Introduction

Artificial Intelligence (AI) is a cutting-edge development in computer science. It has the potential to tackle complex things in the modern world of agriculture and food sector. Combining AI techniques and these systems can create unique and dynamic solutions to address various challenges that include rapid population growth, diminishing natural resources, climate change and shrinking agricultural lands. From improving the productivity of crop yields to resource management and reducing waste, etc., all things can be automated and enhanced by Artificial Intelligence (AI). Finally, AI is a data processing framework as the data source and gets in touch with a prompt that is easy to understand.

Read: August 2023 Issue of Food Infotech Magazine.

Transforming Food Safety: The Impact of AI Robotics

Studies have revealed that using new-age technologies like AI robotics can increase productivity by about 70% in the agricultural sector. The Food and Refreshment Industry is growing rapidly by utilizing new innovations. The top players have been using Artificial Intelligence to retain their position in the Industry. New technologies include robots, augmented reality, virtual reality, three-dimensional printing, sensors, Machine Vision Systems, drones, blockchain, etc. They are altering the food industry, and among them, Artificial Intelligence is like the magic sauce of the food base of the industry. The arrival of COVID-19 pandemic has increased the applications of AI in all sectors, including food and agriculture rapidly.

Sorting

In the Food Industry, sorting food items is crucial since it requires higher attention to detail like size, colour, etc. Further, based on sorting, companies decide how to process various food items, contributing to consumer satisfaction and purchase rates.

One of the most popular and top companies in this field is TOMRA. TOMRA is a company that specializes in the sorting of food products. By using AI technologies, TOMRA has developed advanced machines that enhance the process of sorting food items. These cutting-edge systems are equipped with sensors and take advantage of the features like cameras and near-infrared sensors to visualize food products with precision similar to human perception.

By integrating new techniques of Artificial Intelligence (AI) and sensor-based technologies, TOMRA’s sorting machines can perfectly analyze the size, shape and colour of food items, enabling them to distinguish between various types of quality grades and classes. This capability allows food companies to optimize production processes and ensure that only high-quality and uniform products reach the market. As a result, consumers are more likely to be satisfied with the food they purchase, leading to increased brand loyalty and higher purchase rates.

The use of Artificial Intelligence (AI) in food sorting brings many benefits to the industry. Firstly, it enhances efficiency, as the machines can rapidly and accurately process a large volume of food items, reducing the need for manual labour and potential human errors. Secondly, it helps minimize food waste by precisely identifying and separating products that do not meet the required quality standards, thereby reducing unnecessary discard. Additionally, AI-powered sorting systems can improve food safety by identifying and removing contaminated or potentially harmful items from the production line.

Food Factory - Cold Storage

Adopting AI-driven sorting technologies in the Food Industry, exemplified by TOMRA’s innovative solutions represents a significant step forward in achieving higher productivity, waste reduction and better food safety standards by effectively reducing major costs. As more companies recognize the potential of Artificial Intelligence and invest in such advanced sorting systems, the Food Industry can further elevate its efficiency and ensure that consumers receive products of the highest quality, meeting their expectations and driving their growth in the market.

The algorithm behind the AI-based Robot system used for sorting the quality of Tomato.

The complete process of sorting of quality of tomato is at this moment described in five steps, which are as under:
Step 1 – Capturing the image and its softness value

Here, the robot uses an imaging system to capture an image and measure each tomato’s softness (firmness) value; it is an essential parameter to determine its ripeness and suitability for sorting.

Step 2 – Using Image Processing Techniques, predict the type of tomato

The captured image is then processed by Artificial Intelligence (AI) techniques like Deep Learning and Computer Vision Algorithms. It analyzes the tomato’s visual features and classifies it into a specific class based on its shape, size, etc.

Step 3 – Confirming the prediction of AI

This step is being done to cross-verify the prediction of tomatoes made by the AI model.

Step 4 – Discarding the damaged tomatoes

The robot examines the tomato and if there are any signs of damage, it is picked up and discarded.

