Agriculture Based Automatic Sprinkling Robot

Agriculture Based Automatic Sprinkling Robot

Abstract

Ms. Aher Namrata G., Ms. Aher Pooja D., Ms. Mandlik Vrushali H., Ms. Pawar Someshwari R., Dr. V. A. Wankhede, Mr. N. R. Thakre, Ms. S. M. Bachhav

Dept. of Electronics and Telecommunication Engineering

SNJB's Shri Hiralal Hastimal (Jain Brothers, Jalgaon) Polytechnic Chandwad, Dist. Nashik, India

Modern agriculture faces numerous challenges, including inefficient irrigation practices, water scarcity, and increasing labor demands. This study presents the development of an agriculture-based automatic sprinkling robot designed to address these issues by leveraging automation, sensor technology, and wireless communication. The system integrates soil moisture sensors, GPS navigation, ultrasonic obstacle detection, and a vision camera into a mobile robotic platform, powered by an ESP8266 microcontroller with IoT connectivity. Real-time data on soil conditions is gathered and used to activate precision water spraying mechanisms only when and where needed, significantly conserving water. The robot is capable of autonomous navigation across the field, avoiding obstacles and ensuring targeted irrigation, while also offering Bluetooth-based remote control for manual operation. All sensor data and operational metrics are logged and accessible via a cloud-based dashboard, enabling remote monitoring and analysis. This approach not only reduces the dependency on manual labor but also ensures eco-friendly and resource- efficient farming. The system is cost-effective, scalable, and adaptable to small and medium-sized farms, making it a promising solution for promoting sustainable agricultural practices in the future.

Keywords

Agriculture Robot, Automatic Irrigation, Sprinkler System, IoT, Soil Moisture Sensor, Node MCU ESP8266, Bluetooth Control, GPS Navigation, Ultrasonic Sensor, Smart Farming, Precision Agriculture.

1. INTRODUCTION

   Agriculture continues to be the backbone of Indias economy, sustaining nearly 60% of the population through direct or indirect means. As the demand for food rises due to population growth and urban expansion, Indian agriculture has evolved by adapting to changing climatic conditions and resource availability. However, traditional irrigation techniques still dominate large parts of the country, often resulting in inefficient water use, soil degradation, and increased labor dependency. With increasing farm sizes and shifting weather patterns, manual irrigation management has become both labor- intensive and time-consuming. The need for intelligent and adaptive irrigation methods is more critical than ever. Farmers typically rely on fixed-time irrigation schedules, often lacking real-time feedback on actual soil moisture levels, which leads to overwatering or underwatering both detrimental to crop health and resource efficiency. In recent years, the convergence of automation, robotics, and Internet of Things (IoT) technologies has created new

   opportunities to optimize agricultural processes. Agricultural robots equipped with navigation, sensing, and actuation capabilities are emerging as essential tools in modern farming. These systems can perform tasks such as precision irrigation, weed detection, and autonomous movement across crop fields without requiring constant human supervision.

   Traditional methods of field assessment and irrigation decision-making often relied on manual observation and experience. However, with advancements in sensor networks, image processing, and data analytics, farmers can now receive accurate, real-time feedback from their fields. This shift not only improves decision-making but also reduces water wastage and minimizes manual effort. The use of soil moisture sensors, ultrasonic distance sensors for obstacle avoidance, and GPS modules for navigation allows robotic systems to assess field conditions and apply water precisely where needed. The integration of these technologies in an automatic sprinkling robot offers a smart, eco-friendly solution for sustainable agriculture. Additionally, remote access through mobile applications and IoT dashboards enhances usability and real-time monitoring.

   This paper explores the design and implementation of an agriculture-based automatic sprinkling robot with a focus on intelligent irrigation, resource conservation, and minimal human intervention. The study examines the technological foundation of the system, the operational framework of the robot, and its potential for transforming irrigation practices in both rural and urban farming contexts.

2. LITERATURE REVIEW

   Modern agriculture is rapidly evolving through the integration of automation, smart sensing, and robotics, aiming to resolve challenges such as intensive labor reliance and inefficient water usage. Nicolopoulou- Stamati et al. (2016) highlighted the adverse effects of agrochemicals on human health and ecosystems, underscoring the urgency for sustainable farming.[1]

   To address these needs, researchers have developed several precision-focused innovations. The dropleaf technique helps estimate spray coverage through water-sensitive markers, improving the efficiency of resource application. Machine learning-driven systems, such as those using convolutional neural networks for crop health diagnosis, have emerged for better crop monitoring and automated decision-making (Kotkar et al., 2021)[2]

   Solar-powered robotic platforms that handle field operations autonomously, as explored by Suganya & Jayaranjani (2020), offer pathways to cut energy use and improve productivity. Similarly, Chand et al. (2022) introduced a multipurpose agricultural robot integrating IoT and computer vision for tasks like spraying and irrigation.[3]

