Food Safety is Everyone’s Business

In this post, we'll explore how AI in food manufacturing is helping safety professionals combat foodborne diseases and improve production efficiency.

aiOla Team

1.12.2022

Food safety: A major challenge at a global scale

According to the World Health Organization, approximately 600 million people fall ill after eating contaminated food — that’s almost 1 in every 10 people on the entire planet. Yearly deaths from contaminated food total around 420,000, resulting in a total loss of 33 million years of healthy life.

But perhaps the most damning statistic of all is that a huge percentage of the foodborne disease burden is carried by children under the age of 5, whose 125,000 deaths per year account for 40% of the total.

In other words, food safety is everyone’s business.

A fast-growing market that shows no signs of slowing down

Given the global nature of the challenge of contaminated food, it’ll come as no surprise to learn that the market for food safety testing has been growing steadily. In 2021, it was estimated at $20.73 billion. Forecasts predict a CAGR of 7.4% from 2021 to 2028, which would value the market by that point at a staggering $34.14 billion.

A significant reason behind this prolonged year-on-year growth is the sheer impact of unsafe food on the global economy, with low- and middle-income economies (LMICs) being particularly affected. According to estimates from the world bank, the cost is approximately $110 billion a year in both lost productivity and medical expenses.

In reality, the total figure is almost certainly significantly higher once you factor in elements such as lost trade income, the knock-on medical effects of consumers avoiding perishable foods, and the environmental challenges posed by food waste.

The same study, which was supported by the USFDA, found evidence to suggest some of these costs could be avoided by making key infrastructure changes throughout the food value chain.

Investments related to hardware (like labs and marketplaces) as well as software (such as human capital and digital management systems) could play an important role in mitigating the economic hardship experienced by Low and Low Middle Income Countries (LMICs). To be truly effective, however, any manufacturing optimization made must take into account the context of the current regulatory environment.

The role played by regulations

Two main regulatory systems aim to ensure the safety of food, chemicals, and pharmaceuticals: GMP and HACCP.

GMP is a series of principles that must be fulfilled before a product can be considered to meet basic legal standards for safety and quality. Often thought of as the “first step” to food safety, GMP can be considered to be one of the core components of HACCP.

HACCP is a broader, more systematic approach to food production that is designed with one key goal in mind — preventing hazards from occurring. Although it began with the food industry, HACCP is increasingly being applied to non-food industries like cosmetics and the pharmaceutical industry.

Tackling the problem with regulation-compliant technology

AI has an interesting role to play with regard to both GMP and HACCP. Recent technological advances have resulted in the widespread proliferation of virtual food safety assistants, which are fully interactive AI models designed to help food safety professionals throughout the course of their day-to-day activities.

Because they’re capable of boosting production line efficiency by accomplishing tasks like product recalls and process monitoring, these virtual assistants have proven to be highly useful to food safety professionals. This has led to their increased use as a means of manufacturing optimization across facilities that are implementing HACCP plans.

Perhaps most impressively of all, some virtual food assistants can even contribute to creating HACCP plans or altering existing plans in a fraction of the time it would usually take. And with studies demonstrating that manual inspection is only correct about 80% of the time, deploying artificial manufacturing intelligence in production environments has the potential to radically improve results by cutting down on unnecessary errors.

The intersection of technology and food safety comes at a vital time for the world as well. The FAO predicts that food production will need to increase by 70% by 2050 in order to meet increased demand, while the United Nations Sustainable Development Goals estimate that food wastage could be decreased by as much as 30% with help from using AI in manufacturing environments worldwide.

With more food required than ever and strictly manual processes incurring a significant error rate, it’s clear that technological innovation should be a matter of priority for the global food safety industry.

Bridging the gap between AI and the factory floor

aiOla is applying the most advanced proprietary technologies in AI, ASR & NLP to solve everyday problems, for any user, regardless of their technical skills or capabilities.

aiOla is capturing natural communication (voice, text, and visuals) for existing critical processes in numerous languages in any accent or industry jargon. Our solution creates instant and lasting impact in a wide range of industries and verticals from Food Safety, to Financial Services and to Compliance Challenges in general.

Most data available in the food industry is unstructured by nature. aiOla’s ability to process that data allows factory owners to not only improve efficiency and safety but also minimize waste, positively impacting sustainability in the process.

Because aiOla processes spoken input using NLU (Natural Language Understanding) technology, it’s uniquely capable of analyzing unstructured data across most languages in every accent. Crucially, this analytical process can take place in near real-time, making it particularly effective in the real-world context of a production environment.

aiOla also positively impacts several other key aspects of the food inspection process. Its hands-free inspection capabilities, in addition to being significantly faster on its own, reduce the manual time needed to process paperwork by up to 75%. By freeing up the time of the food safety professionals, these factors lead to a significant knock-on increase in productivity across the board.

How aiOla could benefit the food safety industry

Hands-free inspection

By allowing food safety professionals to record information using spoken natural language, aiOla streamlines the workflow at the floor level and cuts down on errors that occur throughout the process of inspecting food at scale.

Knowledge gathering

aiOla’s collected food inspection data turns into a goldmine of raw manufacturing intelligence. aiOla can then analyze the information at a deep level, allowing the platform to spot trends before they even form and proactively contribute to smarter, more sustainable food safety processes.

AI-based detection and inspection

By automating the food inspection process, aiOla can reduce human error and increase productivity. It’s capable of providing auto-scoring calculations, prepopulating default values, and setting corrective actions for each type of safety defect, creating a more rigorous detection and inspection environment where almost nothing slips through the cracks. In the food industry, where mistakes can lead to people falling seriously ill, having such a high degree of precision is a crucial benefit for manufacturers as well as the population at large.

Real-time collaboration

Communication on the floor is an important part of any well-run food safety operation. aiOla allows inspectors to collaborate in real-time as they carry out their work, acting as a single source of truth around which the workers can coordinate their efforts and improve production line efficiency.

Learn more about aiOla

If you’d like to learn more about how aiOla works or the benefits it can produce for food safety processes, feel free to get in touch with our team or schedule a demo. We’d be happy to clear up any questions you may have or walk you through how the platform works.