IoT Based Smart Agriculture Research Articles

An optimization driven deep belief network model for crop yield prediction in IoT based smart agriculture

An optimization driven deep belief network model for crop yield prediction in IoT based smart agriculture

IoT Based Smart Agriculture Using Machine Learning

Agriculture is one of the crucial sources of economic growth in the country. Agriculture plays a major role in increasing the overall economy of any country. Many countries are having tremendous growth in the production of crops as the demand for food grains and supply increases. India is one of the leading countries in producing a variety of different crops. However, most parts of India are still using the traditional methods for implementation and cultivation of crops, due to which farmers are facing a loss in their production due to inadequate supply of fertilizers and uncertain climatic conditions. To overcome this, there is a need to develop a system that will look for these soil, temperature, and climatic conditions. IoT-based Smart Agriculture using Machine Learning talks about the use of IoT and Machine Learning techniques that will not only look for sensor data but also recommend the farmers the suitable fertilizers and crops to be grown. Smart sensors will be used to get the values related to soil moisture, temperature, humidity, and pH values. These sensors will check for suitable soil conditions, and how wet or dry the soil is, and will also look for temperature values. The real-time data will be fetched and displayed on the live monitoring webpage and Android applications. We can get timely information about the soil moisture value and suitable temperature and humidity value. With the help of Data Analysis techniques, we can figure out which data to take for further exploration. Historical datasets that are publicly available can be used for training and building Machine Learning models. Farmers can access information about their field data, and machine learning algorithms will help the farmers in making informed decisions about what crops to grow in the specific environment. Keywords— Internet of Things, Sensors, Soil moisture, Temperature, Humidity, Microcontroller, Smart Agriculture, Recommendation Model, Crop Prediction, Fertilizers Prediction, Machine Learning Model.

Enhancing water management in smart agriculture: A cloud and IoT-Based smart irrigation system

It is widely acknowledged that traditional agricultural practices must effectively address the increasing global demand for food while facing water scarcity and climate change challenges. The imperative for environmentally sustainable agricultural approaches has never been more urgent. In response, IoT-based Smart Agriculture has emerged as a promising solution. Smart Agriculture can significantly bolster agricultural development by integrating renewable energy sources, particularly in arid regions with abundant sunlight. Real-time control systems utilizing big data acquisition and processing are pivotal in this advancement. This study introduces a cloud-based smart irrigation system to connect numerous small-scale smart farms and centralize pertinent data. The system optimizes irrigation water usage through comprehensive big data collection, storage, and analysis. Leveraging the insights from this data can facilitate informed decision-making regarding water management, thereby fostering conservation efforts, particularly in arid regions. Additionally, this research explores weather prediction services to enhance irrigation control, particularly during intermittent rainy periods, within a real-world testbed powered by solar energy. The testbed incorporates a sophisticated big data management system. It showcases a Smart Farm prototype leveraging the Internet of Things, embedded systems, low-cost Wireless Sensor Networks, NI CompactRIO controller, and Cloud Computing. Encouragingly, the results demonstrate tangible improvements in water conservation. Furthermore, the deployment methodology outlined in this study provides a clear roadmap that can be readily adapted for similar research endeavors.© 2023 Elsevier Inc. All rights reserved.

An Enhanced Multi-Kernel Based Extreme Learning Machine Model for Crop Yield Prediction in IoT-Based Smart Agriculture

An Enhanced Multi-Kernel Based Extreme Learning Machine Model for Crop Yield Prediction in IoT-Based Smart Agriculture

An enhanced multi-kernel-based extreme learning machine model for crop yield prediction in IoT-based smart agriculture

An enhanced multi-kernel-based extreme learning machine model for crop yield prediction in IoT-based smart agriculture

A Novel Rel-DASA Model for Reliable Data Analysis in IoT Based Smart Agriculture

Agriculture today depends largely on these technologies to supply food for human consumption because to their widespread usage. The Internet of Things bridges the gap by providing farmers with critical tools to predict crop growth, availability of moisture in the soil, soil status, and so on. We describe a comprehensive agricultural monitoring system for accurate crop growth management. This proposed research investigates how supplying farmers with real-time data such as weather forecasts through sensor integration might enhance decision-making. Internet of Things, Agricultural Sensors, Wi-Fi Module, Android App, and Raspberry Pi are all integrated.

IOT based Smart Agriculture Monitoring System Project

Abstract: The need for efficient and effective agriculture has led to the development of IoT based smart agriculture monitoring systems. This article covers Arduino, GSM modem, WiFi modem, temperature sensor, humidity sensor, water sensor, mini fan, water pump fluid, crystal oscillator, resistors, capacitors, transistors, cables and connectors, diodes, PCBs, LEDs, transformers/a dapters, buttons, switches and IC sockets. The system allows realtime monitoring and control of the environment necessary for cultivation and optimization. Integrated with advanced technology , the solution enables farmers to make data-driven decisions and improve farming.

