| Model Type | Time Series Forecasting |
|---|---|
| Framework | AI Edge LiteRT |
| Algorithm | Temporal Convolutional Network (TCN) |
| Technical Details | Forecasts future electricity consumption from historical power measurements to support energy monitoring and planning applications. |
Time Series Forecast for Electricity Consumption
Short-term electricity consumption forecasting based on historical time-series data.
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Time Series Forecast for Electricity Consumption
app details
Resources
Use Cases
Predictive Maintenance
Anomaly Detection
Supported SECO Devices
AI optimized hardware
Fanless embedded PCs
Modules
supported chipsets
Intel® Core™ i3
Qualcomm® Dragonwing QCS6490
Qualcomm® Dragonwing QCS5430
NXP i.MX 8M Plus
NXP i.MX 95
Performance Benchmark
Hardware · Backend
Processing unit
Latency (ms)
Avg. Peak RAM
MediaTek Genio 510 · AiEdgeLiteRT
CPU
8.2 ms
135.2 MB
NXP i.MX 8M Plus · AiEdgeLiteRT
NPU
2.9 ms
122.8 MB
NXP i.MX 8M Plus · AiEdgeLiteRT
GPU
2.9 ms
122.8 MB
NXP i.MX 8M Plus · AiEdgeLiteRT
CPU
7.5 ms
136.9 MB
Intel Tiger Lake · AiEdgeLiteRT
CPU
1.4 ms
137 MB
Qualcomm QCS6490 · AiEdgeLiteRT
NPU
5.6 ms
128.4 MB
Qualcomm QCS6490 · AiEdgeLiteRT
CPU
8 ms
134.6 MB
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