Food industry automation

Data management systems, such as automated inventory management, could provide an automated system for managing a restaurant's food catalog. This process has traditionally been a manual process, and for most food delivery platforms and restaurants, remains a manual process. However, automating this process for restaurants, and grocery stores and convenience stores, can help these businesses participate in online marketplaces. A data management system can integrate the merchant data lifecycle, which includes the steps of getting a merchant on-boarded onto a platform, keeping their data updated over time, such as when prices change or marking items out of stock, and offboarding a business should that business decide to change a particular solution.

Without automation, each step in the merchant lifecycle involves various manual processes for platform companies to receive data from a large variety of sources and cleanse and transform it into structured data capable of being used on the platform. For restaurants, especially, the data is unstructured, which makes it harder to automate and continues to require a lot of manual effort to bring it into a platform system. A data management solution whichthat can take a granular approach to the data has a better chance of automating the service, and this system can communicate between the restaurant and the platform, and allow the platform to pick and use the data the platform prefers, while offering enough data to be used by multiple platforms for marketplaces.

A company like Woflow has developed an API to help structure this unstructured data, allowing restaurants to improve connectivity, transparency, and trust in the industry, to help sync onboarding tickets from CRMs or to deliver structured catalog data to benefit the entire food ecosystem and improve efficiencies. The system also uses models whichthat are consistently being developed to help automation within a system and remove humans from the data entry tasks to maintain such a platform.

Product information management (PIM) platforms work to handle product information in one source for all channels, which can help restaurants or grocery stores to maintain the quality of the data and the amount of data in a single place. This could include to change the data for different changes in expectations, such as for digitization and digital innovations; changes in consumer behavior and increased customer expectations; globalization, laws, rules, and restrictions; CSR and sustainability; demographic changes; health, allergies, and diseases; and big data and smart data.

These systems help food producers and sellers to develop a greater amount of data and attributes, such as new laws and regulations, changes in business models, and new innovations and technologies, to help with the complex process of producing and selling food. And this system can bring the information to recipients by channel to meet customer expectations and demands.

Many existing PIM tools do not cover the specific needs of the food industry, and are often found to lack the flexibility to handle regulatory standards and related key aspects of the industry. A lot of this data is typically unstructured and does not fit well into spreadsheets, which can often result in error-prone, time-wasting silos of departmental product data. However, these solutions can help food suppliers and restaurants maintain compliance with industry and government-mandated regulations for food ingredients, traceability, and allergen labeling with verified product information.

While grocers and grocery stores have various forms of possible automations, one of the earliest versions of that automation camcame in the development onof e-commerce with delivery for grocery stores. Although it has existed for longer, the COVID-19 pandemic accelerated the adoption of purchasing groceries online and having them delivered. This was similar to the same rapid adoption experienced by retail outlets during the SARS outbreak in 2003. E-commerce offers grocery stores a chance to provide new services, such as offering greater food safety, offering larger item baskets, offer greater or more collaboration between grocers and brands, offerand more payment options for users and createusers—creating a more competitive landscape for grocers. And for most of those stores, the infrastructure for e-commerce already exists, allowing for more development for grocery e-commerce.

Similar to e-commerce, another way for food processors and grocers to differentiate themselves is to offer meal preparation kits delivered to a consumersconsumer's front door. Similar to e-commerce, thisThis provides a consumer with a chance to either cook for themselves, or to purchase a partially prepared meal, online and have it delivered, and allows grocery stores and food processors to develop a new sales channel. These systems often rely on heavily automated software infrastructures where stock levels, specific meal preparation kits, and online stores for kits are managed. And, for those working to develop these services, there are several platforms whichthat help or act as that automated infrastructure.

When talking about automation in grocery stores, one of the more talked about developments is in the B2C store space, where e-commerce businesses such as Amazon or Wayfair develop brick-and-mortar establishments, other than warehouse spaces, for shoppers to go and shop products. For example, Amazon has piloted cashier-less, and almost people-less, supermarkets, where a user can scan in to the store with an Amazon account, pick out whatever items at the supermarket, and leave. And these stores, a concept also piloted with Amazon-owned Whole Foods, charge the user for the items, which are tracked using computer vision.

