An automated AI-powered IoT algorithm with data processing and noise elimination for plant monitoring and actuating
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces an AI-powered IoT system for automated crop monitoring and action. The system uses sensors and AI to manage plant conditions, reporting remotely to farmers for improved crop health.
Area Of Science
- Agricultural Technology
- Artificial Intelligence
- Internet of Things
Background
- Traditional farming requires constant human monitoring.
- Crops like chili are sensitive to environmental changes and pests.
- Automated systems can improve efficiency and crop yield.
Purpose Of The Study
- To develop an AI-powered IoT system for autonomous crop monitoring and management.
- To enable remote reporting of plant conditions to farmers.
- To test the system's efficacy on chili plants.
Main Methods
- Designed and fabricated an AI-powered IoT system prototype.
- Integrated soil moisture, CO2, temperature, and camera sensors.
- Applied AI-based signal/image processing and noise elimination algorithms.
Main Results
- The system successfully automated actions like watering, ventilation, and pesticide application based on sensor data.
- AI algorithms effectively processed sensor data and images for decision-making.
- Pest detection on chili plant leaves achieved a 75% success rate.
Conclusions
- The developed AI-powered IoT system demonstrates effective autonomous crop monitoring and management.
- The system provides valuable remote insights into plant health for farmers.
- This technology has the potential to enhance agricultural practices and crop productivity.
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