Smart Farming (Ai-Generated) as an Approach to Better Control Pest and Disease Detection in Agriculture: POV Agricultural Institutions (2025)

Smart farming: An opportunity for efficient monitoring and detection of pests and diseases

Journal of Entomology and Zoology Studies, 2020

Smart farming is a key component of the modern agricultural revolutions. The concept of Smart agriculture was first emerged in the United States in early 1980s. Smart farming means application of precise and correct amount of inputs like water, fertilizer, pesticides etc. at the correct time to the crop for increasing its productivity and maximizing its yields. Smart farming comprises of geospatial technology and Internet of Things (IoT). Intregation of Geographical Information System (GIS) and Remote Sensing provide a solution where mapping for the disease incidences can be carried out. Once mapped, the experts can actually understand the causes which led to the crop infestations. Early warnings and forecasting based methods provide appropriate time for managing pest damage and can thus minimize the crop loss, optimize pest control and reduce the cost of cultivation [8]. In the concept of Internet of Things (IoT), every object is connected with each other through a unique identifier, so that, it can transfer data over the network to the human interaction [21]. Therefore, farmers have to be trained adequately so that they can monitor the dynamics of pests and diseases and take right decision at the right moment.

Importance of Smart Agriculture and Use of Artificial Intelligence in Shaping the Future of Agriculture

Journal of scientific research and reports, 2024

India, the second-most populated country globally with 1.4 billion people, faces significant challenges in its agriculture sector, including the need to feed a growing global population, mitigate climate change impacts, and ensure sustainable resource management. To address these

Artificial Intelligence In Agriculture: Crop Disease Detection And Monitoring Plants

IRJET, 2022

Artificial intelligence is having a significant influence across all industries. By limiting environmental deterioration, AI was able to solve a variety of issues while also protecting a valuable resource. In terms of agricultural output, India ranks second. Each crop is susceptible to certain diseases, which have an impact on yield quantity and quality. Crop diseases account for roughly 42% of crop failure for most of the major food crops. Crop diseases tend to wipe out an entire crop's productivity. Early illness detection will allow for more efficient monitoring and good crop product. This article offers a thorough review of an AI-based strategy for detecting and monitoring pest-infested crops and leaves. We share our research on crop disease detection and crop health using image processing, sensors, and other techniques in this publication. When it comes to assessing crops, the suggested method saves time and yields more precise results. In addition, we mentioned the destiny of AI-Powered agriculture and the realistic and technical demanding situations ahead. This survey will provide a clean concept approximately the present AI-Powered agriculture gadget and could assist researchers to broaden a brand-new ecosystem.

An Organized Review of Current AI Trends for Smart Farming to Boost Crop Yield and Its Advantages

Global Journal of Research in Agriculture & Life Sciences, 2022

At the moment, technology is being used extensively for development, one of which is the use of artificial intelligence (AI) to smart farming. Special powers can be programmed into artificial intelligence (AI) systems as needed. Artificial intelligence (AI), working with agricultural systems, helps to raise the standard of agriculture. The use of this technology in fundamental industries like agriculture is nothing new. Utilizing the most recent paper trends will help enhance agricultural yields in a variety of places. This is essential since there is a rising need for food sources and less land is accessible for agriculture. So, utilizing the features from the most recent year, this systematic review tries to gather the most recent trends in AI studies for Smart Farming publications.