A similar experience has been the buy-online, pickup-in-store (BOPIS) model which has been used by supermarkets for longer than fully automated B2C experiences or the e-commerce. This increases the responsibilities of workers in outlets, rather than to warehouse workers, as often happens in an e-commerce model. However, the BOPIS model has proven to also be more inefficient for stock reasons, especially if a store clogs up retail space with staff collecting BOPIS orders. However, increased automation to the model could provide stores with better fulfillment capabilities, as the use of robotics could increase the collection options and reduce the likelihood of customers seeing items listed as "out-of-stock" or "replaced" and allow warehouses to handle specific demands faster.

Another growing trend in the automation of grocery stores, especially for stores working towards full automation, is the use of robots in the customer areas, rather than just in the warehouses. Robots have already been trialed for warehousing and stock areas in larger stores such as Amazon and Walmart, where thethey have been used to pick items or to move items from shelves to another robotic system capable of moving goods from one area to another. But these systems still require a larger amount of human labor. However, these systems have also grown in popularity due to the move towards delivery and BOPIS models, where more employee hours are spent on fulfilling orders, packing groceries, and delivering orders, rather than on the front endfront-end grocery work of talking to customers, cleaning possible spills, stocking retail shelves, and related duties.

A more common use of robotics in grocery stores has seenbeen using robots used for cleaning spills, cleaning floors, checking inventory, or directing customers. Most of these robotic systems are unable to perform multiple functions. Some examples include Marty, made by Badger Technologies, which is capable of alerting customers to spills in English and Spanish. Similarly, Tally, a robot manufactured by Simbe Robotics, has been used in Giant Eagle and Shnucks, to monitor shelves and alert workers to out-of-stock items or problems related to merchandise presentation or merchandise out of place. Tally takes a predefined route through a store and transmits the collected data to employees.

Restaurants have toyed with and developed AI and voice recognition systems for helping streamline incoming orders and enabling fast-casual restaurants to process drive-thru, phone-in, and kiosk-based orders without need for human labor. And this kind of technology can connect restaurant POS systems to provide the kitchen with the orders without assistance. This type of automation lends itself to the fast-casual restaurants' use of ordering kiosks or the use of mobile applications for order and pay. These different ordering systems provide different types of automation that remove several steps and interactions from the ordering experience and has seen. storesRestaurants likeincluding McDonald's and Shake Shack openhave opened some stores with kiosk ordering only.

At the same time, fast-casual restaurants have offered customers with mobile options for ordering and paying with the promise of reducing wait times and long lines, and allowing those customers to choose for either in-store, curbside, or drive-thru pickup options. And in the case of these online ordering portals, the fast-casual restaurants have an opportunity for using virtual assistants to assisthelp customers and, givegiving customersthem information about the menu, ingredients, store locations, and operating hours, if not offering further food suggestions and information about possible deals.

An example of this type of automation, paired with back-end automation, is Cafe X in San Francisco, which offers a fully-automated cashless specialty coffee experience with customers either paying ahead through a mobile application or paypaying on tablets at the kiosk. These kiosks pair the automated ordering system with automatic coffee machines capable of brewing americanos, espressos, cappuccinos, cortados, lattes, and flat whites while offering customers choicechoices of beans and milk types.

These point-of-sale systems, when adopted, have proven in many cases to be popular with customers, or have been assumed to be popular among customers. These systems are capable of assisting customers with the ordering process, often by giving them details on the flavors or spices used in a dish, showing them promotional material, and offering newly added items. And when these systems are offered through mobile application, they can further collect information about customer preferences and make recommendations based on those preferences. Further, these ordering systems can help restaurants deal with manpower shortages, customer engagements, and reducing inaccurateorder ordersaccuracy.

With the application of artificialArtificial intelligence or machine learning in the front-end systems, especially for fast-casual restaurants, provides a chance to embed the system for various purposes. This could include for customer feedback systems, which can engage with the customers, their food preferences, habits, and complaints, and collect and analyze related information to help food-service-based applications to secure more food orders from old as well as new customers, and to help secure customer loyalty. This feedback can be further used to remove loopholes and complaints from the applications, and help develop more fail-safe and reliable applications. This can include restaurant management frameworks, payment gateway applications, cloud-based big-data applications, and restaurant table booking platforms.