   Portable robotics based on low-cost hardware also demonstrate promise. Chaitanya et al. (2019) built an automated irrigation system using Raspberry Pi and motor drives, showcasing field-ready robotic movement with minimal human input.Further, smart irrigation models using NodeMCU ESP8266 with soil moisture and DHT sensors, deployed on farms, have shown improved water efficiency and environmental adaptation (Alsammak & Mohammed, 2022)[4]

   The integration of IoT platforms in agriculture has facilitated real-time monitoring and control. Smart systems based on NodeMCU ESP8266 relay live data from soil, humidity, temperature, and rain sensors to cloud platforms or smartphone dashboards, enabling precision control and alerts (Althaf et al., 2024)[5]

   While advanced agricultural robots have been developed globally for tasks such as weeding, mapping, and seeding using GPS, vision sensors, and autonomous navigation, irrigation-focused robotics remain underexplored. Nevertheless, many report integrating sensors to navigate fields, avoid obstacles, and apply water accurately (Kor et al., 2023)[6]

   Our proposed Agriculture-Based Automatic Sprinkling Robot builds on these advances by combining:

   • IoT-enabled real-time monitoring using NodeMCU ESP8266, soil moisture and DHT sensors, and GPS;

   • Ultrasonic obstacle detection and automated navigation;

   • Servo-controlled pump and spray nozzle for precision irrigation;

   • Bluetooth and Wi-Fi interfaces for remote control and dashboard monitoring.

   This system exemplifies the shift toward affordable, autonomous, and eco-friendly smart farming solutions for small- and medium-scale agricultural applications.

3. METHODOLOGY

   The mthodology of this project outlines the systematic approach adopted to design and implement an IoT- enabled automatic sprinkling robot aimed at reducing manual labor, optimizing irrigation, and ensuring efficient water use in agriculture. The entire process can be categorized into the following key stages:

   1. System Design and Hardware Integration

      The robot's mechanical and electronic architecture was designed to support autonomous movement and responsive irrigation. The essential hardware components integrated include:

      Microcontroller: The NodeMCU ESP8266 module was used as the core controller for managing all inputs from sensors and handling automation tasks through Wi-Fi communication.

      Motor Driver (L293D): This IC enables control of the DC motors for movement in all four directionsforward, backward, left, and rightbased on instructions from the controller.

      Motors and Chassis: A 4-wheel drive chassis system, equipped with high-torque DC motors, provides stability and smooth navigation in agricultural terrain.

      A small, servo-operated water pump, connected to a sprinkler nozzle, activates only when the system detects dry soil, ensuring water is sprayed efficiently and only when needed.

      Sensors: Soil Moisture Sensor: Continuously monitors soil water levels and informs the controller to activate/deactivate irrigation.

      DHT11 Sensor: Measures ambient temperature and humidity, helping track environmental conditions affecting irrigation cycles.

      Ultrasonic Sensor: Helps detect and avoid obstacles, ensuring safe robot navigation in fields.

      Power Supply: A 12V rechargeable battery pack powers all the components, including motors and sensors, with voltage regulation provided for the controller and pump.

      Switches and Relays: Used for manual override or emergency stop of the system when required.

   2. Control Logic and Communication

      The NodeMCU ESP8266 is programmed to fetch data from all sensors and take real-time decisions. It uses:

      Bluetooth Module (HC-05): For short-range manual control through an Android smartphone.

      Wi-Fi (Inbuilt in NodeMCU): To transmit live sensor data to a cloud-based dashboard or mobile application, enabling real-time remote monitoring and logging.

   3. Movement and Obstacle Avoidance

      Movement commands are generated either via: Manual control using a mobile app (Bluetooth) or, Autonomous mode, where the robot navigates and adjusts spraying automatically based on sensor inputs.Ultrasonic sensors detect obstacles and help the robot avoid collisions by adjusting its path accordingly, making it semi-autonomous in navigation.

   4. Sprinkling Mechanism

      The soil moisture sensor determines whether irrigation is necessary. If moisture is below a predefined threshold, the relay activates the servo pump, and water is sprayed through the nozzle for a fixed time or until the moisture is adequate.This ensures water conservation and targeted irrigation, suitable especially for dry or uneven terrain.

   5. Software and Programming

   6. Overall Workflow

      Power is supplied to the robot.Sensors initialize and begin capturing soil and environmental data. The NodeMCU microcontroller monitors real-time soil moisture levels and decides when irrigation is necessary If needed, the robot moves and activates the water pump accordingly. Live data is displayed on a connected mobile interface via Bluetooth or Wi-Fi.

