Smart Plant Monitoring System Using IoT Technology

Nowadays, one can observe the arrival of several mechanical techniques in the agricultural sector. To make the technology accessible to everyone at an affordable cost and to diminish workload for farmers by making it easier to control and understandable, there should be the presence of new technology and it is IoT, which is elaborated as Internet of Things. Usually, Internet of Things is defined as the number of gadgets are connected through wireless networks such as Wi-Fi, SIM networks, etc. IoT technology in the agricultural sector might create wonders by reducing the burden for farmers in a great way. Using IoT (Internet of Things), modern wireless devices can be constructed at an affordable cost to farmers across the country. Therefore, farmers could gain high productivity as the tasks are getting easier as well as being completed within a short period. This paper centers around the job of the Internet of Things in agribusiness that prompts brilliant cultivating. The modern technology named IoT not only shows the impact in the agricultural field but also provides several functionalities in other fields. The point of this undertaking is to propose IOT based Smart and Automated Agricultural Management System that records the data of moisture, temperature, humidity, heat index, and water level. In Smart and Automated Agricultural Management System, soil moisture sensor, DHT11 sensor, water-level sensor, and Arduino technology are utilized to simplify tasks by controlling the parameters of crop moisture content, environmental temperatures at appropriate times through the mobile application called Blynk with secured working.

India is mostly a farming nation. For most Indian households, agriculture is the most important line of work. It is essential to the growth of an agricultural nation. In India, agriculture accounts for 10% of total exports and roughly 16% of GDP. The primary resource for agriculture is water. Water can be supplied by irrigation, although there can sometimes be significant water waste. Consequently, in order to conserve time and water. Agriculture uses the Internet of Things (IoT) technologies a lot these days. As a result, this article discusses a project that is built on the Internet of Things (IoT) and focuses on the agricultural sector with the aim of reducing water usage in the sector. As a result, this essay discusses a project that leverages the Internet of Things (IoT), where all information can be accessed and managed at the touch of a finger, to reduce water consumption in the agricultural sector. We have an idea for a project called an Automated Plant Watering and Fertilizing with Soil Quality Testing. The proposed method makes use of a variety of sensors that sense the different aspects of the soil, such as temperature, humidity, and soil moisture sensors, automatically irrigate the land by turning the motor on and off depending on the soil moisture value. Key Words: Sensors,PH Sensor,Arduino Board,Temp Humidity Sensor DHT-11,Soil Moisture Sensor,Water Motor, Internet of Things (IOT), Solenoid Valve

The development of Internet of Things (IoT) technology has had a major impact on various aspects of life, including agriculture and plant care. This research aims to design a solution that can overcome the challenges of irrigating ornamental plants by utilizing soil moisture sensors and IoT technology. The approach used in this study is Hardware Programming. This approach involves leveraging hardware and programming to design and implement an IoT-based automatic watering system for ornamental plants. In its implementation, the NodeMCU ESP8266 acts as the control center, while the soil moisture sensor is used to measure soil moisture levels, the DHT11 sensor is used to measure ambient temperature, and the ultrasonic sensor is used to measure the volume of water in the container. The data obtained from these sensors is integrated with the Blynk application. The test results show that the system is able to provide an accurate and fast response regarding soil moisture conditions, as well as making it easier for users to monitor watering through mobile devices. This research contributes to overcoming plant care challenges by utilizing IoT technology and integration with the Blynk platform. It is hoped that this solution will provide benefits, especially for Tangerang Express Park rangers, so that they can monitor plant conditions in real-time.