IOT Based Smart Agriculture for Precession Irrigation - A Model

Abstract: The rapid development of Internet of Things (IoT) technology across all industries, from the automotive to home automation, had an impact on the agriculture sector as well, commonly known as "Smart Agriculture," which moved the entire sector from statistical to quantitative methods. These innovative ideas modify agriculture's current practises, open up new prospects, and help this industry overcome a number of obstacles. This study shows a system that makes use of the possibilities of these IoT and wireless sensing devices as well as the difficulties encountered when fusing these technologies for mutual benefit. This essay demonstrates how to use a smart agricultural application that allows users to monitor and modify soil moisture, temperature, and humidity.The capacity to remotely direct water flow anywhere the user pleases without being present in person. This is accomplished by using a soil moisture sensor that can measure soil moisture, a DHT 11 for measuring temperature and humidity, an Arduino to link the entire system together, and the IOT cloud as the system's database. Our only goal is to create an automated solution for remote gardening that is user-friendly

Smart Agriculture System Using IoT Based

Abstract: Agriculture is becoming an important growing sector throughout the world due to increasing population. Major challenge in agriculture sector is to improve farm productivity and quality of farming without continuous manual monitoring to meet the rapidly growing demand for food. Apart from increasing population, the climate change is also a big concern in agricultural sector. The purpose of this research work is to purpose a smart farming method based on internet of things (IOT) to deal with the adverse situations. The smart farming can be adopted which offer high precision crop control, collection of useful data and automated farming technique. This works presents a smart agriculture system which monitors soil humidity and temperature. After processing the sensed data, it takes necessary action based on these values without human intervention. In IOT-based smart agriculture, a system is built for monitoring the crop field with the help of sensors (light, humidity, temperature, soil moisture, etc) and automating the irrigation system. IOT (internet of things) in an agricultural context refers to the use of sensors, cameras, and temperature and moisture of the soil measured and these sensed values are stored in things speak cloud for future data analysis.

IoT-based smart agriculture: an exhaustive study

IoT-based smart agriculture: an exhaustive study

Deep malware detection framework for IoT-based smart agriculture

The advancement in smart agriculture through the Internet of Things (IoT) devices has increased the risk of cyber-attacks. Most of the existing malware detection techniques are unable to detect new variants of malware and suffer from poor accuracy. To overcome the challenges of new malware, this research work proposes a novel three-phase Deep Malware Detection (DMD) framework based on the fusion of Discrete Wavelet Transform (DWT) and Generative Adversarial Network (GAN) named as DMD-DWT-GAN, for IoT-based Smart Agriculture (IoT-SA). This work applied DWT for multiresolution analysis by decomposing the image into Approximation coefficients (Ac) and Detail coefficients (Dc). Finally, a lightweight Convolutional Neural Network (CNN) is employed for in-depth analysis of the malware family. The performance of the proposed framework is evaluated using two benchmark datasets such as IoT malware and Malimg. The proposed framework has achieved 99.99% accuracy on both datasets and is better than the state-of-art models.

Wireless communication protocols in smart agriculture: A review on applications, challenges and future trends

IoT based smart agriculture systems are important for efficient usage of lands, water, and energy resources. Wireless communication protocols constitute a critical part of smart agriculture systems because the fields, in general, cover a large area requiring system components to be placed at distant locations. There are various communication protocols with different features that can be utilized in smart agriculture applications. When designing a smart agriculture system, it is required to carefully consider the features of possible protocols to make a suitable and optimal selection. Therefore, this review paper aims to underline the specifications of the wireless communication protocols that are widely used in smart agriculture applications. Furthermore, application-specific requirements, which may be useful during the design stage of the smart agriculture systems, are highlighted. To accomplish these aims, this paper compares the technical properties and investigates the practical applications of five different wireless communication protocols that are commonly used in IoT applications: ZigBee, Wi-Fi, Sigfox, NB-IoT, and LoRaWAN. In particular, the inconsistencies in the technical properties of these protocols reported in different resources have been highlighted and the reason for this situation has been discussed. Considering the features offered by the protocols and the requirements of smart agriculture applications, the appropriateness of a particular protocol to a particular smart agriculture application is examined. In addition, issues about cost, communication quality, and hardware of the five protocols have been mentioned. The trending technologies with high potential for the future applications of smart agriculture have been introduced. In this context, the relation of the technologies like aerial systems, cellular communication, and big data analytics with wireless have been specified. Finally, the leading protocol and the smart agriculture application area have been highlighted through observing the year-based distribution of the recent publications. It has been shown that usage of LoRaWAN protocol has become more widespread in recent years.

