Littérature scientifique sur le sujet « Precision Agriculture Adoption, Digitalization, Smart Farming »
Créez une référence correcte selon les styles APA, MLA, Chicago, Harvard et plusieurs autres
Consultez les listes thématiques d’articles de revues, de livres, de thèses, de rapports de conférences et d’autres sources académiques sur le sujet « Precision Agriculture Adoption, Digitalization, Smart Farming ».
À côté de chaque source dans la liste de références il y a un bouton « Ajouter à la bibliographie ». Cliquez sur ce bouton, et nous générerons automatiquement la référence bibliographique pour la source choisie selon votre style de citation préféré : APA, MLA, Harvard, Vancouver, Chicago, etc.
Vous pouvez aussi télécharger le texte intégral de la publication scolaire au format pdf et consulter son résumé en ligne lorsque ces informations sont inclues dans les métadonnées.
Articles de revues sur le sujet "Precision Agriculture Adoption, Digitalization, Smart Farming"
1
Triantafyllou, Anna, Panagiotis Sarigiannidis et Stamatia Bibi. « Precision Agriculture : A Remote Sensing Monitoring System Architecture † ». Information 10, no 11 (9 novembre 2019) : 348. http://dx.doi.org/10.3390/info10110348.
Texte intégralRésumé :
Smart Farming is a development that emphasizes on the use of modern technologies in the cyber-physical field management cycle. Technologies such as the Internet of Things (IoT) and Cloud Computing have accelerated the digital transformation of the conventional agricultural practices promising increased production rate and product quality. The adoption of smart farming though is hampered because of the lack of models providing guidance to practitioners regarding the necessary components that constitute IoT-based monitoring systems. To guide the process of designing and implementing Smart farming monitoring systems, in this paper we propose a generic reference architecture model, taking also into consideration a very important non-functional requirement, the energy consumption restriction. Moreover, we present and discuss the technologies that incorporate the seven layers of the architecture model that are the Sensor Layer, the Link Layer, the Encapsulation Layer, the Middleware Layer, the Configuration Layer, the Management Layer and the Application Layer. Furthermore, the proposed Reference Architecture model is exemplified in a real-world application for surveying Saffron agriculture in Kozani, Greece.
2
Sarri, Daniele, Stefania Lombardo, Andrea Pagliai, Carolina Perna, Riccardo Lisci, Valentina De Pascale, Marco Rimediotti, Guido Cencini et Marco Vieri. « Smart Farming Introduction in Wine Farms : A Systematic Review and a New Proposal ». Sustainability 12, no 17 (3 septembre 2020) : 7191. http://dx.doi.org/10.3390/su12177191.
Texte intégralRésumé :
This study shows a new methodological proposal for wine farm management, as a result of the progressive development of the technological innovations and their adoption. The study was carried out in Italy involving farmers, workers, or owners of wine farms who are progressively introducing or using precision agriculture technologies on their farm. The methodology proposed was divided in four stages (1. understanding the changes in action; 2. identifying the added value of Smart Farming processes; 3. verifying the reliability of new technologies; 4. adjusting production processes) that can be applied at different levels in vine farms to make the adoption of precision agriculture techniques and technologies harmonious and profitable. Data collection was carried out using a participant-observer method in brainstorming sessions, where the authors reflected on the significance of technology adoption means and how to put them in practice, and interviews, questionnaire surveys, diaries, and observations. Moreover, project activities and reports provided auxiliary data. The findings highlighted the issues of a sector which, although with broad investment and finance options, lacks a structure of human, territorial, and organizational resources for the successful adoption of technological innovations. The work represents a basis for the future development of models for strategic scenario planning and risk assessments for farmers, policymakers, and scientists.
3
Hrynevych, Oksana, Miguel Blanco Canto et Mercedes Jiménez García. « Tendencies of Precision Agriculture in Ukraine : Disruptive Smart Farming Tools as Cooperation Drivers ». Agriculture 12, no 5 (16 mai 2022) : 698. http://dx.doi.org/10.3390/agriculture12050698.
Texte intégralRésumé :
Precision farming innovations are designed to improve the efficiency of agricultural activities via minimal initial input of material and human resources and avoiding harmful effects on the environment on one hand and automatizing the production on another hand, thus providing environmental, social and economic benefits. In the article, the tendencies in the adoption of precision agriculture technologies (PAT) in Ukraine were observed, with a specific focus on cooperatives as a valuable tool of social and solidarity economy helping to achieve progress in local rural development. On the example of cooperatives, applying a technology acceptance model (TAM) has identified how the adoption of new smart farming tools influence their behavior in implementing technological innovations. The results of the study will be of particular interest to representatives of other cooperatives and to agribusiness players engaged in agriculture or software development. In addition, the outputs will be useful for researchers in the field of the socio-economic development of territories and the impact of new technologies on it, as well as for local governments and higher-level government officials, which can contribute to the implementation of better rural development strategies.
4
Strizhkova, Alla, Kateryna Tokarieva, Anna Liubchych et Svitlana Pavlyshyn. « Digital Farming as Direct of Digital Transformation State Policy ». European Journal of Sustainable Development 9, no 3 (1 octobre 2020) : 597. http://dx.doi.org/10.14207/ejsd.2020.v9n3p597.
Texte intégralRésumé :
Article is devoted considerations of digital agriculture as directly public policy. By authors it is considered terminological a variety of the studied phenomenon with which scientists of different specialties allocate an object of research. If at first among landowners arose and became settled the term "exact agriculture", then the names "E-Agriculture" and "digital farming" become even more relevant now, however in their work it is considered as synonyms. The essence and advantages of electronic agriculture, prospect revival of economic activity and efficiency of using technologies of digital agriculture and also a condition of legal regulation of digital agriculture in Ukraine are analyzed. Special relevance the idea of use of electronic agriculture in Ukraine enters in connection with plans of the Verkhovna Rada of Ukraine and the government to finish a land reform - to open the market of the land. Offers on further development of state regulation of digital agriculture are formulated.
Keywords: computer aided farming, digital farming, digital transformation, digitalization, e-agriculture, precision agricuture, smart farming, state regulation
5
Baurina, S. B., S. V. Khudyakov et M. Y. Uchirova. « Digital Mainstream in the Promotion of Food Industry Products ». IOP Conference Series : Earth and Environmental Science 988, no 5 (1 février 2022) : 052041. http://dx.doi.org/10.1088/1755-1315/988/5/052041.
Texte intégralRésumé :
Abstract Digitalization of the food industry involves the use of modern digital information technologies at all stages of agro-industrial production, i.e. digital transformation of the industry, as well as other high technologies formed at the intersection of electronics and robotics. Information technologies, digital technologies, science-intensive technologies are currently closely intertwined, and their implementation in the industry depends not only on the degree of computerization, but also on the level of use of systems, devices and mechanisms that allow for the possibility of autonomous use (without human intervention). The article outlines well-known advanced innovative technologies, including “smart”, “precision” farming, artificial intelligence, nanotechnology, biotechnology, off-ground growing of plants (hydroponics) and vertical farming, satellite navigation systems for combines and other equipment, autonomous robots, unmanned aerial vehicles, “Internet of Things”, blockchain technologies. The characteristics of existing digital technologies are given and the options for using artificial intelligence in the food industry are described. In addition to artificial intelligence, complex agricultural technologies are: “smart” agriculture, “smart farming”, “precision farming”, etc.
6
Sigalingging, Xanno, Setya Widyawan Prakosa, Jenq-Shiou Leu, He-Yen Hsieh, Cries Avian et Muhamad Faisal. « SCANet : Implementation of Selective Context Adaptation Network in Smart Farming Applications ». Sensors 23, no 3 (25 janvier 2023) : 1358. http://dx.doi.org/10.3390/s23031358.
Texte intégralRésumé :
In the last decade, deep learning has enjoyed its spotlight as the game-changing addition to smart farming and precision agriculture. Such development has been predominantly observed in developed countries, while on the other hand, in developing countries most farmers especially ones with smallholder farms have not enjoyed such wide and deep adoption of this new technologies. In this paper we attempt to improve the image classification part of smart farming and precision agriculture. Agricultural commodities tend to possess certain textural details on their surfaces which we attempt to exploit. In this work, we propose a deep learning based approach called Selective Context Adaptation Network (SCANet). SCANet performs feature enhancement strategy by leveraging level-wise information and employing context selection mechanism. In exploiting contextual correlation feature of the crop images our proposed approach demonstrates the effectiveness of the context selection mechanism. Our proposed scheme achieves 88.72% accuracy and outperforms the existing approaches. Our model is evaluated on the cocoa bean dataset constructed from the real cocoa bean industry scene in Indonesia.