      1. MODULE DESCRIPTION

         The proposed system integrates multiple hardware and software components designed to automate irrigation in agriculture. It includes a microcontroller platform programmed in embedded C, power supply circuits, DC motors, motor drivers, Bluetooth communication modules,

         and optional voice-command functionalities. These components are connected to form a cohesive unit capable of monitoring soil conditions and responding with precise sprinkler activation

         The control program was developed using the Arduino IDE, coded in Embedded C. The software handles:Sensor calibration and threshold setting,Conditional logic for water spraying,Motor driver operations, Real-time communication via Wi-Fi/Bluetooth.

         1. Microcontroller Unit (Arduino/NodeMCU)

            The heart of the system is a microcontroller boardtypically an Arduino UNO or NodeMCU, depending on the required connectivity. These boards utilize AVR or ESP8266/ESP32 microcontrollers, offering sufficient flash memory, I/O pins, and in-built features for automation control. In many setups, the NodeMCU is preferred due to its built-in Wi-Fi capability and compact design, making it ideal for real-time IoT-based irrigation. The boards support standard communication with sensors, actuators, and motor drivers through GPIO headers. Most modules also include a voltage regulator for 3.3V/5V logic and a 16 MHz crystal oscillator for timing accuracy. The compact design and pin configuration make them suitable for integration with other modules, including Bluetooth, motor drivers, and sensor interfaces.

         2. HCO5 Bluetooth Module

            The HC-05 Bluetooth Module is ideal for easy and cost- effective wireless serial communication in DIY microcontroller projects. Its flexibilityoperating as both master and slavealong with AT configurability, makes it a go-to solution for wireless robotics, IoT, and automation tasks.

         3. NodeMCU with Wi-Fi Module

            The NodeMCU is an open-source IoT development board that integrates the ESP8266 Wi-Fi module, making it ideal for projects requiring wireless communication. It comes with a built-in microcontroller and Wi-Fi capability, allowing devices to connect directly to the internet without additional hardware.. The NodeMCU can be programmed using the Arduino IDE, supports low power consumption, and offers a compact, low-costsolution for smart farming applications.

         4. ESP8266 Camera Module

            The ESP8266 Camera Module is a compact IoT-enabled device that combines the ESP8266 Wi-Fi microcontroller with an onboard camera for image capture and wireless transmission. It is designed to provide both processing and networking capabilities in a single unit, making it suitable for remote monitoring applications. In an agriculture-based automatic sprinkling system, the camera module can be used for tasks such as crop health monitoring, weed detection, and field surveillance.

         5. GPS Module

            A GPS (Global Positioning System) module is an electronic device that receives signals from satellites to determine precise geographic location in terms of latitude,longitude, altitude, and time. In an agriculture- based automatic sprinkling system, the GPS module enables accurate field mapping and navigation for the robot. By providing real-time position data, it ensures the robot follows predefined paths, avoids overlap, and covers the entire field.

         6. Water Pump

            A water pump is a crucial component in an automatic sprinkling system, responsible for drawing and delivering water to the sprinkler nozzles. In an agriculture- based robot, the pump ensures a steady and controlled water flow based on signals from the microcontroller. It is typically powered by a DC motor, allowing it to be operated directly from the robots battery supply.

         7. Spray Nozzle

            A spray nozzle is the component that controls the dispersion of water or agrochemicals in a fine mist or spray pattern. In an agriculture-based automatic sprinkling system, the spray nozzle ensures uniform coverage over crops, improving irrigation efficiency and reducing water wastage. The nozzle designsuch as fan, cone, or mist typedetermines the droplet size, spray angle, and coverage area, which can be selected based on crop tpe and field conditions.

         8. Gear Motor ×4

            Gear motors are DC motors integrated with a gearbox to reduce speed and increase torque, making them suitable for driving heavy loads at controlled speeds. In an agriculture-based automatic sprinkling robot, four gear motors are typically usedone for each wheelto provide stable movement across different terrains such as soil, grass, or uneven farmland.

         9. Motor Driver L298N ×2

            The L298N motor driver is an H-bridgebased electronic module used to control the speed and direction of DC motors. In an agriculture-based automatic sprinkling robot, two L298N drivers are often used to operate multiple gear motorsone module controlling two motors each, enabling movement of all four wheels. The L298N allows the microcontroller (such as Arduino).

         10. Chassis

             The chassis is the structural framework of the agriculture- based automatic sprinkling robot, providing support and housing for all components such as motors, sensors, battery, water pump, and sprinklers. It is designed to be strong, stable, and durable to withstand outdoor farming conditions, including uneven terrain, moisture, and dust. The chassis also ensures proper weight distribution for smooth movement and prevents tipping during operation.