Step 5 – If the tomato is ripened, pick it or else leave it

Suppose the tomato has been ripened properly and ready for consumption, the robot picks it up carefully and places it in a proper storage container.

The algorithm combines image analysis, AI-based classification and firmness evaluation to efficiently sort out tomatoes based on the abovementioned parameters. This process is efficient and reduces the chances of human error.

The Intervention of AI in the Food Supply Chain

The intervention of AI in Food Supply Chain Management has brought about a transformative revolution in the Industry, addressing critical challenges and improving overall efficiency, transparency and sustainability. AI’s advanced capabilities, including data analytics, Machine Learning Algorithms and predictive modelling have optimized supply chain operations. By analyzing large volumes of data, AI-driven systems identify patterns and inefficiencies, streamline processes, reduce costs and eliminate bottlenecks. AI optimizes routing, scheduling and resource allocation from procurement to distribution, resulting in a faster and more cost-effective supply chain processes.

Transparency and traceability have become essential for consumer trust. AI enables end-to-end product tracing, tracking the journey of food products from origin to the consumer’s hands. This level of transparency ensures product authenticity and supports ethical sourcing practices. Accurate demand forecasting is crucial for minimizing food waste and maintaining optimal inventory levels. AI’s predictive analytics analyze historical data and market trends to generate precise demand forecasts. This empowers businesses to make informed decisions regarding production and distribution, avoiding overstocking or stockouts. AI’s intervention also contributes to sustainability efforts. By optimizing energy consumption and transportation routes, AI promotes eco-friendly practices. Reduced energy usage and greenhouse gas emissions benefit the environment and improve operational efficiency. Risk management and supply chain resilience are enhanced through AI’s predictive capabilities. AI-powered analytics identify potential risks and disruptions, enabling proactive risk mitigation strategies. This ensures a more robust supply chain that can adapt to unexpected events.

Quality control and food safety are critical in the Food Industry. AI-powered sensors and vision systems automate inspections, identifying defects and contamination. This ensures that only high-quality products reach consumers, enhancing food safety and reducing the risk of foodborne illnesses. As AI technology advances, its integration in food supply chain management promises further advancements. Embracing AI-driven solutions empowers companies to meet evolving consumer demands and drive sustainability, ensuring a resilient and competitive supply chain.

Personalized Customer Service

Personalized customer service in the Food Industry, with the intervention of AI has ushered in a new era of enhanced customer experiences and brand loyalty. AI’s advanced capabilities, particularly in Natural Language Processing (NLP) and predictive analytics, have revolutionized how companies interact with customers and cater to their unique preferences and needs. One of the most significant benefits of AI-driven personalized customer service is the ability to provide tailored recommendations and suggestions to individual customers. AI algorithms can understand each customer’s tastes and preferences by analyzing vast amounts of customer data, including purchase history, preferences and behaviour. This enables companies to offer personalized product recommendations, special offers and promotions that resonate with individual consumers, increasing the likelihood of repeat business.

AI-powered virtual assistants and chatbots play a crucial role in personalized customer service. NLP technology allows these AI-driven interfaces to interact with customers naturally and conversationally. Customers can ask questions, seek recommendations and resolve issues seamlessly, enhancing their overall shopping experience. These virtual assistants can also provide real-time support, allowing companies to engage with customers 24/7 and address their queries promptly. The power of AI-driven insights goes beyond simple recommendations. Companies can use predictive analytics to anticipate customer needs and behaviour. AI can predict customer preferences, upcoming trends and potential demands by analyzing historical data and identifying patterns. This enables businesses to proactively adapt their product offerings and marketing strategies to stay ahead and improve customer satisfaction.

Moreover, AI empowers companies to engage with customers across multiple channels, including social media, email and websites. Companies can gauge customer feedback and sentiment through AI-powered sentiment analysis, understanding how customers perceive their products and services. This information allows companies to respond to customer feedback promptly and address any issues, further enhancing customer satisfaction and loyalty. The intervention of AI in personalized customer service also enables companies to gain a deeper understanding of their target audience. By segmenting customers based on their preferences and behaviour, companies can develop targeted marketing campaigns that resonate with specific customer groups. This level of personalization fosters a sense of connection and loyalty among customers, leading to increased brand advocacy and word-of-mouth referrals.

