Top Research Papers on Precision Agriculture

Precision farming refers to the latest trends in agriculture that use technology to improve quality, quantity, and productivity, thereby ensuring profitability, sustainability, betterment, and preservation of the environment. The paper discusses the development and needs for precision agriculture in India with its existing problems and opportunities. The challenges in the future cannot be resolved with ancient methods. In order to make agriculture efficient and sustainable, investment in new technologies accompanied by research and development is required. Agronomics is the highest contributor...

To meet the rising food demand of a world population predicted to reach 9 [...]

The world faces the challenge of providing adequate healthy food for a growing population while also addressing environmental conservation concerns. Traditional farming practices, including clearance of vegetative cover (Mark Gregory, 2017), have led to climate change and environmental degradation, particularly visible in developing countries where resources are often limited. This research paper explores how precision farming, supported by technologies such as remote sensing, data analytics, and artificial intelligence, can offer a solution to this dilemma. Precision farming techniques enable...

This study clarifies how precision agriculture powered by the Internet of Things may optimize agricultural productivity and sustainability and demonstrates how precision agriculture has the potential to completely transform contemporary agricultural methods by maximizing crop output, promoting sustainability, and reducing environmental impact.

Preliminary tests show that the IoT-based soil monitoring solution based on the LoRa/LoRaWAN and NB-IoT technologies is water resistant and can communicate up to 1.7km while buried 10cm underground.

The article studies the practice of using space monitoring tools in the agro-industrial complex. It is shown that the use of space images is an element of an integrated high-tech agricultural management system in precision farming. The article considers the possibilities of applying the Normalized difference vegetation index method in order to increase the productivity of agricultural land, improve the processes of managing the agricultural complex, determine the limiting factors of sustainable development and predict yields.

The paper assesses the data collected by sensors and processed in order to produce maps for agrotechnical operations and explains the main sensor types according to their design, the recorded range of electromagnetic spectrum, as well as the way of detection, recording, measuring, and representation of the detected energy.

Precision agriculture (PA) as a concept allows input optimization by farmers and food producers in order to improve productivity and enhance quality yields while minimizing costs and environmental impacts. Developed countries typically identify with precision agriculture due to very large sizes of farms and the possibility of mechanized systems of crop production. The method involves the data collection, analysis, and plotting on productivity, soil quality parameters, and environmental levels at different locations within the field to decide on the amounts of the applicable inputs (such as wat...

Precision agriculture makes use of RS to macro-control, of GPS to locate precisely ground position and of GIS to store ground information. It precisely establishes various operation, such as the best tillage, application of fertilizer, sowing, irrigation, spurting etc,turns traditional extensive production to intensive production according to space variable data. Precision agriculture not only may utilize fully resources, reduce investment, decrease pollution of the environment and get the most of social and economic efficiency, but also makes farm products, the same as industry, become contro...

While the Internet of Things enables machine learning and artificial intelligence by collecting real-time data from operations, the real breakthrough will come from machine learning algorithms that can predict outcomes, maintain standards, and work on the farm.

Some of the latest recent advances in precision agriculture, including the Internet of Things (IoT) and how to make use of big data are examined, including drones, sensors, and machine learning.

Farm and in situ observations together with existing databases provide the opportunity to both predict yields using “simpler” statistical methods or decision support systems that are already used as an extension, and also enable the potential use of artificial intelligence.

Assessment of precision agriculture applicability in the agriculture sector in Egypt and challenges affecting the diffusion of these technologies with proposals of overcoming these challenges are focused on.

The research demonstrates that affordable solutions based on the common differential GNSS infrastructure can be applied for accurate localisation under real field conditions and underscores the potential of GNSS-based automation and robotisation in transforming agriculture into a more efficient and sustainable industry.

This paper presents theAIoT framework, showcasing how AIoT could impact modern agriculture by implementing data-driven solutions based on low-cost devices and open source technologies, empowered by Edge Intelligence.

Natural resources, biotic variables, agro-inputs, and management all impact agricultural production. Uncontrolled use of resources and inputs frequently occurs by farmers, which results in environmental pollution, degradation of land, and financial loss to farmers. The term "precision farming" describes the integration of GIS and GPS tools to provide extensive detailed information on crop growth, crop health, crop yield, water absorption, nutrient levels, topography, and soil variability [1]. Precision agriculture makes use of technology such as sensors, GPS, GIS, Internet of Things, drones, e...

This keynote speech will show how edge computing systems can improve precision agriculture and show how it has been applied in several Spanish and European projects.

The following review article is going to address the most current facts regarding nutrients along with their usage in agricultural production for crop development.

