Artificial Intelligence and IoT based Monitoring of Poultry Health: A Review

Singh, Maninder; Kumar, Rajeev; Tandon, Dinesh; Sood, Pallavi; Sharma, Manish

doi:10.1109/comnetsat50391.2020.9328930

Cited by 27 publications

(9 citation statements)

References 16 publications

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“…The human intelligence and simulation processes include speech recognition, visual perception, natural language processing, and decision-making according to perceived data. 191,192 For the AI system's growth, two parameters are necessary: the metadata available from various health records and the enhancement of the processing power of computers. These two aspects of AI inevitably combine with complicated mathematical algorithms, neural networks (NN), and machine/ deep learning.…”

Section: Role Of Artificial Intelligence (Ai) and Internet Of Things ...mentioning

confidence: 99%

Current advancement in nanomaterial-based emerging techniques for the determination of aminoglycosides antibiotics for antibiotic resistance surveillances

Sajwan,

Hashmi,

Himanshu

et al. 2024

Mater. Adv.

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Section: Role Of Artificial Intelligence (Ai) and Internet Of Things ...mentioning

confidence: 99%

Current advancement in nanomaterial-based emerging techniques for the determination of aminoglycosides antibiotics for antibiotic resistance surveillances

Sajwan,

Hashmi,

Himanshu

et al. 2024

Mater. Adv.

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“…The MV and intelligent automation have enabled the meat and egg processing sector to increase the rate of processing and packing (Chowdhury & Morey, 2020; Innocente et al., 2009; Kamruzzaman, 2023). Spectral imaging devices driven by AI have been successfully shown to increase in multiple studies in terms of increased efficiency, improved quality control, reduced costs, and enhanced safety (Debauche et al., 2020; Puertas & Vázquez, 2020; Singh et al., 2020; Soltani et al., 2015; Wieme et al., 2022).…”

Section: Application Of I40 Technologies In the Egg Industrymentioning

confidence: 99%

“…An AI-based innovative poultry farm is shown in Figure 6. The introduction of AI is a four-step process that has become less complicated due to the invention of accurate sensing, internet access, and cloud-based services (Debauche et al, 2020;Devagiri et al, 2022;Singh et al, 2020). The first stage is automated data collecting using accurate sensors throughout the industry.…”

Section: Ai Iot and Cloud Computingmentioning

confidence: 99%

“…Spectral imaging devices driven by AI have been successfully shown to increase in multiple studies in terms of increased efficiency, improved F I G U R E 7 An artificial intelligence-based cloud computing system for the smart egg industry: transfer of sensing data into a data center-machine learning of data and transfer to the consumer using an app server-end-user quality check to help with purchasing decision. quality control, reduced costs, and enhanced safety (Debauche et al, 2020;Puertas & Vázquez, 2020;Singh et al, 2020;Wieme et al, 2022).…”

Section: Ai Iot and Cloud Computingmentioning

confidence: 99%

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Non‐destructive optical sensing technologies for advancing the egg industry toward Industry 4.0: A review

Ahmed,

Hossainy,

Khaliduzzaman

et al. 2023

Comp Rev Food Sci Food Safe

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

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“…Recent digital advances in sensor technology, sensor networks with The Internet of Things (IoT) connectivity, remote sensing, computer vision and AI for agricultural and human-based applications have allowed the potential automation and integration of different animal science and animal welfare assessment approaches (Morota et al, 2018;Singh et al, 2020). There has been increasing research on implementing these new and emerging digital technologies and adaption to livestock monitoring, such as minimal contact sensor technology, digital collars and remote sensing (Karthick et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

The livestock farming digital transformation: implementation of new and emerging technologies using artificial intelligence

Fuentes

Viejo

Tongson

et al. 2022

Anim. Health. Res. Rev.

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Livestock welfare assessment helps monitor animal health status to maintain productivity, identify injuries and stress, and avoid deterioration. It has also become an important marketing strategy since it increases consumer pressure for a more humane transformation in animal treatment. Common visual welfare practices by professionals and veterinarians may be subjective and cost-prohibitive, requiring trained personnel. Recent advances in remote sensing, computer vision, and artificial intelligence (AI) have helped developing new and emerging technologies for livestock biometrics to extract key physiological parameters associated with animal welfare. This review discusses the livestock farming digital transformation by describing (i) biometric techniques for health and welfare assessment, (ii) livestock identification for traceability and (iii) machine and deep learning application in livestock to address complex problems. This review also includes a critical assessment of these topics and research done so far, proposing future steps for the deployment of AI models in commercial farms. Most studies focused on model development without applications or deployment for the industry. Furthermore, reported biometric methods, accuracy, and machine learning approaches presented some inconsistencies that hinder validation. Therefore, it is required to develop more efficient, non-contact and reliable methods based on AI to assess livestock health, welfare, and productivity.

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Artificial Intelligence and IoT based Monitoring of Poultry Health: A Review

Cited by 27 publications

References 16 publications

Current advancement in nanomaterial-based emerging techniques for the determination of aminoglycosides antibiotics for antibiotic resistance surveillances

Current advancement in nanomaterial-based emerging techniques for the determination of aminoglycosides antibiotics for antibiotic resistance surveillances

Non‐destructive optical sensing technologies for advancing the egg industry toward Industry 4.0: A review

The livestock farming digital transformation: implementation of new and emerging technologies using artificial intelligence

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