Role of Artificial Intelligence in Crop Protection

Research Biotica, 2023

Agriculture is the backbone of Indian economy and India stands second in the world in agriculture production. The progress of Indian economy is directly proportional to the growth of industry in agriculture sector. After green revolution, there is an estimation of farm production loss of US$ 36 billion in India (Dhaliwal et al., 2015). The agricultural production is less because of insect pests, crop diseases and weeds occurring in important agricultural crops (Kavi Kumar and Parikh, 1998). Hence, there is a need of transition in farming system to adopt advanced and innovative technologies for more and sustainable production. Traditional farming methods are becoming outdated, need for advanced innovative technologies to increase the crop production. In recent years artificial intelligence (AI) gained popularity in agriculture and provides solutions in several areas like Information and Communication Technology (ICT), pest and disease forewarning models, mobile applications in integrated pest management (IPM), AI driven crop-advisory system, insect detection, pest and disease identification, Article History

"Artificial Intelligence and Indian Agriculture: Role, Applications and Challenges"

Indian Council of Social Science Research, 2021

Artificial Intelligence (AI) is very essential for agricultural sector that too for a country like India wherein 58% of Indian population directly and indirectly depending on agriculture and related occupation. During this pandemic COVID situation AI plays a vital role where social distancing and hygiene are most practiced. At the same time for India to become a developed nation from developing stage AI is very crucial. In the era of technological advancement and Smartphone usage India Ranks 2 nd in the world with respect to Internet usage. Hence, it is very much needed to upgrade and shift our traditional agriculture techniques to AI enabled agricultural farming. In this study the main areas where AI can be introduced are discussed in detail by taking several live examples at the same time while implementing such technological advancement the kind of problems that may be encountered by farmers are also addressed briefly. In addition, the government of India initiative as part of digital India campaign with respect to AI is also elaborated with detail.

ROLE OF ARTIFICIAL INTELLIGENCE IN FARMING-A CASE STUDY

IAEME PUBLICATION, 2024

Agriculture plays a major role in the economic sector for our country. The world’s population also increases day by day, and so the demand for food increasing rapidly. The general methods that are used in the farming are not sufficient to meet the needs of the increased population. Hence, some of the new automation methods are using to meet these requirements and to provide better job opportunities to more number of people in the agriculture sector. At present, Artificial Intelligence has become the most prominent technologies in agriculture sector. It is playing a very crucial role, and it is transforming the agriculture industry future. In fact, AI is trying to save the agriculture sector from different issues such as climate change, population growth, employment issues in this field, and support food safety. Artificial Intelligence helps to enhance crop production and real-time monitoring of filed, harvesting the crop, processing the crop and marketing also. Different high end technology based computer systems are introduced to find various parameters such as weeds detection, yield prediction, crop quality estimation, and many more other parameters

Qeios, Jaunary 26 , 2024

Artificial intelligence (AI)-based pest management advisory, based on integrated pest management (IPM), provided to cotton farmers on smartphones, resulted in a reduction in pest attacks & up to 22% higher income in the 1 year 2020-21 in Ranebennur, Karnataka, and Wardha, Maharashtra states. However, no significant benefit was seen in a multistate experiment in 2021-22 due to unusually high rainfall, resulting in lower pest attacks. The artificial intelligence was used in pest detection & counting insect numbers in the pheromone trap to decide if threshold numbers were reached for pesticide spraying decisions. This was 1-2 weeks in advance of mass pest emergence and could control it to reduce crop damage. It required manual trap checking by the farmers on a weekly basis, which many farmers disliked. Artificial intelligence coupled to remote sensing, GIS, and/or farm sensors can benefit the farmers by cutting costs, increasing yield, and enabling cleaner production. Lower environmental pollution and less risk to farmers and consumers are cobenefits of the AI-IPM package. However, mating disruption technology, a competitor, includes putting 4-6 pheromone traps per acre for the mass capture of moths. It is organic-compatible, and another competitor is the mechanical growing degree day (GDD)-based IPM advisory, such as that provided by the startup "Fasal." These are unintelligent, mechanical, but very effective algorithms. Thus, a cautious, logical, and gradual approach is needed in promoting AI in agriculture, also keeping in mind its impact on labour displacement.