A quadcopter-type drone is the most used drone in this sector, and seed planting is the least explored drone application area, according to reviewing more than 50 articles.

An automated irrigation system which monitors and maintains the desired soil moisture content via automatic watering through soil moisture sensors which enables the system to use appropriate quantity of water which avoids over/under irrigation.

The development of an automated system, incorporating computer vision, robotic manipulation, QR code identification, QR code identification, and cloud storage, aims to revolutionize the efficiency and precision of plant sorting processes.

This review synthesizes insights from a multitude of research papers, exploring the dynamic landscape of precision agriculture, and focuses on the integration of smart sensors, coupled with technologies such as the Internet of Things, big data analytics, and Artificial Intelligence.

Precision agriculture is a rapidly advancing field that combines advanced technologies and data analytics to improve crop productivity and resource management. This article reviews the advancements, technologies, and applications in precision agriculture. It explores the role of sensing technologies, such as remote sensing, ground-based sensors, and GPS/GIS applications, in data collection and analysis for informed decision-making. The article also examines the impact of variable rate technologies, including variable rate seeding, nutrient application, and irrigation, on optimizing input usage...

The ability to manage fields not as a single unit but by dividing them into separate areas distinguishes precision farming from traditional agriculture. Technologies and techniques used to improve the crop farming is the main domain we are working under precision agriculture.Optical sensors that use the reflectivity of light placed on growing plants to monitor and record the data about soil and crops in real time are available. Electrochemical sensors,are those that monitor plant, soil, and external factors that have a direct impact on plant growth.. A prototype of an intelligent Agriculture R...

The article presents the concept of an agricultural complex that combines elements of agrivoltaics and precision farming. The purpose of the development of this complex is the ability to implement the principle of multipurpose use of sown areas for basic agricultural crops production (wheat, corn, etc.). The design of this complex and the operation of individual elements are described. In terms of agrivoltaics, it is proposed to use rotating photovoltaic panels; for precision farming - the natural division of the structure of the complex into separate areas. The information is collected by sen...

This chapter proposes a platform for precision agriculture which allows collecting fundamental physical phenomena required for the precision agriculture, which will be carried out to calculate the water quantity needed for optimal irrigation.

Precision agriculture is a management system that aims to reduce inputs like seeds, water, and energy; protect the environment; and maximize profitability. Precision agriculture uses advanced technology like positioning technology, geographical information systems, satellite navigation, and remote sensing. There are different factors affect the adoption of precision agriculture like farm size, legal affairs, and social interaction. Under climate change and increases in world population, adoption of precision agriculture could assist farmers to face various challenges to achieve ideal productio...

Digital Precision Agriculture (DPA) is a comprehensive approach to agronomic management that utilizes advanced technologies, such as sensor data analysis and automation, to optimize crop productivity, enhance farm income, and minimize environmental impacts. DPA encompasses various agricultural domains, including pest control, pest management, fertilization, irrigation management, sowing, transplanting, crop health monitoring, yield forecasting, harvesting, and post-harvest stages. Among the enabling technologies for DPA, Unmanned Aerial Vehicles (UAVs) have gained significant attention and mar...

Agriculture has long been an important part of human activities [...]

A farm management system that uses information and technology to identify, analyze, and control the temporal and spatial variability within a field is known as precision farming or precision agriculture. Its goals are to maximize productivity and profitability, preserve the land resource, and minimize production costs. The public's growing environmental consciousness is forcing us to alter agricultural management techniques in order to maintain economic profitability while preserving natural resources like water, air, and soil quality. The application of inputs (such as chemical pesticides and...

Precision agriculture, driven by the growing demand for sustainable farming practices, relies heavily on technologies such as remote sensing. Despite its critical role, a comprehensive review of remote sensing within the context of precision agriculture remains sparse. This paper aims to bridge this gap by providing a thorough overview of remote sensing technologies, their applications, challenges, future trends, and potential impact on precision agriculture. Employing a literature review methodology, we analyzed key studies to comprehend precision agriculture's evolution and remote sensing te...

A systematic review of ML applications in the field of agriculture shows how knowledge-based agriculture can improve the sustainable productivity and quality of the product.

Greenhouse gases released by agriculture account for 19% of global greenhouse gas emission. Moreover, the abuse of pesticides and fertilizers is a fundamental cause of soil and water pollution. Finding sustainable countermeasures for these problems requires completely new approaches and the integration of knowledge. Precision agriculture (PA) is a technology that reduces environmental pollution with minimal input (e.g., fertilizer, herbicides, and pesticides) and maximize the production of high-quality crops by monitoring the conditions and environment of farmland and crops. However, the lack ...

