Group Members:
1. Atina Ahza Maisarah Binti Mohd Nazrin (212020638)
2. Vinnie Ng Xiao Xuan (212021432)
3. Nurin Adila binti Mohd Nazri (212020798)
4. Nur Aleyah Aisya Rosidin (212020782)
5. Nur Hannan Najihah binti Mohd Haffiz (212020790)
1.0 Introduction
Agriculture has been a cornerstone of human civilization, revolutionizing economies and fueling industrial progress. Temperature and humidity control are pivotal for healthy plants, impacting transpiration and nutrient absorption. Ideal humidity in grow rooms ranges from 50% to 70% during vegetative growth and 50% to 60% during flowering. Soil moisture is critical, influencing crop yields and essential plant functions like photosynthesis and nutrient transportation. Precise irrigation schedules are vital. When soil moisture aligns with plant needs, water is absorbed efficiently, dissolving salts to create a nutrient-rich soil solution. Overall, agriculture's impact on civilization, coupled with environmental control, underscores its significance in human survival and progress.
2.0 Problem Statement
In today's context, maintaining the quality and health of palm oil production faces growing challenges , primarily due to unfavorable soil conditions and unpredictable weather patterns within palm oil plantations. The vast expanses of these plantations, often spanning thousands of hectares, present a considerable obstacle for manual monitoring by laborers who need to assess soil suitability and health for palm oil cultivation. To tackle this issue, an IoT-based soil monitoring system is being developed. This system will aid workers in monitoring crucial soil parameters for palm oil cultivation, such as pH levels, moisture content and temperature. The data collected will be processed and managed through a cloud-based system, enabling efficient analysis and informed decision-making to ensure the optimal growth of palm oil trees.
3.0 Objectives
The main objective that can be defined the project outcomes are:
• To develop monitoring system using microcontroller integrated with various sensor.
• To develop an application that monitor pH, soil moisture and temperature.
• To develop a cloud base system to manage the data from these systems.
4.0 Project Scope
This project is focused on developing a
device that can detect the pH, temperature, moisture, light intensity and rain
presence levels in a palm oil's soil using internet of things (IoT) technology.
The sensors will collect data on soil conditions, including moisture levels, pH level and temperature. The Arduino Uno board and ESP32
microcontroller will be used to manage all sensor data and connect it to the
cloud services. The Blynk application is the cloud service used. Blynk apps can
be used on devices such as laptops or mobile phones with the tip of a finger,
making it easy to monitor the data.
5.0 Literature Review
5.1 IoT Soil Monitoring based on LoRa Module for Oil Palm Plantation
An Arduino-based Internet of Things (IoT) layer monitoring system based on LoRa (Low Range) is the focus of this project. By implementing Internet of Things (IoT) in the agricultural sector, the "Industry 4.0" project increases palm oil production. Most oil palm plantations are in rural, remote areas without access to the internet. As a result, LoRa introduces a novel approach to implementing IoT in agriculture. This undertaking utilizes Thingspeak, Arduino, TTGO LoRa SX1278 ESP32 (OLED) , and a pH sensor to gauge corrosiveness or alkalinity with a scope of 0 to 14 for information collection[5]. A dampness sensor is expected to oversee water system frameworks and to identify soil dampness levels. Additionally, the data will be presented to employees via a mobile application. Figure 2.1: The components of project IoT Soil Monitoring based on LoRa Module for Oil Palm Plantation show the components of the project.
The difference between IoT Soil Monitoring based on LoRa Module for Oil Palm Plantation and Soil Monitoring System for Palm Oil Using IoT are does not use LORA technology to save on material costs, but uses other sensors to improve their efficiency including NPK and temperature.
6.0 Methodology
6.1 Flow Chart
Figure below is the
flowchart in the process for making a project monitoring system for palm oil
using IoT. When the component is prepared and the sensor is positioned in the
soil, the project's procedure begins. A specified value for good soil for palm
oil will be detected by a sensor. Soil NPK sensor will detect
nitrogen(870-2600gms), phosphorus(1250-3750gms) and potassium(670-2000gms). The
acidity level pH value is ranging from 5-6.9. Besides, the optimum moisture
level for palm oil is between 30% to 75% and temperature sensor will detect
between 20-33 degrees Celsius(°C). The soil will be suitable for planting oil
palm trees, with the understanding that there will be some restrictions and
limitations. Next, the Blynk applications will provide the data in graphical
and numerical representations for temperature, pH and capacitive soil wetness. The data will also be
shown on the LCD.