Smart Agriculture: The Future of Agriculture using AI and IoT

Journal of Computer Science, 2021

Corresponding Author: Artika Farhana Department of Computer Science, Jizan University, Saudi Arabia Email: far1984hana@gmail.com Abstract: Agriculture sector contributing a significant share in World economy and in more than nine counties agronomy is the leading segment. Population is rising immensely therefore quality and quantity of food demand increases enormously. Agriculture segment is providing employment prospects to large population as well. Conventional farming styles used by farmers are not competent to fulfil the enlarged demand. To meet the growing demands, emerging innovative practices need to be introduced which can be observed as Agricultural Intelligence and can brought agriculture 4.0 revolution. Artificial Intelligence and Internet of Things like promising technologies convert traditional farming into smart agriculture by optimizing resources, reducing human labor, crop monitoring, weed handling, crop disease management, irrigation, harvesting and supply chain mana...

Prospect of Machine Learning in Smart Farming

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2021

Smart farming is an epicentre of the new upcoming agricultural methodologies. It is the amalgamation of new technology-oriented procedures wrapped with sustainable practices that enhances productivity by not harming mother earth through overuse of pesticides, fertilizers, and other natural resources. Technologies such as Machine learning, IoT, Sensor-based agriculture, etc. are gearing up the pace in making their presence in modern-day farming practice. Our farmers can improve the production capabilities, reduce the wastage of yield, and maximize their productivity by adapting to the technology-oriented farming. The usage of these technologies will have a positive edge. Agriculture combined with the advantages of sensor based data collections can be used to monitor soil health, water level of soil, crop quality, weed detection, disease detection, etc. This review paper indicates the usage of the machine learning techniques in the field of agriculture in order to optimize the yield.

Transforming Farmers and Farming by Artificial Intelligence in Agricultural Environment

Asian Journal of Microbiology Biotechnology and Environmental Sciences, 2022

The agricultural industry contributes significantly to the economy. The primary issue and a hot topic globally is the automation of agriculture. The population is growing rapidly, and this growth is also increasing the demand for food and jobs. Farmers have been employing traditional methods but were insufficient to meet these demands. New automated techniques were consequently introduced. These innovative techniques supplied the world's food needs while simultaneously giving billions of people access to jobs. Agriculture has undergone a revolution thanks to artificial intelligence. The agricultural output has been shielded by this technique from a number of circumstances, including population expansion, job issues, and food security concerns. Recently, the agriculture industry is witnessing the application of artificial intelligence (AI). To increase production, the industry must overcome a number of obstacles, including poor soil management, insect and disease infestation, the need for large amounts of data, low output, and a knowledge gap between farmers and technology. The major ideas behind AI in agriculture are its adaptability, excellence, accuracy, and economy. This essay provides an overview of the ways artificial intelligence has been applied to managing weeds, diseases, crops, and soil. The application's advantages and disadvantages are highlighted and also how to use expert systems to increase productivity.

Understanding the potential applications of Artificial Intelligence in Agriculture Sector

Artificial Intelligence (AI) has been extensively applied in farming recently. To cultivate healthier crops, manage pests, monitor soil and growing conditions, analyse data for farmers, and enhance other management activities of the food supply chain, the agriculture sector is turning to AI technology. It makes it challenging for farmers to choose the ideal time to plant seeds. AI helps farmers choose the optimum seed for a particular weather scenario. It also offers data on weather forecasts. AI-powered solutions will help farmers produce more with fewer resources, increase crop quality, and hasten product time to reach the market. AI aids in understanding soil qualities. AI helps farmers by suggesting the nutrients they should apply to increase the quality of the soil. AI can help farmers choose the optimal time to plant their seeds. Intelligent equipment can calculate the spacing between seeds and the maximum planting depth. An AI-powered system known as a health monitoring system provides farmers with information on the health of their crops and the nutrients that need to be given to enhance yield quality and quantity. This study identifies and analyses relevant articles on AI for Agriculture. Using AI, farmers can now access advanced data and analytics tools that will foster better farming, improve efficiencies, and reduce waste in biofuel and food production while minimising the negative environmental impacts. AI and Machine Learning (ML) have transformed various industries, and the AI wave has now reached the agriculture sector. Companies are developing several technologies to make monitoring farmers' crop and soil health easier. Hyperspectral imaging and 3D laser scanning are the leading AI-based technologies that can help ensure crop health. These AI-powered technologies collect precise data on the health of the crops in greater volume for analysis. This paper studied AI and its need in Agriculture. The process of AI in Agriculture and some Agriculture parameters monitored by AI are briefed. Finally, we identified and discussed the significant applications of AI in agriculture.

Artificial Intelligence in Smart Agriculture: Applications and Challenges

CURRENT APPLIED SCIENCE AND TECHNOLOGY

Artificial intelligence has been categorized as a subfield of computer science wherein machines perform smart learning tasks with the help of data and statical methods. Agriculture is one of the oldest social activities performed by humans. It provides many crucial things like raw materials, food, and employment. Due to the increasing population, it is the need of the hour that the agriculture sector should increase production of resources to match actual demand. Many agronomic factors such as weeds, pests, water condition and availability, and climate conditions impact overall yield. At present, methods used by farmers for management are traditional and insufficient to meet increased demand. To match future demand, new innovative agriculture methos need to be adopted. Artificial intelligence techniques in smart farm monitoring can enhance the quality and quantity of yield. This paper surveys different areas in agriculture where artificial intelligence is applicable. Artificial in...

A Systematic Review of Current Trends in Artificial Intelligence for Smart Farming to Enhance Crop Yield

Journal of Robotics and Control (JRC)

Current technology has been widely applied for development, one of which has an Artificial Intelligence (AI) applied to Smart Farming. AI can give special capabilities to be programmed as needed. In cooperation with agricultural systems, AI is part of improving the quality of agriculture. This technology is no stranger to being applied in basic fields such as agriculture. This smart technology is needed to increase crop yields for various regions by utilizing the current trends paper. This is necessary because less land is available for agriculture, and there is a greater need for food sources. Therefore, this systematic review aims to collect the current trends in AI studies for Smart Farming papers using the latest year features from 2018-2022. This paper is handy for researchers and industry in looking for the latest papers on research to enhance crop yields. The authors utilized Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) of 534 articles from IEEE...

Introduction of Smart Agriculture

Big Data in Bioeconomy, 2021

Smart agriculture is a rising area bringing the benefits of digitalization through big data, artificial intelligence and linked data into the agricultural domain. This chapter motivates the use and describes the rise of smart agriculture.

Information technology based smart farming model development in agriculture land

IAES International Journal of Artificial Intelligence (IJ-AI)

Smart farming in various worlds is not just about applying technology in terms of storing data on agricultural land. However, having a concept of measurable data based on available computational techniques trained and then generating knowledge. As an application, the agri drone sprayer can be used for the process of applying pesticides and liquid fertilizers on each side. In addition, drone surveillance is also useful in implementing smart farming such as mapping land so that farmers will know the condition of their agricultural land. However, the soil and weather sensor will also help the farmers to monitor the farmland as well. Devices with sensors can only obtain data in the form of air and soil humidity, temperature, soil pH, water content and forecasting the harvest period. So that the smart farming model can help farmers to get recommendations, in preventing the predicted damage to their land and crops. However, according to its geographical location, the application of smart ...

Smart Agriculture: Could IT Be the Future of Romanian Farmers?

Risk in Contemporary Economy, 2021

Domestication and cultivation of useful plants are correlated with the evolution and development of human civilization. The current evolution of agricultural technologies has allowed the development of new concepts of intelligent agriculture, based on ITC. In order to optimize crop production, pest control, soil and plant growth monitoring and better information collection for farmers, in the context of the world's growing population, smart agriculture will need to make more use of information technology. The future of agriculture in the coming years will be the result of the connection between satellites and intelligent technical means, both with monitoring and control of agricultural activity. The article presents the trends of smart agriculture and aspects related to the development of Romanian agriculture. The obtained results allow the development of more extensive analyzes, the presented study being part of the documentation related to the doctoral research.

