The rapid growth of precision agriculture demands intelligent monitoring systems that can optimize water usage, improve crop productivity, and reduce energy consumption. This project presents an Energy-Efficient All-Dynamic Multiparameter Sensor System for Battery-Less Smart Nodes in Agricultural Internet of Things (AIoT) using a Raspberry Pi Zero 2W as the central processing unit. The system continuously monitors important environmental parameters such as soil moisture, temperature, humidity, rainfall, and light intensity using a Capacitive Soil Moisture Sensor, DHT22 Sensor, Rain Sensor, and LDR Module. The status of the project will display on LCD. Here Arduino NANO  works as a ADC converter.

The collected sensor data is transmitted to a web-based monitoring platform, allowing farmers to remotely observe real-time field conditions from anywhere through the internet. To enhance decision-making, the system incorporates Machine Learning algorithms that analyze past and present sensor data to predict future soil moisture levels and weather conditions. Based on these predictions, the system intelligently determines the irrigation requirements of the field.

An automatic irrigation control mechanism is implemented using a relay-driven AC water motor. When the predicted soil moisture level falls below a predefined threshold and no rainfall is expected, the system automatically activates the water motor. Similarly, the motor is turned OFF when sufficient soil moisture is achieved or rainfall is predicted, thereby preventing water wastage and improving irrigation efficiency.

The proposed battery-less and energy-efficient architecture minimizes maintenance requirements while ensuring continuous operation. By integrating IoT, Machine Learning, cloud monitoring, and automated irrigation control, the system provides a smart, sustainable, and cost-effective solution for modern agriculture, helping farmers conserve water, reduce labor, and maximize crop yield.

Objectives:

1. To monitor soil moisture, temperature, humidity, rainfall, and light intensity using sensors.
2. To display sensor data on a web page for remote monitoring.
3. To display sensor data on LCD for local monitoring.
4. To store sensor data for future analysis.
5. To predict future soil moisture levels using Machine Learning.
6. To forecast weather conditions based on collected sensor data.
7. To automatically control the AC water motor using a relay.
8. To reduce water wastage through smart irrigation.
9. To improve crop growth and agricultural productivity.
10. To minimize human effort in irrigation management.
11. To develop an energy-efficient IoT-based smart farming system.

The major building blocks of the project are:

• Regulated Power Supply.
• Raspberry pi zero 2W.
• Arduino NANO.
• SD card.
• LDR sensor.
• DHT22 sensor.
• Capacitive Soil sensor.
• Rain sensor.
• Relay with AC motor.
• LCD display.

Software’s used:

1. Raspbian OS.
2. Machine Learning.
3. Express SCH for Circuit design.

Block diagram:

video:

We can even set up this in our home and get alerts for time-to-time changes in climate which would help us in planning our daily work easily. It would be helpful for a farmer in this agricultural activity by which he can protect his crops according to climatic changes. It would help in transportation giving information of weather conditions.

Internet of things, IoT, as an important part of the new generation of information technology, have developed rapidly both in theory and practice since proposed and derived many applications such as smart home, intelligent environmental monitoring. Things not only liberated a lot of manpower, but also achieved a standardized, automated management.

The main aim of this project is to design a smart way of weather monitoring system using cloud storage technology based on wireless Wi-Fi communication and wireless voice alert based on RF technology. The weather parameters are monitored using sensing devices like rain sensor, temperature and humidity sensors. Then the collected data and analysis results will be available to the user through Wi-Fi to the cloud storage and provides thing speak. When the system detects any abnormal condition, it will give the voice alert wirelessly through speaker. The status of the project will display on LCD. This data will be helpful for future references. The smart way to monitor environment this device is an efficient low-cost embedded system.

The major building blocks of this project are:

1. Adapter power supply.
2. Raspberry pi4.
3. DHT22 sensor
4. Rain sensor.
5. LCD display.
6. SD Card.
7. RF transmitter, receiver.

Software’s used in the project:

1. Raspbian OS.
2. Python language.
3. Express SCH for Circuit Design.
4. THINGSPEAK CLOUD.

Block diagram:

video:

1. Adapter power supply.
2. Arduino UNO.
3. DHT22 sensor.
4. Soil moisture sensor.
5. LCD display with I2C.
6. ESP8266 WI-FI module.

Software’s used in the project:

1. ARDUINO IDE.
2. Embedded C language.
3. MYSQL.
4. Express SCH for Circuit Design.

Video: