Contemporary Research and Analysis of Food Industry: Case of Russian Restaurant Business Network Branch

Fainshtein, Elizaveta; Elena, Serova; Vorobyev, Pavel

doi:10.1007/978-3-030-65085-8_12

Cited by 3 publications

(1 citation statement)

References 40 publications

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“…Ooshma Garg, the founding father of Gobble, shared a thought that a food industry can be phrased as a tech company. It was a disputable assertion for the rest of the world, but there's some truth behind this [37,38]. Data science has become a prerequisite in current technology-driven industries for elevating and maneuvering their diverse business practices.…”

Section: Data Analysis At Food Industrymentioning

confidence: 99%

Opportunities of Artificial Intelligence and Machine Learning in the Food Industry

Kumar

Rawat

Mohd

et al. 2021

Journal of Food Quality

121

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The food processing and handling industry is the most significant business among the various manufacturing industries in the entire world that subsidize the highest employability. The human workforce plays an essential role in the smooth execution of the production and packaging of food products. Due to the involvement of humans, the food industries are failing to maintain the demand-supply chain and also lacking in food safety. To overcome these issues of food industries, industrial automation is the best possible solution. Automation is completely based on artificial intelligence (AI) or machine learning (ML) or deep learning (DL) algorithms. By using the AI-based system, food production and delivery processes can be efficiently handled and also enhance the operational competence. This article is going to explain the AI applications in the food industry which recommends a huge amount of capital saving with maximizing resource utilization by reducing human error. Artificial intelligence with data science can improve the quality of restaurants, cafes, online delivery food chains, hotels, and food outlets by increasing production utilizing different fitting algorithms for sales prediction. AI could significantly improve packaging, increasing shelf life, a combination of the menu by using AI algorithms, and food safety by making a more transparent supply chain management system. With the help of AI and ML, the future of food industries is completely based on smart farming, robotic farming, and drones.

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Section: Data Analysis At Food Industrymentioning

confidence: 99%

Opportunities of Artificial Intelligence and Machine Learning in the Food Industry

Kumar

Rawat

Mohd

et al. 2021

Journal of Food Quality

121

View full text Add to dashboard Cite

show abstract

Artificial Intelligence for Improving Food Quality

Sharma¹,

Singh²,

Kumar³

2022

Artificial Intelligence Applications in Agriculture and Food Quality Improvement

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There is no doubt about the fact that artificial intelligence (AI) has stepped into improving quality of food throughout the world. Artificial intelligence makes it possible to be done for machine to profit as a material or substance of fact examining facts from different data sources and make conclusions, and can perform most humanly tasks with more than the limits of act without any fault. Due to the interference of humans in the production and packaging of food product, there is lack in maintaining the demand supply chain and also in safety of food to prevail over these issues of food industry. Automation is the best possible solution. It wraps up an enormous amount of streaming data, often noted as “big data,” which brings fresh and new opportunities to watch agricultural and food processes. Besides sensors, big data from social media is becoming important for the food industry. During this review, the authors present a summary of artificial intelligence (AI) and its role in shaping further of agri-food systems.

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The Role of Machine Learning and Computer Vision in the Agri-Food Industry

Ravikumar¹

2022

Artificial Intelligence Applications in Agriculture and Food Quality Improvement

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The food industry has been unable to control the demand-supply cycle and has also fallen short on food safety due to human engagement. Food production and distribution activities may be controlled more efficiently while also improving operational competence using an artificial intelligence-based solution. The food industry's future is entirely reliant on drones and also witty and robotic farming, thanks to AI and machine learning. Smart farming (soil monitoring, pest monitoring, and fertilizer management), food processing (production, processing, marketing, and customer feedback), and food safety, among other topics, need a detailed evaluation of machine learning applications in the agrifood business. It is vital to monitor production lines to ensure that the manufacturing process and products fulfill the required quality standards. A plethora of data may now be created throughout the production process due to growing digitization.

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Contemporary Research and Analysis of Food Industry: Case of Russian Restaurant Business Network Branch

Cited by 3 publications

References 40 publications

Opportunities of Artificial Intelligence and Machine Learning in the Food Industry

Opportunities of Artificial Intelligence and Machine Learning in the Food Industry

Artificial Intelligence for Improving Food Quality

The Role of Machine Learning and Computer Vision in the Agri-Food Industry

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