curve
S
- Sample Rate / Frequency
- Segmentation
- Semi-supervised Learning
- Sensor Fusion
- Sequence Models
- Smart Devices
- System-on-Chip (SoC)
- Spectrogram
- Spiking Neural Networks (SNNs)
- Stakeholders
- Supervised Learning
- Synthetic Data
T
- Tiny Machine Learning (TinyML)
- Training
- Training Split
- Transfer Learning
- Transformation
U
- Unsupervised Learning
V
- Validation Split
- Virtual Sensor
W
- Window
- Wizard of Oz Prototype