Top Research Papers on Precision Agriculture

A survey regarding the potential use of UAVs in PA is provided, focusing on 20 relevant applications, which investigate in detail 20 UAV applications that are devoted to either aerial crop monitoring processes or spraying tasks.

The findings are that remote sensors are the most used technology, the required knowledge is an important criterion for deciding to implement precision agriculture, and no framework was found that guides its implementation.

The Support Vector Machine (SVM) is a Machine Learning (ML) algorithm which may be used for acquiring solutions towards better crop management. The applications of SVM in precision agriculture (PA) are compared by identifying its interactions with variables, comparing its model performance, highlighting its strengths and weaknesses, as well as suggestions for improvements. From the perspective of six ML applications in PA, we confirmed features which may benefit the model in general (e.g. feature selection) or specific applications (e.g. phenology). SVM was found to outperform most models, wit...

It is argued that this discourse of novelty is a reinvention of precision agriculture in the context of the growing “smart” agricultural economy, and that the smart agricultural economy is perhaps less about supporting land and its stewards than promising future tech and profits.

It is found that temperature and humidity have a larger impact on the sensor readings inside the greenhouse than initially thought, which is successfully solved through the airflow box design.

An overview of remote sensing systems, techniques, and vegetation indices along with their recent (2015–2020) applications in Precision agriculture is provided.

This study aims to briefly review recent scientific and technological trends in PA and their application in crop and livestock farming, serving as a simple research guide for the researcher and farmer in the application of technology to agriculture.

It was shown that the most common disease is blight; fungus is the most important pathogen and grape and watermelon are the most studied crops; the most used drone type is the quadcopter and the most applied machine learning task is classification.

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.

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.

An embedded system enhanced with ML functionalities, ensuring continuous detection of pest infestation inside fruit orchards and guaranteeing an extended battery life thanks to the integration of energy harvesting functionalities is presented.

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.

The applications of nanotechnology and artificial intelligence in agriculture are discussed, highlighting the opportunities and challenges of using these technologies to achieve sustainable and precision agriculture.

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.

Nanofertilizers increase efficiency and sustainability of agricultural crop production. Due to their nanosize properties, they have been shown to increase productivity through target delivery or slow release of nutrients, thereby limiting the rate of fertilizer application required. Nanofertilizers can be synthesized via different approaches ranging from physical and chemical to green (biological) synthesis. The green approach is preferable because it makes use of less chemicals, thereby producing less chemical contamination and it is safer in comparison to physicochemical approaches. Hence, d...

The benefits of nanotechnology in this field include the development of advanced nanomaterials for enhanced seed germination and micronutrient supply, along with the alleviation of biotic and abiotic stress.

The results indicate that 84% of the interviewed farmers use at least one digital technology in their production system that differs according to technological complexity level, and 95% of farmers would like to learn more about new technologies to strengthen the agricultural development in their properties.

In the face of growing challenges in modern agriculture, such as climate change, sustainable resource management, and food security, drones are emerging as essential tools for transforming precision agriculture. This systematic review, based on an in-depth analysis of recent scientific literature (2020–2024), provides a comprehensive synthesis of current drone applications in the agricultural sector, primarily focusing on studies from this period while including a few notable exceptions of particular interest. Our study examines in detail the technological advancements in drone systems, includ...

This work provides a summary of the most recent research activities in the form of research projects implemented and validated by the authors in several European countries, with the objective of presenting the already achieved results, the current investigations and the still open technical challenges.

The subsystems and the architecture of an intelligent irrigation system for precision agriculture, the AREThOU5A IoT platform, and the operation of the IoT node that is utilized in the platform are described.

The paper proposed the prediction model of Apple disease in the apple orchards of Kashmir valley using data analytics and Machine learning in IoT system and discusses the challenges faced when incorporating these technologies in the traditional farming approaches.

The main goal of this article is to acquire an awareness of the Big Data latest applications in smart agriculture and be acquainted with related social and financial challenges to be concentrated on.

A thorough understanding of related terms and techniques involved in the implementation of vision-based intelligent systems for precision agriculture is established, and the challenges associated with implementing generalized computer vision models for real-time deployment of fully autonomous farms are outlined.

A literature review and an analysis of the characteristics of several mobile applications for use in smart/precision agriculture available on the market or developed at research level are presented to provide to farmers an overview of the applications type that exist, what features they provide and a comparison between them.

Agriculture is the primary source of income in developing countries like India. Agriculture accounts for 17 percent of India’s total GDP, with almost 60 percent of the people directly or indirectly employed. While researchers and planters focus on a variety of elements to boost productivity, crop loss due to disease is one of the most serious issues they confront. Crop growth monitoring and early detection of pest infestations are still a problem. With the expansion of cultivation to wider fields, manual intervention to monitor and diagnose insect and pest infestations is becoming increasingly...