This paper describes the development of a monitoring and controlling system for a garden using the Internet of Things (IoT). The system is designed to assist users in managing their plants and gardens remotely and effectively. Soil moisture levels are difficult to assess and manage, and achieving their target levels can be challenging. Therefore, an automatic water pump system is the optimal solution for this situation. The soil moisture sensor measures the moisture content in the soil, and the system automatically turns on the water pump when the moisture level is insufficient for healthy plant growth. A Light Emitting Diode (LED) is used to notify the user when the water pump is operating. A NodeMCU is used as the microcontroller for this project, which has a built-in Wi-Fi module, making it easier to interface with the Blynk software on a smartphone. The input is a soil moisture sensor, and the outputs are a water pump and an LED. The system successfully demonstrated real-time monitoring and automated control of soil moisture, ensuring optimal plant health. The integration of NodeMCU with Blynk enabled seamless remote access and notifications, enhancing user convenience. Experimental results confirmed the system's reliability in maintaining soil moisture levels within the desired range, reducing manual intervention, and improving water efficiency. This IoTbased approach provides a practical and scalable solution for smart gardening applications.

Objectives: Soil moisture information plays an important role in environmental monitoring, agricultural production and hydrological studies. Particularly, agricultural yield depends on several growing parameters like temperature, humidity, soil moisture and pH of the soil, etc. In this paper, we have designed and developed a system for measuring and monitoring soil moisture by interfacing low-cost soil moisture sensor with CC3200 LaunchPad and using Internet of Things (IoT), Cloud computing and Mobile computing technologies. Methods/Statistical Analysis: Two types of soils, namely red and black were collected from the field and experiments were carried out at room temperature. Moisture levels were measured using the commercially available soil moisture sensor: FC-28. Such values downloaded from the Cloud (earlier these values are uploaded into AT&T’s M2X Cloud technology and mobile application using CC3200 LaunchPad) are compared with the gravimetric dry basic technique. The results are in agreement with a deviation of 2%. Findings: Data corresponding to the moisture contents of red and black soils were uploaded to the AT&Ts’ M2X Cloud and accessed on-line and monitored the humidity levels on the screens of the mobile/laptop. In parallel the data acquired is also stored in the form of excel sheet for further processing. Conclusion: In this paper, we have designed and developed a Cloud computing Android system that gives on-line information about soil moisture. The results obtained for two types of soils are uploaded to the Cloud and accessed through the mobile/laptop from a remote area are presented.

Introduction:: The most crucial ingredient in agriculture is water. The amount of water that plants require must be provided to them. However, growers alternate between giving their plants more water than they truly need and giving them less and partly because they become overwatered due to meteorological circumstances like unexpected rainfall. Methods:: We employ an IoT-based intelligent irrigation system to get around this problem. It includes a centrifugal pump, a motor driver board, and a soil moisture sensor with YL69 probes. When the soil moisture level drops, the pump automatically delivers water to the plants with minimal human involvement. The electrical conductivity theory is how the sensor for soil moisture functions. A DHT11 sensor and a barometer, which provide information on the local temperature, humidity, and atmospheric pressure, are both parts of the weather monitoring system with the help of this, farmers can forecast the local weather and plan their irrigation accordingly. Results:: In this patent study, the thing speak API enables us to continually monitor information from a computer or mobile device, and the ESP8266 module links the complete system to the internet. Through this approach, water waste is reduced, and irrigation efficiency is increased while crop health and quality are preserved. Conclusion:: Overall, this research demonstrated how the Internet of Things-based intelligent irrigation systems may enhance agricultural water management. By combining soil moisture monitoring, weather monitoring, and autonomous management, we may develop irrigation techniques that are more precise, effective and patent leading to higher crop yields and sustainable agricultural practices.

The internet of things (IOT) has various use in Agriculture filed. Main moto is making IOT based Plant monitoring system is monitor plant growth system and control plant monitoring growth. In this system using DHT11 sensor, Touch sensor, soil moisture to monitor and collecting data. collect the data through the real time basic and send it through the cloud there is alert system if there anyone touches the plant then you have given an alert through an Alert Notification, On your mobile phone. there is one sensor dh11 to you know the real time temperature in what temperature is our environment if there is less soil moisture in soil, you again receive an alert message to Turn on the motor through your phone. This all about our project. KEYWORDS: Plant monitoring, Soil monitor, Alert system, Automation monitoring Plant,

