The Smart Indoor Plant Care System is an IoT-based solution that automates plant care by monitoring soil moisture, temperature, humidity, and light intensity. The system uses these sensor inputs to automatically water the plant and control lighting, ensuring optimal conditions for growth. Additionally, it provides real-time feedback to users through a mobile/web interface.
1. Components Required
SIPEED MAXDUINO IoT Kit: Core controller and connectivity.
Soil Moisture Sensor: To monitor the soil moisture level.
Temperature and Humidity Sensor: To keep track of environmental conditions.
Light Sensor: To measure the light intensity the plant receives.
Water Pump and Reservoir: For automated watering.
LED Grow Lights: To provide additional light when needed.
Camera Module: For visual monitoring of plant health.
Breadboard: for connecting components and jumper wire.
Jumper Wire: According to the project, it depends.
2. Circuit Diagram Explanation
The project utilizes the SIPEED MAXDUINO IoT Kit as the main controller, interfacing with multiple sensors and actuators. Here’s a breakdown of the components used in the system:
SIPEED MAXDUINO: The core microcontroller that collects data from sensors and controls the system.
Soil Moisture Sensor: Measures the moisture level of the soil to decide when to water the plant.
DHT11 Temperature & Humidity Sensor: Monitors environmental conditions to ensure they are within optimal ranges.
LDR (Light Dependent Resistor): Measures light intensity and controls grow lights accordingly.
Water Pump: Automatically irrigates the plant when the soil moisture falls below a threshold.
Relay Module: Used to control the water pump and external devices like grow lights.
LED Grow Lights: Ensures the plant receives sufficient light when natural light is insufficient.
The circuit diagram will show how these components are connected to the SIPEED MAXDUINO’s GPIO pins.
3. Code Explanation
The code is divided into several key functions, each managing a specific part of the system.
Sensor Readings:
The soil moisture sensor data is read to check the current moisture level.
The DHT11/22 sensor reads temperature and humidity data, which is used for future improvements, such as automatic climate control.
The LDR measures ambient light intensity and is compared with a predefined threshold to decide whether to turn on the grow lights.
Watering Logic:
If the soil moisture level drops below a set threshold, the water pump is activated via the relay module, and it waters the plant until the moisture reaches an acceptable level.
Light Control:
Based on the light sensor data, the system decides whether to activate the grow lights to supplement the natural light.
Real-Time Monitoring:
Sensor data is continuously uploaded to a cloud server for storage and analysis. Users can access this data through a web interface to monitor plant health and get real-time alerts if action is required.
Automation:
The system runs automatically without the need for manual intervention. All decision-making (watering, lighting control) is done based on real-time sensor readings.
4. Working Demonstration
Step 1: Sensor Data Collection
The soil moisture sensor constantly monitors the soil's moisture content. Similarly, the temperature, humidity, and light sensors gather data in real-time. All sensor data is processed locally on the SIPEED MAXDUINO.
Step 2: Automated Watering
When the moisture level drops below the predefined threshold, the water pump is activated. Once the desired moisture level is reached, the system turns off the pump.
Step 3: Light Control
If the light sensor detects that the natural light is insufficient, the system automatically turns on the LED grow lights to provide the necessary illumination for plant growth.
Step 4: Real-Time Feedback
The data from the sensors is sent to a cloud service, allowing users to access the system remotely. Users receive notifications if the plant needs attention, such as refilling the water tank or adjusting the system.
Step 5: Health Monitoring (Optional AI Integration)
The camera module can be used to capture plant images, which are analyzed by AI algorithms to detect signs of plant health issues like diseases or pests. The system can alert users when it detects abnormalities.
5. Project at Various Stages
Showcasing the following stages:
Initial Hardware Setup: The assembled hardware components (SIPEED MAXDUINO, sensors, water pump, etc.) on a breadboard or final enclosure.
Wiring & Circuit Connections: Displays the connections between the MAXDUINO and the sensors, relays, water pump, and grow lights.
Sensor Testing: Showing the system in action, testing individual components like the soil moisture sensor and grow light control.
Final Working Setup: Displays the system in operation with the plant, demonstrating automated watering and lighting control.
User Interface: Real-time monitoring dashboard, displaying sensor data and plant conditions.
Click on the GitHub Image to view or download the code
