Enhancing smart farming through the applications of Agriculture 4.0 technologies

International Journal of Intelligent Networks, Journal Year: 2022, Volume and Issue: 3, P. 150 - 164

Published: Jan. 1, 2022

Agriculture 4.0 represents the fourth agriculture revolution that uses digital technologies and moves toward a smarter, more efficient, environmentally responsible sector. Agricultural have emerged to enhance sustainability discover effective farm methods. This encompasses all digitalisation automation processes in business our daily lives, including Big Data, Artificial Intelligence (AI), robots, Internet of Things (IoT), virtual augmented reality. These technological advancements are having profound impact on lives. From technical standpoint, it brings us precision agriculture. provides data-driven strategy for efficiently growing maintaining crops cultivable land, enabling farmers use most resources at their disposal. Throughout supply chain, operations create massive volumes data. Most this information was previously untouched, but with help big data technologies, such can be used improve performance production any crop. Depending crop type its growth needs, digitised harvesters handle huge areas various situations, particularly paper is brief about condition. Smart farming, Various key specific domains Exploring Domain discussed detail and, finally, identified significant applications technologies. essential lives since they simplify duties without recognising them. In systems, fleets equipment employ current infrastructures like cloud computing connect, identify processing condition different regions requirement input materials coordinate machinery.

Language: Английский

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Off-Road Electric Vehicles and Autonomous Robots in Agricultural Sector: Trends, Challenges, and Opportunities

Vehicles, Journal Year: 2022, Volume and Issue: 4(3), P. 843 - 864

Published: Aug. 15, 2022

This paper describes the development trends and prospects of green-energy-based off-road electric vehicles robots in agricultural sector. Today, agriculture sector faces several challenges, such as population growth, increasing energy demands, labor shortages, global warming. Increases demand cause many challenges worldwide; therefore, methods are suggested to achieve independence from fossil fuels reduce emissions. From a long-term point view, electrification renewable sources appear be an essential step for robotic smart farming Agriculture 5.0. The trend technological growth using fully autonomous seems one emerging technologies tackle increased food address environmental issues. vehicles, alternative green fuels, more energy-efficient hybrid electric, robotic, is improving work quality operator comfort. Furthermore, related digital advanced network communication, artificial intelligence techniques, blockchain discussed understand opportunities industry research.

Language: Английский

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Open Innovation in Agribusiness: Barriers and Challenges in the Transition to Agriculture 4.0

Sustainability, Journal Year: 2023, Volume and Issue: 15(11), P. 8562 - 8562

Published: May 25, 2023

Industry 4.0 digital technologies in agribusiness will enable traditional farming systems to migrate Agriculture 4.0. Open innovation emerges as an enabler for implementing these and increased sector competitiveness. However, there are still doubts questions about how open relate drive This study identified which of have more adherence agribusiness, what the barriers facilitators using are, can increase competitiveness agribusiness. The results show that related Internet Things (IoT) is most prominent. main users’ need knowledge advanced skills, evidences investment training operators. Among stand pre-existence several technologies, bring with them already defined basic structures, control technology, communication between systems. To overcome enhance migration 4.0, developing devices, tools, systems, software, machines essential. More stakeholders, managers, practitioners may share such opportunities through concept Innovation. benefit from it, facilitators, should search alternatives their problems engineering solutions providers.

Language: Английский

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A Bibliometric Review of the Use of Unmanned Aerial Vehicles in Precision Agriculture and Precision Viticulture for Sensing Applications

Remote Sensing, Journal Year: 2022, Volume and Issue: 14(7), P. 1604 - 1604

Published: March 27, 2022

This review focuses on the use of unmanned aerial vehicles (UAVs) in precision agriculture, and specifically, viticulture (PV), is intended to present a bibliometric analysis their developments field. To this aim, research papers published last 15 years presented based Scopus database. The shows that researchers from United States, China, Italy Spain lead agriculture through UAV applications. In terms employing UAVs PV, are fast extending work followed by finally States. Additionally, paper provides comprehensive study popular journals for academicians submit work, accessible funding organizations, nations, institutions, authors conducting utilizing agriculture. Finally, emphasizes necessity using PV as well future possibilities.

Language: Английский

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Experimenting Agriculture 4.0 with Sensors: A Data Fusion Approach between Remote Sensing, UAVs and Self-Driving Tractors

Sensors, Journal Year: 2022, Volume and Issue: 22(20), P. 7910 - 7910

Published: Oct. 18, 2022

Geomatics is important for agriculture 4.0; in fact, it uses different types of data (remote sensing from satellites, Unmanned Aerial Vehicles-UAVs, GNSS, photogrammetry, laser scanners and other data) therefore fusion techniques depending on the applications to be carried out. This work aims present a study area concerning integration acquired (using techniques) remote techniques, UAVs, autonomous driving machines fusion, all reprocessed visualised terms results obtained through GIS (Geographic Information System). In this we emphasize importance methodologies managing nature with optimise vineyard cultivation production. particular, note applied (focusing vineyard) geomatics-type developed works integrated here used optimised order make contribution 4.0. More specifically, NDVI (Normalized Difference Vegetation Index) multispectral satellite images drone (suitably combined) identify vigour plants. We then an guided vehicle (equipped sensors monitoring systems) which, by estimating optimal path, allows us fertilisation, irrigation, etc., using various sensors. Everything improve management field according its potential, also historical environmental, climatic socioeconomic characteristics area. For purpose, experiments out individually application cases have been into are coordinated provide research/application cues Agriculture

