Weather Station – Automating Crop Health Monitoring for Farmers.
A student from Codeavour2021 created this project with the aim of simplifying crop monitoring for farmers. The project helps farmers automate the monitoring of their crops’ health by providing information about the humidity and temperature of the surroundings, wind detection, soil moisture levels, water level, and plant health. With the use of Artificial Intelligence (AI) and Machine Learning techniques, the project helps farmers to better manage their crops.
The developers utilized PictoBlox extensions such as Sensors Blocks for evive and Arduino boards, Actuators blocks for DC motors and servos connected to evive and Arduino boards, Text to Speech blocks, and Dabble blocks to enable evive and Arduino boards. The Dabble Extension had all the blocks that enable evive and other Arduino boards to communicate with Dabble. The designers created a screen with five buttons, including Humidity, Temperature, Soil Moisture, Water Level, and Plant Health Detection, to further simplify the system.
They used the DHT Sensor to calculate the humidity and temperature of the surroundings and inserted the same device into the soil to measure the soil moisture. They trained the computer for Plant Health Detection based on an image of a plant using the Teachable Machine. The project further provides the suggestion of visiting a nearby Krishi Kendra for an unhealthy plant.