7
Shevtsova, Hanna, Nataliia Shvets, Maiia Kramchaninova et Hanna Pchelynska. « In Search of Smart Specialization to Ensure the Sustainable Development of the Post-Conflict Territory : the Case of the Luhansk Region in Ukraine ». European Journal of Sustainable Development 9, no 2 (1 juin 2020) : 512–24. http://dx.doi.org/10.14207/ejsd.2020.v9n2p512.
Texte intégralRésumé :
This work highlights a range of problems related to ensuring sustainable development of post-conflict territories, as well as ways to overcome those through smart specialization approach. The influence of military conflict on Luhansk region's economy structure and economy's pace of development had been determined. Capacities of smart specialization as a contemporary tool meant for intensifying innovative development, structural modernization and improving competitiveness of regions had been studied. While researching regional context the current state and structure of the chemical sector, which is region's traditional specialty, had been analyzed and also its SWOT analysis had been conducted. Potential for diversification, innovative and cross-sectoral evolution of the existing chemical business was discovered. We pay attention to chemical production's digitalization horizons and its integration into rapidly growing region's agricultural sector as part of precision farming concept. The suggested agrochemical ecosystem's model facilitates communications between leading stakeholders, increases efficiency of entrepreneurial discovery process, creates new areas of specialization and new leverage for ensuring region's sustainable development. Keywords: sustainable development, smart specialization, chemical industry, agriculture, ecosystem, precision farming, Luhansk region
8
Groher, Tanja, Katja Heitkämper, Achim Walter, Frank Liebisch et Christina Umstätter. « Status quo of adoption of precision agriculture enabling technologies in Swiss plant production ». Precision Agriculture 21, no 6 (8 mai 2020) : 1327–50. http://dx.doi.org/10.1007/s11119-020-09723-5.
Texte intégralRésumé :
Abstract This paper presents the state of application of Precision Agricultural enabling Technology (PAT) in Swiss farms as an example for small-scale, highly mechanised Central European agriculture. Furthermore, correlations between farm and farmers’ characteristics and technology adoption were evaluated. Being part of a comprehensive and representative study assessing the state of mechanisation and automation in Swiss agriculture, this paper focuses on the adoption of Driver Assistance Systems (DAS) and activities in which Electronic Measuring Systems (EMS) are used. The adoption rate of DAS was markedly higher compared to EMS in all agricultural enterprises. The adoption rate was highest for high-value enterprise vegetables and surprisingly low for the high-value enterprise grapes. The results of a binary logistic regression showed that farmers located in the mountain zone were less likely to adopt PAT compared to farmers in the valley. Small farm size correlated with low adoption rates and vice versa showing adoption happens country-specific in the upper farm size distribution. The results show the potential for novel technologies to be adopted by farmers of high-value products. Furthermore, technologies have been partially used to reduce physical workload but not yet to evaluate crop or management performance to support decisions. However, automatic collection and forwarding of data is a fundamental step towards Smart Farming realizing its full potential in the future.
9
Caria, Sara, Todde, Polese et Pazzona. « Exploring Smart Glasses for Augmented Reality : A Valuable and Integrative Tool in Precision Livestock Farming ». Animals 9, no 11 (1 novembre 2019) : 903. http://dx.doi.org/10.3390/ani9110903.
Texte intégralRésumé :
The growing interest in Augmented Reality (AR) systems is becoming increasingly evident in all production sectors. However, to the authors’ knowledge, a literature gap has been found with regard to the application of smart glasses for AR in the agriculture and livestock sector. In fact, this technology allows farmers to manage animal husbandry in line with precision agriculture principles. The aim of this study was to evaluate the performances of an AR head-wearable device as a valuable and integrative tool in precision livestock farming. In this study, the GlassUp F4 Smart Glasses (F4SG) for AR were explored. Laboratory and farm tests were performed to evaluate the implementation of this new technology in livestock farms. The results highlighted several advantages of F4SG applications in farm activities. The clear and fast readability of the information related to a single issue, combined with the large number of readings that SG performed, allowed F4SG adoption even in large farms. In addition, the 7 h of battery life and the good quality of audio-video features highlighted their valuable attitude in remote assistance, supporting farmers on the field. Nevertheless, other studies are required to provide more findings for future development of software applications specifically designed for agricultural purposes.
10
Kovalyev, I. L., et M. N. Kostomakhin. « Development vectors and foreign experience of information technologies in the agro-industrial complex of Russia and Belarus ». Glavnyj zootehnik (Head of Animal Breeding), no 1 (1 janvier 2021) : 49–61. http://dx.doi.org/10.33920/sel-03-2101-06.
Texte intégralRésumé :
The current stage of information technology development is characterized as digital called BCG (Boston Consulting Group) digitalization, while the analog period in agriculture is over, the industry has entered the digital era, which means that by 2050 the use of new generation technologies will be able to increase the productivity of world agriculture by 70 %. The main stages of information technology development in the world considers some of the most important areas of it technology development and global trends in the digital transformation of the agro-industrial complex based on the analysis of global scientific achievements, research reports, articles by well-known scientists, scientific and expert organizations have been investigated in the article. The main trends that determine the conceptual development of the so-called “Smart (digital) agriculture” are identified, the active use of elements of which contributes in every possible way to the highly rational social, economic, technical and technological development of the agricultural sector. A promising area is Precision Animal Husbandry (similar to Precision Farming). Among the elements of Precision Animal Husbandry the most widely used are identification and monitoring of individual animals using modern information technologies (feeding ration, milk yield, growth, body temperature, activity), meeting their individual needs; automatic regulation of the microclimate and control of harmful gases; monitoring the health of the herd, product quality; electronic database of the production process; robotization of the milking process.
Thèses sur le sujet "Precision Agriculture Adoption, Digitalization, Smart Farming"
1
lombardo, stefania. « Studies on the adoption of digitalization and high technology for precision agriculture ». Doctoral thesis, 2020. http://hdl.handle.net/2158/1212002.
Texte intégralRésumé :
The study investigates which are the effective approaches for the introduction in the use of new technologies in sustainable precision agriculture and what the necessary networks are for effective technology adoption.
Lo studio indaga quali siano gli approcci proficui per l’introduzione nell’uso delle nuove tecnologie in agricoltura di precisione sostenibile e quali siano le reti necessarie perché l’adozione della tecnologia sia effettiva
Chapitres de livres sur le sujet "Precision Agriculture Adoption, Digitalization, Smart Farming"
1
Kumari, Shiva, Yaman Parasher, Sidharth Mehra et Prabhjot Singh. « Digitization in Agriculture ». Dans Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture, 1–24. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-1722-2.ch001.
Texte intégralRésumé :
The chapter starts with a focus on the current scenario of the digitalization in agriculture space. It pinpoints the reason behind the need and explains the emergence of new Agtech-based startups that work on new innovative digital technologies. The chapter also tries to discuss the post-COVID implications along with the merits of digitalization in the agricultural domain. Apart from this, it also discusses different aspects of the digitalization on the agriculture space in general that includes the concept of telematics, precision farming, blockchain, artificial intelligence, etc. At last, some of the main challenges like the issue of connectivity, interoperability, portability, and need of public and private sector cooperation were discussed.
2
R. Shamshiri, Redmond, Siva K. Balasundram, Abdullah Kaviani Rad, Muhammad Sultan et Ibrahim A. Hameed. « An Overview of Soil Moisture and Salinity Sensors for Digital Agriculture Applications ». Dans Digital Agriculture, Methods and Applications [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.103898.