Precision farming is made possible by rapid advances in deep learning (DL) and the internet of things (IoT) for agriculture, allowing farmers to upgrade their agriculture operations to sustainably fulfill the future food supply. This paper presents a comprehensive overview of recent research contributions in DL and IoT for precision agriculture. This paper surveys the diverse research on DL applications in agriculture, such as detecting pests, disease, yield, weeds, and soil, including fundamental DL techniques. Also, the work describes the IoT architecture and analyzes sensor categorization, ...

A hierarchical structure based on the collaboration between unmanned aerial vehicles (UAVs) and federated wireless sensor networks (WSNs) for crop monitoring in precision agriculture proved to be a robust and efficient solution for data collection, control, analysis, and decisions in such specialized applications.

This paper makes the first comprehensive but not exhaustive review of the public image datasets collected under field conditions for facilitating precision agriculture, which include 15 datasets on weed control, 10 datasets on fruit detection, and 9 datasets on miscellaneous applications.

The excessive use of conventional fertilizers leads to environmental issues associated with the loss of nutrient through leaching, volatilization, denitrification and surface run-off. Biochar-based fertilizer has gained much research interest as it can be used as a slow release fertilizer. Biochar-based fertilizer can alleviate the properties of soil to slow down the nutrient release rate. However, the sustained release mechanism of biochar-based fertilizer is still facing limitations. As a solution to mitigate this issue, the integration of encapsulating technology and biochar-based fertilize...

A comprehensive survey on the importance of integrating both blockchain and IoT in developing smart applications in precision agriculture and proposed novel blockchain models that can be used as important solutions for major challenges in IoT-based precision agricultural systems.

A wireless sensor network of low-cost sensor nodes for soil moisture that can help farmers optimize the irrigation processes in precision agriculture and developed a specific communication protocol to improve the performance.

Climate change has introduced many challenges, which affect various sectors including agriculture. The major challenge lies in increasing food productivity while confronting climatic changes. The recent advent of Information and Communication Technology (ICT) provides a solution to increase food productivity and address climate change issues in the agricultural domain. The growth of Wireless Sensor Networks (WSNs), Internet of Things (IoT) technologies, and particularly the introduction of Unmanned Aerial Vehicles (UAVs) leads to the development of economical precision agriculture applications...

A step approach is defined to describe the performance dichotomy between resource availability and objectives for PA and a multidisciplinary architecture is proposed: AgriFusion, for efficient and cost-effective agriculture solutions.

It is concluded that Sentinel-2 has a wide range of useful applications in agriculture, yet still with room for further improvements, and compared the panoply of satellites currently in use for land remote sensing that are relevant for agriculture to the Sentinel- 2 A + B constellation features.

In recent years, Light Detection and Ranging (LiDAR) technology has been one of the most innovative subjects in laser scanning, remote sensing, and object detection systems. This technology may be popular because it can pinpoint structures or zones of interest in millimetre detail. It can also highlight variations and irregularities, such as surface degradation and vegetation growth. This paper presents a review of the specialised literature on LiDAR systems applied to precision agriculture; specifically, in cultivating crops. First, some preliminaries of LiDAR systems according to the mode of...

The applications of remote sensing technologies to precision agriculture were reviewed. The different uses of conventional satellites and unmanned aerial vehicles (UAVs) for data collection were also examined. The ways in which the collected data have been used in terms of precision agriculture are laid out in further detail. Modern UAVs provide a range of advantages over conventional satellites in data collection and analysis. In addition, precision agriculture itself is a wide topic; and practitioners, researchers, and policy planners need to account for a complex value chain with diverse st...

The suggested model achieves the automatic right diagnosis of banana leaf diseases and gives a workable method for the detection of crop leaf diseases with high recognition accuracy.

Greenhouse technology is an opportune tool for increasing crop yields through the accurate adjustment of internal climate growth conditions such as temperature, humidity, light intensity and CO2 concentration. The aim of this paper is to present an overview of the most recent technological advances in modern greenhouses, and highlights their application in hardware design, environmental monitoring, dynamics modeling, microclimate control, energy optimization, green energy integration and storage systems implementation. The main objectives can be summarized in presenting sufficient contribution...

Abstract Pesticide spraying is one of the risky and very essential task in agriculture to protect plants from harmful organisms. Many farmers are used manual pesticide spraying devices that they carry these devices on their shoulders and spray on the entire plant. Due to this, harmful pesticide chemicals spread into the air and may enter into the body of farmers and farm workers through the breathing system and mostly affect their body parts even, so many farmers lost their life. For this serious problem, we present the best solution to perform this task without the intervention of man is to u...

Instance segmentation opens many possibilities for optimized weed removal actions, and Weed electrification, for instance, could benefit from the targeted adjustment of the voltage, frequency, and location of the electrode to the plant.