Language: Английский

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Industrial revolution and smart farming: a critical analysis of research components in Industry 4.0

The TQM Journal, Journal Year: 2024, Volume and Issue: unknown

Published: May 21, 2024

Purpose The domains of Industry 4.0 and Smart Farming encompass the application digitization, automation, data-driven decision-making principles to revolutionize conventional sectors. intersection these two fields has numerous opportunities for industry, society, science, technology research. Relatively, this is new, still, many grey areas need be identified. This research a step toward identifying current trends. Design/methodology/approach present study examines prevailing patterns prospective prospects within Farming. accomplished by utilizing Latent Dirichlet Allocation (LDA) methodology applied data procured from Scopus database. Findings By examining available literature extensively, researchers have successfully discovered developed three separate questions. questions mentioned above were afterward examined with great attention detail after using LDA on dataset. paper highlights notable finding lack existing scholarly in combined field. database consists restricted collection 51 papers. Nevertheless, forthcoming terrain harbors immense possibilities exploration offers plethora additional investigation cerebral evaluation. Research limitations/implications Industrial Revolution's Farming's practical effects, focusing proposed method could help agricultural practitioners implement technology. It additionally counsel developers innovation ease transfer. regulatory frameworks, incentive programs resource conservation may policymakers government agencies. Practical implications proposes that incorporation into operations can enhance efficiency, production sustainability. Furthermore, it significance creating user-friendly solutions specifically tailored farmers companies. indicates implementation supportive legislative programmes methods might encourage adoption smart technologies, resulting more sustainable practices. Social Originality/value Based thorough examination literature, been established there convergence However, progress achieved field seclusion. To date, provided dataset not subjected analysis technique any researcher.

Language: Английский

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Harvesting a sustainable future: An overview of smart agriculture's role in social, economic, and environmental sustainability

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 434, P. 140338 - 140338

Published: Dec. 25, 2023

Language: Английский

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Application of Quality 4.0 (Q4.0) and Industrial Internet of Things (IIoT) in Agricultural Manufacturing Industry

AgriEngineering, Journal Year: 2023, Volume and Issue: 5(1), P. 537 - 565

Published: March 7, 2023

The objective of this research is to apply Quality 4.0 (Q4.0) concept in Agriculture (A4.0) digitize the traditional quality management (QM) system and demonstrate effectiveness zero-defect manufacturing (ZDM) agricultural part industry. An autonomous was developed based on ZDM using Industrial Internet Things (IIoT). Both systems were evaluated six-sigma indicators machining inspection cost analysis. resulted a significant improvement CARD148 manufacturing, increasing process from low level sigma high (0.75 5.10 sigma). component rejection rate reduced by percentage, leading economic benefits reduction cost. yield also increased percentage. found be consistent improving turning process, with notable increases tool life total significantly, while PPM value notably. While study focuses agriculture-related organizations, has potential for other industries improve levels, particularly such as automotive medical.

Language: Английский

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A comprehensive review of soil organic carbon estimates: Integrating remote sensing and machine learning technologies

Journal of Soils and Sediments, Journal Year: 2024, Volume and Issue: 24(11), P. 3556 - 3571

Published: Oct. 5, 2024

Abstract Purpose Accurately assessing soil organic carbon (SOC) content is vital for ecosystem services management and addressing global climate challenges. This study undertakes a comprehensive bibliometric analysis of estimates SOC using remote sensing (RS) machine learning (ML) techniques. It showcases the historical growth thematic evolution in research, aiming to amplify understanding estimation themes provide scientific support change adaptation mitigation. Materials Methods Employing extensive literature database analysis, network clustering techniques, reviews 1,761 articles on RS technologies 490 employing both ML technologies. Results Discussion The results indicate that satellite-based RS, particularly Landsat series, predominant other associated studies, with North America, China, Europe leading evaluations Africa having low adopting technology. Trends research demonstrate an from basic mapping advanced topics such as (C) sequestration, complex modeling, big data utilization. Thematic clusters co-occurrence suggest interplay between technology development, environmental surveys, properties, dynamics. Conclusion highlights synergy ML, techniques proving be critical accurate estimation. These findings are crucial estimation, informed strategic decision-making.

Language: Английский

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Agriculture Digitalization: A Global Examination Based on Bibliometric Analysis

IEEE Transactions on Engineering Management, Journal Year: 2022, Volume and Issue: 71, P. 1330 - 1345

Published: March 30, 2022

Several research studies discuss the process of agriculture digitalization proposing technologies able to face current agri-food challenges. However, extant bibliometric do not fully exploit complementarity different modern tools, such as performance analysis and science mapping consider entire field timespan. Therefore, aim this study is complement update previous works provide a broad quantitative qualitative view Agriculture 4.0 by using synergistically mapping. The was realized on sample 2334 papers adopting statistical frequency VOSviewer. Performance provided key findings about following indicators: subject areas, publications trend, most productive journals, document types, authors productivity, authors' index keywords, cited papers, influent institutions, country map collaboration, documents funding sponsor. Science main thematic field' clusters their evolution overtime: technology application in agricultural industry, data model for prediction, experimentation applicative smart agriculture, decision support systems crop monitoring. This could benefit: food companies, supporting identification; governments, suggesting policies stimulate process; academics, incentivizing more consciousness topic agenda; those who approach first time, facilitating bibliographical referencing.

Language: Английский

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