iot-anomaly-detection
CommunityDetect IoT anomalies, enhance agronomic automation.
AuthorLNieto-V
Version1.0.0
Installs0
System Documentation
What problem does it solve?
The iot-anomaly-detection skill addresses the issue of detecting and managing anomalies in IoT sensor data for agronomic purposes, improving automated control and security in smart greenhouses.
Core Features & Use Cases
- Anomaly Detection: Evaluate telemetry against agronomic thresholds to detect and flag anomalies in sensors such as temperature, humidity, and pH levels.
- Proactive Decision Making: Implement automatic actions based on anomaly detection, minimizing the risk of plant damage or system failures.
- Use Case: Automatically trigger ventilators and turn off irrigation in case of detected extreme temperatures or humidity levels.
Quick Start
Analyze IoT data for anomalies using the iot-anomaly-detection skill with 'analyse-iot-data -f path_to_sensor_data_file'.
Dependency Matrix
Required Modules
fastapisupabasegeminipydantic
Components
scriptsreferencesassets
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: iot-anomaly-detection Download link: https://github.com/LNieto-V/agronexus_ai/archive/main.zip#iot-anomaly-detection Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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