Emerging Technologies in Agriculture

Sadiku, Matthew N. O.; Ashaolu, Tolulope Joshua; Musa, Sarhan M.

doi:10.51542/ijscia.v1i1.6

Cited by 13 publications

(5 citation statements)

References 7 publications

(5 reference statements)

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“…Deep learning, a subfield within the broader domain of machine learning, is founded upon our comprehension of the structural organization of the human brain. The utilization of artificial neural networks inside deep learning serves as the foundational framework for current advancements in the field of artificial intelligence, encompassing notable applications like as autonomous vehicles and ChatGPT [25][26][27].…”

Section: Difference Between Ai Machine and Deep Learningmentioning

confidence: 99%

Integration of Blockchain and AI: Exploring Application in the Digital Business

Xuan,

Ness

2023

JERR

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Artificial intelligence (AI) and blockchain are two disruptive technologies that have emerged from the Fourth Industrial Revolution (IR4.0) and have brought about significant transformations in the industry. The convergence of artificial intelligence (AI) with blockchain technology presents significant opportunities for the development of novel business models facilitated by digitalization. The current body of research pertaining to the integration of artificial intelligence (AI) with blockchain technology is available, although there is a lack of comprehensive understanding of the practicality and effectiveness of this integration within the business context. In order to bridge this existing knowledge gap, the primary objective of this research endeavor is to comprehensively analyze and delineate the various applications and advantages of integrated artificial intelligence (AI) and blockchain platforms within diverse sectors of the business industry.

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Section: Difference Between Ai Machine and Deep Learningmentioning

confidence: 99%

Integration of Blockchain and AI: Exploring Application in the Digital Business

Xuan,

Ness

2023

JERR

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“…Leveragingtheblockchain'selectronicdistributionledgerandchainoftrustisanaddedbenefitto agriculturetorecordanddigitizetransactionssuchassupplychaintransfers,foodtraceability,disease outbreak, and manufacturing (Sadiku et al, 2020). Ku (2021) opined that blockchain provides a mechanismfortheagriculturalandfoodproductionprocesstoincreasetraceability.Anotheraspect ofblockchainisthattheledgerhelpsprovideinsightintomarketpricingandcreatesawarenessof thesupplyanddemandrelationshipintheagricultureandfoodindustries(Sadikuetal.,2020).The benefitsofblockchaininthefarmingandfoodindustriesarestillevolving;nonetheless,theadvantages listedabovehighlighttechnologicalgainsfromanelectronicdistributionledger.…”

Section: Blockchainmentioning

confidence: 99%

“…Artificial intelligence and machine learning in agriculture are used to automate the discovery of actionable patterns in data (Sadiku et al, 2020). Artificial intelligence and machine learning algorithmsenablefarmerstoexaminefarmingdatatoenhancecropandlivestockproductivityand outputandoptimizecost(Sadikuetal.,2020).Artificialintelligenceisavitaltechnologicalcapability inagriculture.Itenablesfarmerstomakeinformeddecisionstooffsetclimatechange,soaringcosts, landshortage,andanincreasinglyglobalfoodsupply-demand.…”

Section: Artificial Intelligencementioning

confidence: 99%

Food Sustainability, Cyber-Biosecurity, Emerging Technologies, and Cybersecurity Risks in the Agriculture and Food Industries

Nobles

Burrell

Waller

et al. 2022

International Journal of Environmental Sustainability and Green Technologies

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The United Nations forecasts that by 2050, the world's population will reach 9.8 billion and 11.2 billion in 2100. An ever-growing global population threatens food security, accompanied by an increasing food shortage and relentless cybersecurity attacks. Agriculture 4.0, smart farming, and precision farming are essential to provide the technological breakthroughs to increase agricultural production while simultaneously expanding cybersecurity risks in the agriculture and food industries. With a global cybersecurity talent shortage and increasing cyber-attacks on the agriculture and food industries, there is a dire need to address cybersecurity solutions for the agriculture and food industries. A developing area in agriculture is cyberbiosecurity, an integrated concept of biosecurity and cybersecurity underline the need to safeguard systems, humans, animals, and plants from biological mischiefs, such as bioterrorism, environmental terrorism, infections, plagues, and pandemics. This paper explores these complex dynamics through an exploration of current and emerging literature.

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“…In fact, one of climate change's impacts is the reduction of the occurrence of precipitation, and when it occurs, it happens with very high intensity and time concentration [16]. To cope with this issue, agriculture requires the development of new techniques and management practices [17], such as so-called dryland farming or dry farming [18], a production without irrigation in dry seasons, especially in regions receiving a maximum of 50 cm of rainfall in a year [19]. Surprisingly, drylands are also common in developed countries, characterised by an increased risk of desertification [20].…”

Section: Introductionmentioning

confidence: 99%

Climate Change and Natural Resource Scarcity: A Literature Review on Dry Farming

Santo

Russo

Sisto

2022

Land

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The agricultural sector is facing the challenge of climate change, which is increasing difficulties to the activity and the economic sustainability of the primary sector, also affecting farmers’ revenues. There is a growing need to support policy makers’ decisions and help them develop cross-sectional strategies to support farmers. To this aim and to collect useful information for policy makers and stakeholders for the development of efficient strategies for the management of dryland farming, the paper examines how this issue has been analysed in the literature. A mixed method, based on a systematic literature review and a bibliometric analysis of 79 Scopus documents using VOSviewer software, was applied. Major results highlight the need to implement participatory policy interventions so as to include farmers. It was possible to summarise the main adaptive and technical interventions implemented by farmers. The results indicated the importance of the concept of the resilience of territories and the need to analyse agricultural systems by considering their multifunctionality. The innovativeness of this study relies on its relationships with several policy aspects and not only with purely technical and agronomical features, analysing thus the issue from the under-investigated perspective of the global challenge, contributing to filling this literature gap.

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Emerging Technologies in Agriculture

Cited by 13 publications

References 7 publications

Integration of Blockchain and AI: Exploring Application in the Digital Business

Integration of Blockchain and AI: Exploring Application in the Digital Business

Food Sustainability, Cyber-Biosecurity, Emerging Technologies, and Cybersecurity Risks in the Agriculture and Food Industries

Climate Change and Natural Resource Scarcity: A Literature Review on Dry Farming

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