An IoT-enabled Intelligent Indoor Plant Health Monitoring and Recommendation Framework
Keywords:
Artificial intelligence, DHT11, ESP32, Indoor plant monitoring, IoT, LDR sensor, Smart garden, Soil moisture sensor, Sustainable garden, Web dashboardAbstract
Indoor gardening has gained popularity due to its positive impact on mental well-being, stress reduction, air purification, and environmental sustainability. Indoor plants enhance emotional health, improve concentration, and create a calming atmosphere. However, maintaining healthy indoor plants is often challenging. Busy lifestyles limit the time available for plant care, and many individuals lack sufficient knowledge about proper watering, lighting, temperature, and humidity management. As a result, plants may suffer from improper care, leading to poor growth or early damage. To address these challenges, the smart mindful garden is proposed as an IoT-based system designed to monitor and support indoor plant health. The system uses an ESP32 microcontroller integrated with soil moisture, temperature, humidity, and light intensity sensors to collect real-time environmental data. This data is transmitted through Wi-Fi to a cloud-connected web platform for monitoring and analysis. The system applies rule-based artificial intelligence using predefined threshold values based on plant care guidelines. When environmental conditions deviate from optimal ranges, the system generates alerts and recommendations, such as watering reminders or light adjustment suggestions. A web-based dashboard displays real-time readings, historical trends, and notifications in a user-friendly format, enabling remote monitoring and informed decision-making for effective indoor plant care.
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