FUNCTION 01
System Control
Manual system activation, zone-specific misting, cycle control, and emergency stop functionality
Home Assistant 整合
Home Assistant · Python · ESPHome
Moogo Mosquito Misting System
Complete Home Assistant integration for Moogo automated mosquito misting systems
Moogo is an advanced automated mosquito misting system that provides comprehensive outdoor mosquito control through precisely timed releases of EPA-registered pyrethrin-based insecticide mist. Unlike portable repellent devices, Moogo installs as a permanent perimeter system with strategically placed nozzles that create an invisible barrier around your entire outdoor living space.
Features
3 system functions
Integration Features
Comprehensive control over your automated mosquito misting system.
FUNCTION 02
Schedule Management
Create, modify, and override misting schedules with precise timing control and seasonal adjustments
FUNCTION 03
Monitoring & Diagnostics
Track system status, reservoir levels, nozzle health, pump operation, and maintenance alerts in real-time
Entities
4 entity groups
Available Sensors & Controls
Monitor every aspect of your misting system in real-time.
Spray Timing & Status
- Last mist cycle time
- Next scheduled mist
- Mist duration (seconds)
- Active misting status
- Cycles completed today
System Health
- System status (active/idle/maintenance)
- Insecticide reservoir level (%)
- Pump pressure (PSI)
- Nozzle diagnostics & health
- Last maintenance date
Zone Configuration
- Zone 1: Front yard
- Zone 2: Backyard patio
- Zone 3: Pool area
- Zone 4: Side yard
Controls
- Manual mist activation (immediate)
- Zone enable/disable toggles
- Mist duration control (15-60s)
- Schedule override (pause/resume)
- Emergency stop button
Automations
4 recipes
Advanced Home Assistant Automations
Without this integration, systems operate in isolation with only basic scheduled behaviors. Home Assistant integration unlocks sophisticated automation capabilities:
AUTOMATION 01
Weather-Integrated Misting
Automatically adjust misting schedules based on real-time weather conditions. Skip misting cycles during rain, high wind, or extreme temperatures when effectiveness is reduced. Increase misting frequency during warm, humid conditions when mosquito activity peaks. Integrate with local weather forecasts to optimize timing.
Example: "Before each scheduled mist cycle, check weather conditions. Skip if current rain detected, wind above 15mph, or temperature below 50°F or above 95°F. During high humidity (>70%) and temperature 75-85°F, add extra evening mist cycle. Check hourly forecast and delay misting if rain expected within 2 hours."
AUTOMATION 02
Presence-Aware Protection
Coordinate misting cycles with outdoor activity and presence detection. Delay misting when people or pets are detected in outdoor areas, then automatically resume after spaces clear. Integrate with door sensors, outdoor cameras, and motion detectors to prevent misting during active use while ensuring protection before outdoor activities.
Example: "When back door opens or patio motion detected, delay any scheduled misting for 30 minutes. If patio occupied during scheduled mist time, queue cycle and execute 15 minutes after last motion detected. Send notification before initiating delayed mist cycle. Automatically mist all zones 30 minutes before calendar event labeled 'outdoor'."
AUTOMATION 03
Smart Reservoir Management
Proactively monitor insecticide levels and predict when refills are needed based on current usage patterns and upcoming schedule. Send graduated alerts as levels decrease, automatically add refill reminders to shopping lists, and adjust misting intensity to extend reservoir life when running low. Track consumption trends to optimize purchasing.
Example: "Monitor reservoir level continuously. At 40%, send informational notification with estimated days remaining based on current schedule. At 25%, add 'Moogo Refill' to shopping list with urgent priority. At 15%, send critical alert and suggest reducing mist duration by 30% to extend remaining supply. Track monthly consumption and predict next refill date."
AUTOMATION 04
Seasonal Schedule Optimization
Automatically adjust misting frequency and timing based on mosquito season, temperature trends, and daylight hours. Increase protection during peak mosquito months (typically May-September in most climates) and reduce or pause during winter dormancy. Adapt dawn and dusk misting times as sunrise/sunset times shift throughout the year.
Example: "During mosquito season (April-October), execute full misting schedule: 30 minutes before sunrise, 30 minutes before sunset, and additional cycle at 10pm. During shoulder season (March, November), reduce to sunset misting only. December-February, suspend all automatic misting. Adjust all dawn/dusk-relative times based on actual sunrise/sunset for current date."
Installation
HACS · PyPI · GitHub
Installation & Support
METHOD 01 · HOME ASSISTANT
HACS installation
Install directly from HACS (Home Assistant Community Store). This is the easiest method and provides automatic update notifications.
新增至 Home AssistantManual sequence
- 01Open Home Assistant and navigate to HACS
- 02Search for 'Moogo' in the Integrations section
- 03Click Download and wait for installation to complete
- 04Restart Home Assistant and add the integration from Settings → Devices & Services
METHOD 02 · PYTHON
Python library
For developers building custom integrations or scripts, the underlying Python library is available on PyPI.
pip install pymoogoREQUIREMENTS
- Home Assistant 2025.11.0 or newer
- Active Moogo account with configured misting system
- Moogo system connected to Wi-Fi and operational
SOURCE CODE
GitHub
View the source, report an issue, or contribute to the project.
在 GitHub 上查看 ↗OPEN SOURCE · COMMUNITY MAINTAINED
This integration is an unofficial, open-source project developed by the Home Assistant community. It is not affiliated with or endorsed by Moogo, Inc. The integration is actively maintained with regular updates to support new features and system configurations. Community contributions and feature requests are welcome on GitHub.