Plant health monitoring is crucial in ensuring a constant food supply to satisfy the growing demand for food. Hence, it is essential to monitor plant health to maximize the yield and minimize the risk of various diseases. Soil moisture and temperature are of critical importance in plant growth, and predicting them enables farmers to take preventive actions, thereby mitigating the issues affecting plant health. This work presents a plant health monitoring approach by forecasting soil moisture and heat levels by collecting data in an Internet of Things (IoT) environment. Here, for transmitting the soil data acquired by the IoT nodes, a cluster head (CH) selection and routing technique using Gannet Namib beetle optimization (GNBO) is used. The data is routed to a prediction module, wherein soil moisture and heat levels are predicted by Convolutional long short term memory (Conv-LSTM). Furthermore, the hyperparameters of the Conv-LSTM are optimized by the GNBO algorithm. The efficiency of the GNBO-Conv-LSTM is examined based on link life time (LLT), energy, delay, distance, negative predictive value (NPV), positive predictive value (PPV), and true negative rate (TNR) and is observed to have achieved values of 0.675, 0.478 J, 0.092 ms, 50.200 m, 0.885, 0.882, and 0.875, correspondingly.

Drought is defined as a protracted lack of precipitation that lasts at least a season, resulting in a water deficit that affects plants, animals, and humans. It is a widespread and repeating feature of climate change in practically all temperate zones, ranging from excessively wet to burned. In Somalia, the government and farmers lack the technological skills to identify and monitor recurrent environmental issues. Our research created a technique for detecting droughts early on to reduce their impact. Using internet of things (IoT) devices, we created a system that measures temperature, humidity, and soil moisture. We then examined the data and used a line chart to show it in a web application (PHP and MySQL). The device reads these environmental parameters using an Arduino Uno, a DHT11 sensor, and a soil moisture sensor. The system deployed provides a real-time, cost-effective method for monitoring and controlling drought in modern agriculture.

The integration of the Internet of Things (IoT) with intelligent automation systems has opened new opportunities in precision agriculture, particularly for small-scale and indoor farming. This study presents the design and implementation of a smart terrarium system based on the Internet of Things and fuzzy logic to autonomously regulate environmental conditions, such as temperature, humidity, soil moisture, and light intensity. The prototype employs an ESP32 microcontroller integrated with DHT11, soil moisture, and LDR sensors, which continuously monitor the microclimate and control actuators, including a cooling fan, water pump, and grow lamp. Unlike traditional threshold - based control, the fuzzy inference system enhances adaptability by processing uncertain and nonlinear sensor data, thereby improving the decision-making accuracy under dynamic environmental conditions. The system was connected to the Blynk IoT platform, which enabled real-time monitoring, remote control, and manual override functions. The experimental results demonstrate reliable system performance: the fan activates under hot conditions, the pump operates under dry soil states, and the lamp responds to low light intensity, effectively maintaining an optimal microclimate. These findings highlight the advantages of combining the Internet of Things and fuzzy logic for adaptive environmental management, reducing manual intervention, improving resource efficiency, and ensuring plant growth stability in compact urban settings. Furthermore, this study contributes to sustainable agriculture by offering a scalable model that can be extended to larger urban farming applications. Future research should explore predictive analytics, machine learning integration, and enhanced user interfaces to further strengthen system resilience, scalability, and usability.

The design of a Soil moisture monitoring system with the Smart Farming Concept for IoT-based Chili Cultivation is a system design tool used to monitor Soil moisture in cayenne pepper cultivation. The monitoring system can determine Soil moisture conditions by monitoring Soil moisture information using IoT-based Microcontroller technology so that farmers can monitor the growth of cayenne pepper plants without the need to come to the Greenhouse location to monitor. The design of this monitoring systemuses a Soil moisture sensor. Where the Soil moisture sensor works is to monitor in real-time the state of Soil moisture in a Greenhouse. The classification of Soil moisture on soil quality so that the growth of cayenne pepper plants does not experience problems for dry soil and 61% to 100% for wet soil. The optimal Soil moisture content for cayenne pepper plant growth is in the range of 60% to 70% moist. The program flow to create a Soil moisture monitoring system for IoT-based chili cultivation goes through 3 main stages, namely the initialization, setup, and loop stages so that it can produce a display on the Soil moisture monitoring system application in real time. The results of the design of a Soil moisture monitoring tool based on trials show the optimal Soil moisture value at an average humidity of 63.5% and automatic watering will be carried out by the system when the Soil moisture level decreases from 60% so that it can be concluded that the IoT- based Soil moisture monitoring system can work well.

