Project Description of IoT Based Robot Monitoring and Controlling Soybean Field Soil Condition
The goal of Robot Monitoring and Controlling Soybean Field Soil Condition project is to develop a system to monitor and control the soil conditions of a soybean field using a K-Nearest Neighbor algorithm and Message Queuing Telemetry Transport (MQTT) protocol. The system will be deployed in the field using sensors and an MQTT gateway. The sensors will collect data on soil temperature, moisture, and pH levels which will be sent to a cloud-based server (thingspeak) via the MQTT protocol. The server will then process the data using a K-Nearest Neighbor algorithm to determine if the soil conditions are suitable for soybean growth. If the soil conditions are not suitable, the server will send commands via the MQTT protocol to the gateway to activate soil-conditioning equipment such as pumps, sprinklers, and fertilizers.
In order to ensure accuracy and reliability of the system, the sensors will be calibrated to ensure they are accurately measuring the soil conditions. The MQTT gateway will be used to securely transmit the data from the sensors to the server. The server will then use the K-Nearest Neighbor algorithm to analyze the data and determine the soil conditions. If the soil conditions are not suitable, the server will send commands to the gateway to activate the soil-conditioning equipment.
Hardware and software requirements for Robot Monitoring and Controlling Soybean Field Soil Condition project implementation:
Hardware Requirements of Robot Monitoring and Controlling Soybean Field Soil Condition:
- Sensors: The sensors required for monitoring and controlling the soil conditions in a soybean field are Temperature sensor, Humidity sensor, Soil moisture sensor, pH sensor and light sensor.
- DHT11 sensor: It is used to check the temperature and humidity of the soya bean field.
- Soil-moisture sensor: This will check the current status of the moisture in the soil which can be connected to analogy pin or digital pin.
- pH sensor: This is used to measure the pH level in the water and is used them in the soil.
- Raspberry Pi: A microprocessor such as raspberry pi is required to receive data from the sensors and process them
- Communication Module: A communication module such as GSM/GPRS is needed to send the data from the microprocessor to the cloud.
- Server: A server is needed to store the data sent from the microprocessor and process it using the K-Nearest Neighbor Algorithm.
- Power Supply: Utilized to supply electric power to an electrical load.
- MQTT Protocol: The Message Queuing Telemetry Transport protocol is used to send the data from the server to the cloud.
- Thingspeak: To check the current status of the sensors data uploaded to cloud, thingspeak dashboard is used to monitor it.
Software Requirements of Robot Monitoring and Controlling Soybean Field Soil Condition:
- Programming Language: A programming language such as Python is needed to program the Raspberry pi.
- K-Nearest Neighbor Algorithm: The K-Nearest Neighbor Algorithm is used to process the data sent from the microprocessor.
- MQTT Protocol: The Message Queuing Telemetry Transport protocol is used to send the data from the server
What You Will Learn? By working on the project
- Gain experience in the fields of embedded systems, robotics, data science, and machine learning.
- Cloud computing and data management: Learn the fundamentals of K-Nearest Neighbor Algorithm and Message Queuing Telemetry Transport Protocol (MQTT).
- Understand the principles of soil science and agriculture.
- Hardware and software : Design and develop a robotic system capable of monitoring and controlling the soil condition in a soybean field.
- Algorithm: Implement the K-Nearest Neighbors Algorithm to analyze the data from the soil sensors.
- Utilize the MQTT protocol to communicate with the robotic system.
- Project management: Develop a user interface for controlling the robotic system.
- Create a system for collecting and analyzing the data from the robotic system
- Analyze the data to provide insights into the soil condition in the soybean field.