         11. Ultrasonic Sensor

             An ultrasonic sensor is a distance-measuring device that uses sound waves to detect objects and measure the space between the sensor and an obstacle. In an agriculture- based automatic sprinkling robot, it plays a crucial role in autonomous navigation by preventing collisions with plants, rocks, or other field obstacles. The sensor emits ultrasonic pulses and measures the time taken for the echo to return, converting this into distance data.

         12. Volt Battery

             A 12-volt battery serves as the primary power source for the agriculture-based automatic sprinkling robot, supplying energy to all components such as motors, pumps, sensors, and the microcontroller. Its voltage level is ideal for driving DC gear motors, water pumps, and motor drivers while also being compatible with voltage regulators for powering lower-voltage electronics.

         13. DHT Sensor

             A DHT sensor is a digital temperature and humidity sensor used to monitor environmental conditions in real time. In an agriculture-based automatic sprinkling robot, the DHT sensor measures ambient temperature and relative humidity, providing essential data for irrigation decisions. This helps optimize water usage by preventing irrigation during high humidity or unsuitable weather conditions.

         14. Soil Moisture Sensor

             A soil moisture sensor is a device used to measure the water content in the soil, helping determine when irrigation is required. In an agriculture-based automatic sprinkling robot, this sensor plays a key role by sending real-time soil moisture data to the microcontroller, which then decides whether to activate the water pump and sprinklers. This data ensures water is only supplied when needed, preventing overwatering or underwatering of crops.

         15. Servo Motor

A servo motor is a rotary actuator that allows precise control of angular position, speed, and torque using a control signal. In an agriculture-based automatic sprinkling robot, the servo motor is often used for controlling the direction of spray nozzles, adjusting camera angles, or operating small mechanical arms for tasks like weed removal.

Step-by-step Process:

1. System Start: The robot system powers on and prepares for operation.

2. Configure I/O Ports: The microcontroller sets up all digital and analog ports required for communication and actuation.

3. Activate Bluetooth Module: The Bluetooth interface (e.g., HC-05) is initialized to establish a wireless link with the Android device.

1. FLOWCHART FOR ROBOT OPERATION

2. CONSTRUCTION OF THE SPRINKLER

   The construction of the automatic sprinkler irrigation system follows a structured and modular approach inspired by the operational logic outlined in the robot control flowchart. This framework guides each step, from planning to implementation, ensuring consistency and functional integrity.

   In the initial design phase, strategic decisions were made regarding the placement of sprinkler nozzles, soil moisture sensors, and temperature sensors to ensure comprehensive irrigation coverage and precise environmental monitoring. The system employs an Arduino-based controller, programmed using embedded C language, to manage hardware components such as DC motors, motor drivers, and sensors.

   During assembly, the Arduino board was integrated with the Bluetooth module for wireless communication, allowing users to control the robot remotely via a mobile application. The control commandssuch as start, stop, left, right, and sprayare executed based on button input or voice recognition (ASR), enhancing accessibility.

   To optimize performance, the sprinkler system was designed for uniform water distribution using servo- controlled water pumps. Pipes and nozzles were placed considering field layout and pressure dynamics. The system allows flexible operation, making it suitable for both small farms and gardens.

   The entire construction process emphasized adaptability and reliability. Rigorous testing was performed at each stage to ensure proper functioning of the electronics, mobility of the robot, and effective water delivery. Upon validation, the system was fine-tuned for optimal irrigation efficiency. This architecture not only simplifies the automation of irrigation but also promotes scalability and maintenance.

3. RESULTS AND DISCUSSION

   The Bluetooth-controlled automatic sprinkling robot showed effective performance in addressing irrigation challenges. It combined wireless control and automated water distribution based on real-time soil moisture data, leading to optimized water usage and minimal waste. The robots mobility and sensor-based operation ensured targeted and need-based irrigation, improving crop care especially on small and medium farms. The system maintained stable Bluetooth connectivity, allowing farmers to control and monitor it remotely via a mobile app. It also featured low power consumption and potential solar integration, supporting eco-friendly use. Economically, the system used affordable components, making it a budget-friendly solution for farmers. Its adaptability to different field sizes and crop types increases its practical value. Environmentally, it reduced manual labor, pesticide overuse, and chemical runoff, contributing to soil health and sustainability. While quantitative data collection is ongoing, early results confirm its practical efficiency and potential for wider application.

4. CONCLUSION AND SCOPE FOR FUTURE

WORK

The developed system marks a step forward in modern farming by combining automated irrigation and pesticide spraying using real-time sensor data and Bluetooth control. It improves crop care, labor efficiency, and environmental impact. Future improvements could include AI for predictive control, wider connectivity (e.g., Wi-Fi), integration with weather data, and solar-powered operation. This work sets the groundwork for advanced, smart, and sustainable farming technologies.

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