6.2 Hardware Development
6.2.1 Arduino Uno Board
The Arduino Uno is a popular
microcontroller board, featuring an ATmega328P microcontroller, providing a
versatile platform for building interactive electronic projects. It offers 14
digital input/output pins, 6 analog inputs, a 16 MHz quartz crystal, USB
connection for programming, and power jack. Its compact size and ease of use
make it ideal for beginners and hobbyists to create various devices, from
simple LEDs and sensors to complex automated systems. The Uno is programmed
using the Arduino IDE, facilitating code development for a wide range of
applications, making it a fundamental tool in the maker and electronics
community.
6.2.2 ESP32 Board
The ESP32 is a low-cost System on Chip (SoC) Microcontroller designed for Internet of Things (IoT), wearable electronics, and mobile applications. Similar to ESP8266's advantages, ESP32 has some. Furthermore, because few external components are required, it is quite easy to build hardware around the ESP32. A 32-bit LX6 microprocessor with a 240 MHz clock frequency is supported, and it has a single or twin core model. Handles BLE requirements and Old Bluetooth v4.2, as well as 802.11 b/g/n Wi-Fi connections up to 150 Mbps. It is available in single-core and dual-core versions. The Arduino IDE will be used to write code for the ESP32. Figure below shows an ESP32 and their label.
6.3.5 Gravity Analog PH Sensor/Meter Kit
The Gravity Analog pH Sensor/Meter Kit is a sensor kit designed for measuring pH levels in liquids. It includes a pH sensor probe, a signal processing board, and connecting cables. The kit can be connected to a microcontroller, such as an Arduino, to display the pH levels on an LCD screen or send data to a computer or mobile device. The sensor probe is designed for long-term use and can be easily cleaned and calibrated. The Gravity Analog pH Sensor/Meter Kit is ideal for use in a variety of applications, including hydroponics, aquariums, and environmental monitoring, where pH levels are critical to maintaining optimal conditions. Figure below show the gravity analogue pH sensor.
6.3.6 DS18B20 Temperature Sensor
The waterproofed DS18B20 sensor, as shown in Figure 3.7 has pre-wired connections and may be used to measure objects that are far away or that are wet. While utilising the Sensor, the temperature ranges from -55°C to 125°C (or -67°F to +257°F). The jacket of the cable is made of PVC. These 1-wire computerised temperature sensors are extremely accurate, with a range of 0.5°C. They are compatible with any microcontroller that has a single digital pin. The sensor must also be pulled up from the DATA line to the VCC line using a 4.7k resistor.
6.3.7 Capacitive Soil Moisture Sensor
The moisture content of the soil must be measured using a soil moisture sensor. For this purpose, a capacitive kind of soil moisture sensor is suggested. We will use an analogue capacitive soil moisture sensor to measure the quantity of soil moisture. This demonstrates that the capacitance changes with soil moisture content. The voltage level that the translated measured capacitance often falls between 1.2V and 3.0V at its peak. Capacitive soil moisture sensors have a long service life since they are made of a material that resists corrosion. The Capacitive Soil Moisture Sensor v2.0 has an operating voltage range of 3.3V to 5.5V DC. The output is in analogue format up to a maximum of 3V.. The output voltage can be transformed into a percentage value. Figure 3.8show the capacitive soil moisture sensor.
6.3.8 LCD Display 20x4
A 20x4 LCD (Liquid Crystal Display) is a type of alphanumeric display that contains 20 columns and 4 rows of characters. It is commonly used in electronic devices such as embedded systems, meters, and instruments that require the display of text, numbers, and symbols. The display can be controlled by a microcontroller or other electronic device, and can be programmed to display custom characters or graphics. The 20x4 LCD display is an improvement over the 16x2 LCD display, as it provides more characters per line, allowing for more information to be displayed. It is widely used in industrial and consumer applications due to its versatility and ease of use. Figure below show the example of LCD display.
6.4 Software Development
6.4.1 Arduino IDE
Arduino IDE (Integrated Development Environment) is a software platform used for programming microcontrollers, such as the Arduino. It is a free and open-source application that allows users to write, compile, and upload code to their Arduino boards. The IDE comes with a code editor, a compiler, and a bootloader that enable users to upload code to their boards using a USB cable. Arduino IDE also includes a library of pre-written code that can be used to add features to your projects, such as controlling sensors and motors. The IDE supports a simplified version of C++ programming language, making it easier for beginners to learn coding. Overall, Arduino IDE is an essential tool for developing Arduino projects. Figure below show the Arduino IDE.
6.4.2 Blynk App
Blynk is a mobile app platform for IoT devices that lets users remotely control and monitor their projects. Compatible with Arduino, Raspberry Pi, and ESP8266, it offers a drag-and-drop interface to create custom interfaces for projects, including buttons, sliders, and gauges. Blynk also provides a range of tools such as notifications, email/SMS alerts, data logging, and others. Blynk is also a powerful platform that can serve as a cloud storage solution for soil monitoring project. It because Blynk offers a user-friendly interface to create custom IoT applications and connect various sensors, devices, and microcontrollers to the cloud. By utilizing Blynk as cloud storage, it can securely store and access data collected from the project.
7.0 Results and Discussions
Video Simulation
This is the position on how each sensors will operate. All the sensors are dig into the soil to receive input and send it to ESP32 to display output. Gravity Analog PH sensor is connected to Arduino Uno while DS18B20 Temperature Sensor and Capacitive Soil Moisture sensor is connected to ESP32.
7.2 Hardware Result
Figure below shows the LCD display output that measures 3 sensors and values. LCD display provides real-time information to the user about temperature, soil moisture, and soil pH levels, all of which are monitored by sensors. This system offers users a comprehensive overview of the environmental conditions affecting the plants. The LCD display serves as a user-friendly interface, presenting essential data for informed decision-making in managing the plant or crop environment. This integrated setup enables users to track and respond to changes in temperature, soil moisture, and pH levels, promoting effective cultivation and ensuring optimal growth conditions for plants.
7.3 Software Result
In the innovative integration of an LCD display with DS18B20 Temperature Sensor, Capacitive Soil Moisture sensor, and Gravity Analog PH sensor, the aim is to provide users with real-time and accurate data through a Blynk app interface. This sophisticated system ensures that users can conveniently monitor crucial environmental parameters for optimal plant growth. The Blynk app offers remote accessibility for more convenient monitoring. However, potential disparities in the displayed data may arise due to the presence of delays in the system. These delays, inherent to the communication between the sensors, the microcontroller, and the Blynk app, can lead to a slight lag in data synchronization. It's important to understand that any observed differences between the LCD display and the Blynk app results can be attributed to these inherent delays, and they do not indicate inaccuracies in the sensor readings themselves.
8.0 Conclusion & Future Work
In conclusion, the project "Soil Monitoring System using IoT" has demonstrated its capacity for effective connectivity, data collecting, and cloud integration. It successfully collected vital information on the state of the soil by integrating a number of sensors, including temperature, pH, and soil moisture. After extensive testing and debugging, it was determined that the ESP32 and Arduino UNO microcontrollers could reliably transmit data to the Blynk cloud-based system. This simulation offers a strong foundation for real-world application and permits data-driven decision-making and remote monitoring in palm oil plantations.
A few things that can be added to this project's gadget for future work. The first thing is integrate more sensors for comprehensive soil analysis, such as sensors for measuring nutrients like nitrogen, potassium, phosphorus or sensors for detecting salinity levels. This is because high levels of salinity in soil can adversely affect plant growth. So, detecting salinity levels can helps farmers take corrective actions, such as adjusting irrigation practices or choosing suitable crops for specific soil conditions. At the same time, enhance the system's connectivity by using more advanced wireless protocols like LoRa or Zigbee for longer-range communication or in areas with poor connectivity. So, this protocols suitable for monitoring soil conditions across larger agricultural areas or in remote locations with poor connectivity. Besides that, implement algorithms to analyze data collected from multiple sensors together to derive more meaningful insights about the soil condition. Algorithms can identify correlations and relationships between different soil parameters. For example, they can analyze how soil moisture levels correlate with temperature variations or how pH levels affect nutrient availability. Understanding these interrelations can provide deeper insights into the soil's overall condition and its impact on plant growth.