Texte intégralRésumé :
Soil salinity and the water crisis are imposing significant challenges to more than 100 countries as dominant factors of agricultural productivity decline. Given the rising trend of climate change and the need to increase agricultural production, it is crucial to execute appropriate management strategies in farmlands to address salinity and water deficiencies. Ground-based soil moisture and salinity sensors, as well as remote sensing technologies in satellites and unmanned aerial vehicles, which can be used for large-scale soil mapping with high accuracy, play a pivotal role in precision agriculture as advantageous soil condition monitoring instruments. Several barriers, such as expensive rates and a lack of systematic networks, may hinder or even adversely impact the progression of agricultural digitalization. As a result, integrating proximal equipment with remote sensing and Internet of things (IoT) capabilities has been shown to be a promising approach to improving soil monitoring reliability and efficiency. This chapter is an attempt to describe the pros and cons of various soil sensors, with the objective of promoting IoT technology in digital agriculture and smart farming.
Actes de conférences sur le sujet "Precision Agriculture Adoption, Digitalization, Smart Farming"
1
Vasilevska, Daina, et Baiba Rivza. « DIGITAL TRANSFORMATION OF AGRICULTURE : PRIORITIES AND BARRIERS ». Dans 22nd SGEM International Multidisciplinary Scientific GeoConference 2022. STEF92 Technology, 2022. http://dx.doi.org/10.5593/sgem2022/2.1/s07.04.
Texte intégralRésumé :
In the practice of leading countries, digital transformation implies the industry principle of supporting the introduction of new technologies. At the same time, programs and projects can be built both on the principle of introducing any one promising group of technologies in several industries, where it is especially relevant, and provide for the digital transformation of a particular industry through the forced introduction of many technologically heterogeneous solutions that are in demand in a given sector of the economy or social sphere. Digital transformation contributes to solving systemic problems in industries, reorganizing labor and automating routine tasks. Thus, in the electric power industry, the number of accidents at infrastructure facilities is reduced, in construction - the level of injuries at the construction site. Digital products improve coordination within and between organizations and reduce transaction costs. For example, platform solutions in logistics reduce the role of intermediaries, while expanding the possibilities for communication with end users. The digital transformation of agriculture is largely based on the integrated implementation of a number of digital technologies within the interrelated concepts of precision farming and smart agriculture. The purpose of this study is to determine the level of digitalization of agriculture in Latvia. Determine which digital technologies are most in demand in the country's agriculture, study the change in demand for advanced digital technologies, and identify the main constraints for the development of digital agriculture.
2
Lados, Mihály, et Ferenc Pongrácz. « Facing urban challenges ». Dans The Challenges of Analyzing Social and Economic Processes in the 21st Century. Szeged : Szegedi Tudományegyetem Gazdaságtudományi Kar, 2020. http://dx.doi.org/10.14232/casep21c.5.
Texte intégralRésumé :
Closed to three-quarters of Europeans live in cities today, and by the growth of the population worldwide, this ratio is ever increasing. The accelerated speed of urbanization poses unprecedented challenges on people, cities, and the environment. Sustainability became a key global objective since Rio via Tokyo until Paris Agreement. The United Nations prepared an agenda for a better and more sustainable future for all. The 17 Goals are related to global challenges such as climate change, poverty, and the effects of urbanization. Over the last decade, various Smart City approaches have emerged among the government, non-profit sectors, and industries to use Information and Communication Technology as a tool to manage these challenges and to improve the quality of life for their citizens. At the same time, Industry 4.0, the digitalization of industries, has diffused across the world, setting the scene for a new stage of innovation yet keeping the competitiveness of business players. Tungsram, a multinational corporation headquartered in Hungary, has refocused its mission and stood up to expand its product portfolio by including Smart City solutions. Tungsram Edge focuses on three major Smart City offerings: indoor farming, efficient buildings, and Smart Solutions. Indoor farming (AgriTech), a science-based approach to agriculture, uses the latest research to establish precision indoor farming facilities. Efficient buildings (PropTech) has come to life to support the universal goal of reducing cities’ ecological footprint. Each smart solution has a direct or indirect effect on several objectives of the Sustainable Development Goals of the United Nations. The first part of the paper identifies the key contemporary challenges of cities and industries and the evolution and links of Smart City and Industry 4.0 approaches. The second part of the paper is a case study of a multinational company headquartered in Hungary entering into these processes by building a Smart City Action Plan and by developing key smart products (Smart City portfolio) to react to and to provide solutions for urban challenges.