Smart agriculture: a literature review DOI
Disha Garg, Mansaf Alam

Journal of Management Analytics, Год журнала: 2023, Номер 10(2), С. 359 - 415

Опубликована: Апрель 3, 2023

Industry 4.0 brings revolutionary changes to farming businesses by integrating emerging technologies such as the Internet of things (IoT), big data analytics (BDA), cloud computing (CC), and artificial intelligence (AI). These Emerging are potential enablers data-driven smart farming. Realizing importance agriculture, we provide a complete picture current literature in agriculture using review classification framework divided into four categories: (i) Smart Farming Activities, (ii) BDA Levels, (iii) Models, (iv) Techniques. This work uses preferred reporting items for systematic reviews (PRISMA) methodology on intelligent A total 90 papers have been identified, content analysis was conducted mine knowledge domain 2011–2022. The primary intention this is clarify most prominent activity, level analytics, models, techniques Finally, findings our discussed, suggestions addressed further research.

Язык: Английский

Recent advances in environmental and agricultural applications of hydrochars: A review DOI

Maryam Nawfal Mahmood Al-Nuaimy,

Nangyallai Azizi, Yahya Nural

и другие.

Environmental Research, Год журнала: 2023, Номер 250, С. 117923 - 117923

Опубликована: Дек. 16, 2023

Язык: Английский

Процитировано

35

Non‐destructive optical sensing technologies for advancing the egg industry toward Industry 4.0: A review DOI Creative Commons
Md Wadud Ahmed,

Sahir Junaid Hossainy,

Alin Khaliduzzaman

и другие.

Comprehensive Reviews in Food Science and Food Safety, Год журнала: 2023, Номер 22(6), С. 4378 - 4403

Опубликована: Авг. 21, 2023

Abstract The egg is considered one of the best sources dietary protein, and has an important role in human growth development. With increase world's population, per capita consumption also increasing. Ground‐breaking technological developments have led to numerous inventions like Internet Things (IoT), various optical sensors, robotics, artificial intelligence (AI), big data, cloud computing, transforming conventional industry into a smart sustainable industry, known as Egg Industry 4.0 (EI 4.0). EI concept potential improve automation, enhance biosecurity, promote safeguarding animal welfare, intelligent grading quality inspection, efficiency. For transformation, it analyze available technologies, latest research, existing limitations, prospects. This review examines non‐destructive sensing technologies for industry. It provides information insights on different components 4.0, including emerging production, grading. Furthermore, drawbacks current workarounds, future trends were critically analyzed. can help policymakers, industrialists, academicians better understand integration automation. productivity, control, optimize resource management toward development

Язык: Английский

Процитировано

34

A comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produce DOI Creative Commons
Guduru Dhanush, Narendra Khatri, Sandeep Kumar

и другие.

Scientific African, Год журнала: 2023, Номер 21, С. e01798 - e01798

Опубликована: Июль 7, 2023

Every nation's economic development depends heavily on agriculture. Fulfilling the current population's need for food is becoming increasingly difficult because of factors including population growth, frequent climate change, and a lack resources. However, agriculture sector's biggest problems are trained workers, urbanization, available labour. Automation in essential to provide food, fibre, fuels rapidly growing population. Since harvesting critical step farming, authors present systematic review machine vision systems artificial intelligence algorithms detecting agricultural produce this article. The areas that being concentrated include systems, sensors, different image processing utilized detection harvesting. Review various types sensors used automated It demonstrates how several 3D methods, which were obtain position, orientation, point cloud fruit or crop, function compare them. Furthermore, it compares deployed precision This article shows knowledge-based can boost quality.

Язык: Английский

Процитировано

30

Cyber-agricultural systems for crop breeding and sustainable production DOI Creative Commons
Soumik Sarkar, Baskar Ganapathysubramanian, Arti Singh

и другие.

Trends in Plant Science, Год журнала: 2023, Номер 29(2), С. 130 - 149

Опубликована: Авг. 28, 2023

The cyber-agricultural system (CAS) represents an overarching framework of agriculture that leverages recent advances in ubiquitous sensing, artificial intelligence, smart actuators, and scalable cyberinfrastructure (CI) both breeding production agriculture. We discuss the progress perspective three fundamental components CAS - modeling, actuation emerging concept agricultural digital twins (DTs). also how CI is becoming a key enabler In this review we shed light on significance revolutionizing crop by enhancing efficiency, productivity, sustainability, resilience to changing climate. Finally, identify underexplored promising future directions for research development.

Язык: Английский

Процитировано

29

Smart agriculture: a literature review DOI
Disha Garg, Mansaf Alam

Journal of Management Analytics, Год журнала: 2023, Номер 10(2), С. 359 - 415

Опубликована: Апрель 3, 2023

Industry 4.0 brings revolutionary changes to farming businesses by integrating emerging technologies such as the Internet of things (IoT), big data analytics (BDA), cloud computing (CC), and artificial intelligence (AI). These Emerging are potential enablers data-driven smart farming. Realizing importance agriculture, we provide a complete picture current literature in agriculture using review classification framework divided into four categories: (i) Smart Farming Activities, (ii) BDA Levels, (iii) Models, (iv) Techniques. This work uses preferred reporting items for systematic reviews (PRISMA) methodology on intelligent A total 90 papers have been identified, content analysis was conducted mine knowledge domain 2011–2022. The primary intention this is clarify most prominent activity, level analytics, models, techniques Finally, findings our discussed, suggestions addressed further research.

Язык: Английский

Процитировано

28