IoT Based Smart Agriculture and Animal Detection System

Abstract: Agriculture, the science and art of cultivating plants, plays a pivotal role in the evolution of a primary agricultural economy. More than 50% of the population in India depends upon farming. Hurdles concerning agriculture have significantly retarded the growth in this sector. The most significant obstacle incurred by the farmers is inefficient crop management and crop raiding by external sources, especially the human-wildlife conflict. A cumulative approach including the application of “Internet of Things” and traditional farming techniques, along with methods to barricade crop destruction has been elaborately highlighted by way of integrated systems. Hence this proposed module targets at making agriculture smart by proposing a device detects the presence of any living being by using either PIR Sensor or Ultrasonic Sensor, especially animals around the land to be cultivated, along with smart irrigation control and real-time data analysis which is also inclusive of smart warehouse management parameters like- temperature, humidity and pressure measured by using (DHT22 Sensor and BMP180 Sensor). This data may either be visualized by using the Blynk Software or received in the form of messages through the GSM Module. To combat the ruckus caused by animals, detection of their presence along with a laser security system has been provided in the proposed system. Efforts have been made to help the farmer in rectifying multiple issues at once. Keywords: PIR Sensor, DHT22 Sensor, BMP180 Sensor, Blynk App, GSM Module

IoT Based Smart Agriculture Monitoring, Weather Control and Irrigation System

Agriculture plays vital role in the development of agricultural country like India. In India about 70% of population depends upon farming. Agriculture is done manually from ages. As the world is trending into new technologies and implementations it is a necessary goal to trend up with Agriculture also. due to migration of people from rural to urban there are difficulties in agriculture. In day today life, technology is updating and it is also necessary to trend up agriculture too. IoT can play a key role in smart agriculture. Hence the paper aims at making agriculture smart using automation and IoT technologies. IOT based Agriculture monitoring system makes use of wireless sensor networks that collects data from different sensors deployed at various nodes and sends it through the wireless protocols. It includes the humidity sensor, temperature sensor, soil moisture sensor and water level sensor. The features of this project include an android application which shows the live information about the temperature, humidity, soil moisture, water level. Secondly it includes smart irrigation with smart control and intelligent decision making based on accurate real time field data. Thirdly an automatic weather control system which controls the humidity and temperature of the field (e.g. green house).

IoT Based Smart Agriculture and Plant Disease Prediction

Agriculture is a very prominent sector in our country and has been one of the highest contributors to the GDP. During the 1960s, an all-time high was reached with approximately 50% contribution to the GDP of the country, as more than half of the population was rural and focused primarily on agriculture as means of their livelihood. But from the latest records of 2019, the contribution by this sector has decreased to 15.96 percent. IoT plays a significant tole in remote sensing with machine learning in monitoring crops and surveying, which in turn aids agriculturists in ways for efficient field management. The proposed work integrates the role of Internet of Things and Deep learning deployment in farm management and disease identification of leaves. With the use of Internet of Things through remote sensing this work monitors the agriculture field parameters in remote cloud environment. With modified Resnet model deployed on the cloud for the purpose building a smart disease prediction. This system achieves 99.35% accuracy for the dataset. Overall this approach will provide an opportunity for agriculturists to test the plant disease with a smart phone connected to Internet and take appropriate actions.

Smart agriculture using IoT

IOT based smart agriculture is a breakthrough in the agriculture sector that gives better solution for water conservation, reduces labour cost, electricity conservation and helps the farmer to keep a record of his yields throughout the year on a wireless mode. This research paper deals with an IoT based application for sustained farm practice by sensing the soil moisture from the soil using the soil moisture sensor module, communicating over internet by the ESP-8266 Wi-Fi module that controls the switching of the submersible motor pump (motor driver-289D) via Arduino Uno R3. The communication request is created by the computer on the given web page of THINKSPEAK APP from the server which further displays the real time sensor values and the pump status in a graphical form. The prototype was designed and tested to sense the real time soil moisture values, send it to the Arduino via the serial communication over the ESP-8266 Wi-Fi module that further plots this value on the created THINGSPEAK channel and is made user-friendly via using virtuino app in the mobile, which enables the remote monitoring the soil moisture values and thus assisting the control of the water pump.

A Comprehensive Review on Iot Based Smart Agriculture Monitoring System: Wireless Communication Technologies, Iot Platforms, Wireless Sensor Networks, Sensor Types and Security Challenges

A Comprehensive Review on Iot Based Smart Agriculture Monitoring System: Wireless Communication Technologies, Iot Platforms, Wireless Sensor Networks, Sensor Types and Security Challenges

Development of IoT-based smart agriculture monitoring system for red radish plants production

Development of IoT-based smart agriculture monitoring system for red radish plants production

A study on IoT Based Smart Agriculture System

In this fast growing world of automation there is an increase in IOT based systems installed for time and labour management. Agriculture industry is one of the industries which require correct time management. AI based smart agriculture is one of the solution to overcome this problem. In agriculture one has to keep an eye on their crops for water, pesticides & fertilizers. This paper focuses on a (automatic) smart agriculture system. The objectives of this smart agricultureb system is to efficiently manage water, pesticides and fertilizer can be used to increase the productivity of the crop and saves time. This system provides an automatic pathway for irrigation and crop management technique with the help of sensors and micro controller chips for machine guidance in accordance with moisture control and other parameters of soil required for a particular crop to manage water requirement. Agrotech gives a new vision of agriculture system. These modifications will provide a future outlook on the new trends in agriculture system.

IoT based Smart Agriculture using Thingspeak

IoT based Smart Agriculture using Thingspeak