Moisture content is a critical factor that determines the quality of tobacco. Inappropriate moisture levels, whether too high or too low, can degrade quality and trigger damage during storage. Previous studies have mostly focused on soil moisture monitoring or other agricultural products, while research on integrated monitoring and automatic control systems for tobacco moisture content in small-scale storage is still limited. This study aims to design an Internet of Things (IoT)-based system for monitoring and controlling tobacco moisture content using a Wemos D1 microcontroller, soil moisture sensor, Firebase, and an Android application developed with MIT App Inventor. The system monitors moisture levels in real time, sends automatic notifications to a smartphone, and controls a storage roof mechanism that opens when the moisture exceeds 14% and closes when it falls below 10%, in accordance with the Indonesian National Standard (SNI). The system was tested on a small scale under several scenarios, including measurements of dry and wet tobacco, notification delay testing, and internet connection range testing. Experimental results show that the system can detect tobacco moisture content with satisfactory accuracy, with an average notification delay of about 2.8–3 seconds. The roof control mechanism driven by a servo motor successfully operated in 100% of trials. The system also worked effectively within a Wi-Fi connection range of up to 20 meters without obstacles and 15 meters with obstacles. In conclusion, this study demonstrates that an IoT-based solution using Wemos D1 provides a practical approach to maintaining tobacco moisture content within the required quality standards for small-scale storage. Future work may include employing more precise capacitive sensors, integrating historical data storage, and applying predictive models to enhance the reliability of automated tobacco storage systems.

Automation of soil moisture sensor-based basin irrigation system

Soil moisture is a crucial factor in agriculture that affects plant growth and crop productivity. In modern agricultural systems, accurate soil moisture monitoring is essential for optimizing water usage and enhancing the efficiency of automatic irrigation systems. This study aims to develop an Internet of Things (IoT)-based soil moisture monitoring system and evaluate the performance of three types of soil moisture sensors: Soil Moisture FC-28, Capacitive Soil Moisture Sensor, and Soil Moisture Hygrometer Module Sensor. The evaluation compares the accuracy and effectiveness of each sensor in measuring soil moisture. The research methodology involves measuring soil moisture in ten different soil samples using the three sensors simultaneously. The system is based on the ESP32 microcontroller, where data from the sensors are processed and displayed on an LCD Liquid Crystal I2C 20x4. Data analysis is conducted using the one-way ANOVA statistical method to determine whether there are significant differences among the measurement results of the three sensors.The results indicate that each sensor exhibits different measurement characteristics based on its working principle. The Soil Moisture FC-28 sensor, which operates on resistance, shows high sensitivity to changes in soil moisture but is susceptible to corrosion. The Capacitive Soil Moisture Sensor is more durable as it does not have direct contact with the soil, yet it requires more precise calibration. Meanwhile, the Soil Moisture Hygrometer Module Sensor provides more stable results under various environmental conditions. The one-way ANOVA analysis reveals no significant differences in the measurement results among the three sensors.

Organic culture has been widely promoted to famers as the best solution for many kinds of fruits and vegetables. However, the serious issue of organic culture is to optimal control soil moisture. This paper presents a soil moisture sensor based on internet of things (IoT) technology. The prototype IoT based soil moisture sensor has been implemented including with four components: sensing unit, connectivity, data processing and data analysis. The results show that the proposed soil moisture sensor not only shows the real-time soil moisture data but also analyze the soil moisture regulation.