Performance Modes & Battery Saving
Balance visible cameras, stream quality, detection work, heat, memory, and battery without assuming one fixed limit for every device.
Performance Modes
Settings: Settings → Performance Mode
| Mode | Stream policy | Detection | Best For |
|---|---|---|---|
| ⚡ Power Saving | Fewer active decoders; favor sub streams | Reduced frequency and camera budget | All-day monitoring on battery, low-activity scenes |
| ⚖️ Balanced (default) | Adaptive camera and decode budget | Motion-gated AI when configured | Everyday use, home monitoring |
| 🚀 High Performance | More work when resources permit | Higher refresh and camera budget | Plugged in, critical security, maximum cameras |
SmartRTSP can reduce work under memory, thermal, or power pressure. Measure on the target device; universal stream-count and battery-per-hour numbers are not reliable.
Background Limits on iPhone, iPad, and Apple TV
Apple controls background execution. SmartRTSP cannot guarantee that camera decoding, detection, recording, an Apple Home bridge, or a remote hub will continue after the app is suspended.
When the system suspends or terminates SmartRTSP:
- • Camera streams disconnect
- • Local detection and event recording stop
- • A bridge or hub running in that process becomes unavailable
- • Previously scheduled local work is not proof of continued media processing
- • Use a powered Mac and keep SmartRTSP running.
- • Disable sleep only when appropriate for the machine and security policy.
- • Test recovery after network loss, camera restart, app update, and Mac restart.
- • On iPhone, iPad, and Apple TV, keep SmartRTSP in the foreground for a dependable live session.
Cascade Detection — How It Saves Battery
Running a full AI model on every video frame would drain battery in hours. SmartRTSP's cascade approach runs heavy AI only on frames where it matters.
Running higher-cost analysis continuously increases compute, memory bandwidth, heat, and battery use.
Motion gating reduces unnecessary model work in quiet scenes. The measured benefit depends on scene activity and the configured models.
Sub-Stream for Multi-Camera
When monitoring 4 or more cameras, switching to Sub Stream significantly reduces CPU and battery usage:
- High decode CPU load
- High memory usage
- ~2-8 Mbps per camera
- Lower decode CPU in typical configurations
- Much lower memory
- ~200-500 Kbps per camera
Battery Saving Tips
-
1
Use Power Saving or Balanced mode
High Performance is designed for plugged-in use. Switch to Balanced or Power Saving for battery operation.
-
2
Use Sub Stream for multi-camera
Camera Settings → Stream → Sub Stream. The lower resolution and bitrate usually reduce decode and network load.
-
3
Only enable AI detection on cameras that need it
If a camera covers a low-risk area, use motion detection only instead of full AI. Much less CPU.
-
4
Set Do Not Disturb schedules
Disable detection during hours when you don't need it (e.g., 11 PM – 7 AM). Reduces background processing.
-
5
Plug in for background monitoring
Background monitoring with continuous streaming increases battery draw. Connect to power for extended sessions.
-
6
Use a dedicated Mac for 24/7 monitoring
A powered Mac is the preferred host for long-running monitoring. Configure login, sleep, storage, and restart behavior for your environment.
-
7
Mute audio when not needed
Decoding and playing audio requires CPU and DAC power. Mute streams you don't need to listen to.
macOS — No Restrictions
Apple TV Notes
Apple TV (tvOS) supports up to 4 simultaneous streams in the multi-camera grid. Background detection and recording are not available on tvOS — it is a viewer-only platform.