However, it is essential to balance AI-driven personalization and customer privacy. Customers must feel comfortable sharing their data, knowing it will be used responsibly and ethically. Transparent data policies and clear communication regarding data usage are crucial to building customer trust.

Challenges of Artificial Intelligence and Available Solutions

Undoubtedly AI has marked certain advancements in the food industry, but it also has challenges. The challenges with AI are financial investment requirements and convincing stakeholders.

On the other hand, companies lacking the resources to build-in house solutions to the problems can seek out food and beverage solution providers that already offer well-established AI systems. These providers can provide front-end and back-end AI solutions that improve various processes within the company.

As the Food Industry continues to evolve, the integration of AI becomes increasingly essential for companies seeking to remain competitive. By combining different aspects of AI and predictive analytics, the potential for innovation and improved food production and distribution efficiency becomes limitless. Embracing AI technology is not just a trend; it has become a strategic imperative for food companies aiming to thrive in the fast-paced and dynamic market.

Conclusion:

Artificial Intelligence (AI) is a transformative game-changer in the Food Industry, providing innovative solutions to complex challenges. It revolutionizes various aspects of food production, supply chain management and customer service, improving productivity, resource management and waste reduction while addressing critical issues like rapid population growth and climate change. AI-powered systems, such as robotics and predictive analytics enhance sorting processes, ensuring high-quality products reach consumers, driving brand loyalty.

Leading companies like TOMRA showcase AI’s immense potential, empowering others to follow suit and meet consumer demands. However, integrating AI presents challenges like implementation costs and stakeholder buy-in. Companies without resources can turn to established solution providers for ready-to-use AI solutions. As AI technology advances, its applications in the Food Industry are expected to expand further, driving competitiveness and success.

Adopting Artificial Intelligence (AI) in the food industry is a transformative step, achieving higher productivity, food safety standards and cost-effectiveness. AI’s innovative solutions revolutionize food production, supply chain management and customer service, addressing challenges like population growth and limited agricultural lands. With robotics and predictive analytics enhancing sorting processes, high-quality products reach consumers driving brand loyalty. Leading companies like TOMRA demonstrate AI’s potential, inspiring others to revolutionize their operations. Yet, challenges exist in AI integration, including implementation costs and stakeholder buy-in. However, ready-to-use AI solutions from established providers offer alternatives. As AI technology advances, it will expand further, empowering companies to meet evolving consumer demands and stay competitive.

References:

1. Sahni, V., Srivastava, S., & Khan, R. (2021). Modelling Techniques to Improve the Quality of Food Using Artificial Intelligence. Academic Editor: Alessandra Durazzo. Volume 2021, Article ID 2140010. Open Access.
https://doi.org/10.1155/2021/2140010.

2. Yang, M., Kumar, P., Bhola, J., et al. (2022). Development of image recognition software based on artificial intelligence algorithm for the efficient sorting of apple fruit. International Journal of Systems Assurance Engineering and Management, 13(Suppl 1), 322–330. https://doi.org/10.1007/s13198-021-01415-1.

3. Chen, L., Li, Y., Zhang, J., & Chen, F. (2020). Application of AI technology in the food industry: A review. Frontiers in Nutrition, 7, 162. doi: 10.3389/fnut.2020.00162.

4. Talavera-Garcia, R., & Ruiz-Real, J. L. (2021). The role of artificial intelligence in the food supply chain: A systematic literature review. Sustainability, 13(7), 3819. doi: 10.3390/su13073819.

About the Authors:

Authors - Kushagra Agrawal & Nisharg Nargund

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Author

An editor by day & dreamer at night; passionately involved with both print and digital media; Pet lover; Solo traveller.

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