IRJET- USE OF ARTIFICIAL INTELLIGENCE IN AGRICULTURE

IRJET, 2020

Since the initiation of human race, we have been rapidly consuming resources in order to survive on this planet later, also for wants and leisure. The human race is expanding rapidly , UN quoted that the earth's population will reach above 2 billion and as the population expands so will the basic and leisurely needs and wants will, but one of the most basic needs that we have is food , it is essential for the proper functioning of human body and mind and in Post green revolution we witnessed an increase in the output of the agriculture. But in order to sustain the ever increasing population we need another revolution. In this article we will discuss how we can implement IoT (internet of things) and AI (artificial intelligence) in modern agriculture in order to increase output and to decrease the input. SCOPE OF ARTIFICIAL INTELLIGENCE IN AGRICULTURE In a country like India where 58% of rural population is still dependent on agriculture in indirect or direct manner.Most of the farming done by farmers in the rural area is of an organised manner and very scattered agriculture techniques. The industry is in dire need of skilled and educated farmers. Adoption of artificial intelligence and machine learning both in terms of agricultural production in field farming techniques can be a game changing move in the sector. Some of the search techniques is cognitive computing which uses various predetermined data sets and special monitoring tools to monitor each specific batches of crops in order to analyse their growth and health to maximize efficiency and effectiveness. Farmers can also be given advice by experts of each specific fields of agriculture based on on the data that is being recorded by the system.Adopting such techniques would mean that more manual labour can be utilised in order to increase output. Now will talk about some of these techniques which can be implemented in the agricultural sector IMAGE PROCESSING With the help of drones and high resolution cameras in constant 24 hour surveillance of each and every single plant in batches ,we can collect the data and process it with the help of a machine learning algorithm trained it with predetermined data sets in order to determine the health and growth of individual types of plant as well as to group the relevant data together in order to organise the data and inform the certified person regarding the issues found. This technique can also help in harvesting where it can inform the farmer regarding where each batch of crops in terms of harvesting status which will result in decrease in wastage of resources by constantly monitoring and responding the data to the machine learning algorithm, which in turn will organise the data and inform the farmer regarding the status of the crops. Internet Of Things (IoT) With the help of arduino and different type of sensor we can gather huge volumes of data everyday both in organised and unorganised format. Historical data such as weather patterns rainfall research pattern pest infestation, high resolution data for soil testing and proximity sensors can help analyse

SMART FARMING PROJECT DOCUMENTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF BACHELOR OF TECHNOLOGY IN DEPARTMENT OF INFORMATION TECHNOLOGY MEGHNAD SAHA INSTITUTE OF TECHNOLOGY

The foregoing project entitled SMART FARMING is hereby approved as a creditable study of an engineering subject carried out and presented in a manner satisfactory to warrant its acceptance as prerequisite for the degree for which it has been submitted. It is to be understood that by this approval the undersigned do not necessarily endorse or approve any statement made, opinion expressed or conclusion drawn therein but approve the thesis only for the purpose for which it has been submitted.

An Examination of the Implementation of Artificial Intelligence in Agricultural Extension of Developing Nations: A Comprehensive Analysis

Developing nations primarily depend on rain-fed agriculture and traditional methods to manage and prevent crop pests and diseases. However, the impact of global warming has significantly reduced agricultural productivity in these regions, making them more susceptible to food insecurity. The lack of sufficient extension services and limited access to information provided by agricultural organizations at both local and national levels has resulted in the decreased productivity of arable lands in these countries. This research contends that utilizing digital tools can assist farmers in enhancing farm output in the face of the aforementioned issues. Artificial intelligence (AI) and machine learning (ML) are advanced technologies that can be used to create applications that offer farmers with precise and upto-date agricultural information, which is crucial for making informed decisions. This research aims to determine the role of artificial intelligence (AI) in agriculture to address the issues encountered by farmers in developing countries.