Big Data: Food & Beverage Meets the IIoT
Most people are aware that “IoT” refers to Internet of Things. Put simply, the IoT is “the interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data.” It is essentially a system of interrelated computers, mechanical and digital machines provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. (Thank you, Merriam-Webster.)
However, there is another buzzword/acronym being used more and more: the Industrial Internet of Things, or the IIoT.
The IIoT, while obviously related to the IoT, refers to the extension and use of the IoT in industrial sectors and applications. With a strong focus on machine-to-machine communication, big data, and machine learning, the IIoT enables industries and enterprises to have better efficiency and reliability in all their operations. The IIoT nowadays can encompass many industrial applications—such as robotics, medical devices, and software-defined production processes.
According to a definition in Trend Micro, the IIoT goes “far beyond normal consumer devices and the internal networking of physical devices usually associated with the IoT.” What makes the IIoT different from the IoT is the intersection of information technology (IT) and operational technology (OT). The OT refers to the networking of operational processes and industrial control systems. This includes human-machine interfaces, supervisory control and data acquisition systems, distributed control systems, and programmable logic controllers.
The convergence of IT and OT provides industries, including the Food & Beverage industry, with greater system integration—both in terms of automation and optimization, and better visibility of the company’s supply chain and logistics management. The IIoT makes it easier for a company to monitor and control the physical infrastructure of its industrial operations—all made easier via the use of smart sensors, remote access and control, and actuators.
F&B and Evolving Technologies
Despite rapid industrial growth in the F&B industry, there are still some problems with emerging market trends and evolving tech applications and their integrations. This can intensify market competition and squeeze revenues. A Feb. 2020 article from SoulPage suggests that, since AI and automation technologies are at the core of every modern business, “the integration of big data and data science technologies can solve 90% of the problems faced by the food and beverage industry.”
The article names five important ways big data (a more conversation-friendly way to say the IIoT) can help transform the F&B industry. They include transparency in the supply chain; a value-added production and delivery system; the ability to predict product shelf-life; optimizing marketing and branding; and something termed “sentiment analysis.”
Sentiment analysis can help improve customer services that “further enhance the customer satisfaction after consuming the end product,” according to SoulPage. Sentiment analysis is the tabulation of data available on digital and non-digital platforms. It is used to drive insights from customer reviews, complaints, and info gathered from such tools as surveys or rating systems.
“Sentiment analysis helps in understanding the customer behavior patterns that can help in improving existing business operations. The Food & Beverage industries, by leveraging data analytics, NLP, and text-mining tools, can quickly predict the customer’s satisfactory views at different nodes of the customer life-cycle for offering better products and services,” states the SoulPage, Feb. 2020 article.
Crises in F&B
No company wants to face the crisis of a product or ingredient recall—or, as every person on the planet is seeing in 2020—having to manage during a global pandemic. COVID-19 has upended every aspect of working life, especially for those involved in the essential F&B industry.
Cority is a company that provides environmental, health & safety, and quality management (EHSQ) software solutions across multiple industries—including F&B and pharmaceuticals. Sean Baldry, CRSP, Product Marketing Manager, Safety & Health Solutions at Cority, discussed ways big data analytical tools can be used to help in multiple ways in the food & beverage industry.
Take, for example, the idea of traceability (as in the cases of a large recall or a virus outbreak). Baldry averred that developing any crisis management plan requires participation from key internal stakeholders, i.e., management and workers, and coordination with local/regional agencies. Such coordination will ensure that the organization relies on information from a single, credible source, which will improve decision-making.
Baldry states, “Ultimately, I think it’s important that organizations remain flexible and that their response plans remain adaptable to changing conditions. If decisions need to be made to reduce and/or scale down operations, these decisions should be made based on credible data and through open, transparent discussions with key stakeholders, so there is consistent communication—and so rumors do not create unnecessary anxiety.”
Traceability is also key in crisis management. One of the most encouraging ways that big data analytics can help organizations manage their pandemic response effort, for example, is through the emergence of predictive analytical modeling. Baldry says, “Analytical modeling tools in EHSQ software solutions are growing at an exponential rate. And, with predictive modeling software, organizations are able to feed their historical data into machine-learning algorithms. This predictive modeling can be used to create a prediction of where infection “hot spots” are, for example, in the current pandemic. The same predictive analysis can be applied to a product recall, as well, in a similar way.”
It’s in everyone’s best interests to work toward devising solutions in an efficient, timely manner. The F&B industry can benefit from data science technology that can interpret data in a way that optimizes all aspects and functions within an individual operation or business.
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