The escalating demands for food, fiber, energy, and water due to swift population growth have underscored the necessity for the sustainable utilization of natural resources. The advent of precision farming tools and machinery since the 1990s has markedly enhanced productivity and optimized the employment of inputs in aquaculture. The burgeoning connectivity in rural regions and its improved integration with data from sensor systems, remote sensors, equipment, and smartphones have paved the way for innovative concepts in Digital Aquaculture. Automation is the most effective strategy to manage s...

This study is to not only present a complete picture, but also to elucidate the context by highlighting major scientific research and applications related to optoelectronics proximate sensors by attempting to create a 360-degree vision.

The use of IoT in the agricultural sector helps to improve sensing and monitoring of production, including farm resource usage, animal behavior, crop growth, and food processing, and it provides a better understanding of the individual agricultural circumstances.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2021 The Authors. Journal of Agricultural Economics published by John Wiley & Sons Ltd on behalf of Agricultural EconomicsSociety. Department of Agricultural Economics, Purdue University, West Lafayette, IN, USA

The purpose of this study was to determine selected Arkansas school-based agricultural education (SBAE) teachers’ perceptions of the importance, ability to teach, inservice needs, and barriers relative to incorporating precision agriculture (PA) into their programs. A non-probability sample (n = 44) of teachers participating in an introductory PA workshop completed the survey. Teachers rated each of the  PA competencies as being above average or high importance but rated their ability to teach each competency as being none or below average. When competencies were grouped into seven PA topics, ...

The adoption of digital technologies in the agricultural sector has been the focus of research in the last few years, assessing the benefits of using electronic devices, robots, sensors, automation and IoT to improve farming sustainability.

This study provides a detailed review of how these IoE subdomains, in conjunction with 6G, blockchain, and machine learning (ML), can enhance precision farming in areas like crop monitoring, resource management, and disease control.

The recent advances of the important soil sensors in agricultural applications, including temperature sensors, moisture sensors, organic matter compounds sensors, pH sensors, insect/pest sensors, and soil pollutant sensors are reviewed.

The main aim of this research is to achieve precision agriculture by selecting suitable data analytics techniques, such as autoregressive integrated moving average, linear regression, artificial neural networks, and decision tree, by trained to forecast weather behaviors such as rainfall, humidity, and temperature.

Precision agriculture is often seen as disembodied and placeless, promised to either bring about a fourth agricultural revolution or as the start of dystopian rural futures, where farmers and their knowledge will be replaced by machines. A growing body of literature shows more nuanced ways of working with precision agriculture. This illustrates the need to investigate how, and under which conditions, precision agriculture is integrated and internalised by farmers. Based on 25 in‐depth interviews with male Dutch crop farmers, contractors, researchers, and ag‐tech developers, we develop the conc...

Based on the definition of precision agriculture, some key techniques of precision agriculture and its study and application situations in the United States and Germary were presented. Several problems involving farmland shortage, water shortage, agricultural environment pollution etc. seriously affect the sustainable agricultural development in Tianjin. The development of precision agricultural is significant to increase the utilization of resources, improve rural eco-environment, as well as promote sound development of agricultural economy. Combined with the situation in Tianjin, four possib...

The devices connected to the IoT network are constantly sending and receiving data based on long range communication protocols are providing information that can be used on the level of data science modules for PA for task optimization and cost minimization.

A smart and novel electric sprayer that can be assembled on a robot with a crop perception system that calculates the leaf density based on a support vector machine (SVM) classifier using image histograms.

The efficacy of IoT simulation on Tinkercad as a tool for modeling and simulating agricultural environments is demonstrated and the potential of smart precision agriculture in enhancing crop productivity, conserving resources, and mitigating environmental impact is underscored.

The increasing global population, expected to reach over 10.3 billion in the mid-2080s, is putting huge pressure on the demand for food, making innovative techniques essential. Conventional methods have relied much on heavy chemical fertilizers, which have devastating environmental consequences, such as pollution and inefficiency of nutrient use. Precision farming deploys specific fertilization methods in response to these challenges, made possible by the latest technologies: remote sensing technology, global positioning system, wireless sensor network, internet of things, blockchain system, a...

This overview paper discusses a series of scheduling problems the authors developed that is pervasive in precision agriculture and agricultural technology and suggests which ones should be addressed and which ones can be deferred.

This work uses and trains You Only Look Once model on video clips of apples, oranges and pumpkins, and implements ResNet as DeepSORT’s new feature extractor, which is lightweight, accurate and generically works on different fruits.