And for fine dining restaurants, where the use of kiosks or even table-side mobile applications or tablets could be considered to interfere with the dining experience, the POS system can have these AI systems built in. And, for using statistical analysis, these POS systems can be used to further predict the type of food being ordered, relevant inventories, and providingprovide predictions for stock levels and staffing levels depending on the type of day to reduce the burden on management decisions.

For front of housefront-of-house and reservation and table management, a table booking platform can provide automation through an online portal. This can free up waitstaff and restaurantsrestaurant hosts from answering phones and managing table bookings, and can further reduce the possibility of human-errorhuman error. Often this software ties into the POS or reservation management software used by a restaurant. And the reservation and table management software can further provide integrations with a POS or restaurant management system to provide better data for staffing and food preparation predictions.

In the kitchen, or the back of most restaurants, automation is focused on robotics and their possible use in kitchens. With further advancements in AI as well, these robotic systems can be more capable, and more capable of completing complex tasks. The use of robotics has been more successful in the fast-casual restaurant space, especially as more fine-dining establishments focus on more complex food and menu building. There has historically been reluctance to bring in robotics and automated systems into a kitchen as the cost of these technologies have been higher than employing relevant or related manpower. But, asAs the capabilities of robotics continue to increase, they become a more attractive possibility, but will be unlikely to be adopted until their productivity and lifetime or initial cost are considered to be lower than that of training and maintaining employees.

One example of using robots to make food has been used in Zume Pizza, in northern California, which has used pizza-making robots that are capable of handling low-skill repetitive tasks such as pressing dough, pressing,spreading sauce spreading, and placing pizzas into the oven. The restaurant uses predictive technology to guide production, and indicate both the volume and types of pizzas that will satisfy demand. As well, Zume Pizza allows customers to order online or via mobile application, while the pizza finishes cooking in transit in a specially designed delivery vehicle.

And usingUsing automation or robotics in the back-end of the restaurant also provides a chance to increase food handling safety and maintainingimprove compliance with safety standards, as well as offers a chance for increasing consistency in quality and the product delivered to the customer. However, even in scenarios such as Zume Pizza, human labor remains an important part of putting the final product together.

Back office automation can include various tasks whichthat are undertaken on a daily basis, including forecasting, production, vendor ordering, receiving, and scheduling. All of these tasks offer different chances for artificial intelligence anand automation to bring greater efficiency in these functions, and even work to provide restaurants with better plan purchasing, menus, and staffing. Often these systems can be integrated into the POS system and reservation management software to create a more integrated software system environment in the restaurant. This software can also help smaller restaurants manage social media accounts and reduce the amount of redundant social media posting.

Most restaurant management software is capable of integrating, if not offering already, product information management tools, data management tools, and can integrate with delivery platforms to create efficiencies and automated workflows for restaurants and reducing friction for customers.

With the increase of delivery services, restaurants have become similar to retail outlets in the early 2000s and the push towards e-commerce. Except, for restaurants, these delivery platforms operate as e-commerce marketplaces. Often a restaurant has its own website where it can include a recent menu, locations, and a phone number, but often will offer links for online food delivery to a participating platform, or platforms, and for bookings and reservations, similar instructions. This allows a restaurant to focus more on the product, and less on the software needed to bring customers into the building or to bring the food to the customer. As well, a delivery platform offers a chance for customers to discover a restaurant they otherwise might not discover.

Besides delivering already made food, some restaurants also offer meal kits where they, provideproviding a customer with the necessary ingredients to cook one of their recipes at home, or even provide a near-finished recipe that only requires the customer to finish, and the customer in turn receives a hot meal from the restaurant of their choice.

In any case of a restaurant offering delivery services, there are a variety of services and technologies that are automated to make the services work smoothly. One of the simplest of these technologies includes automated order processing, which means a restaurant does not have to check to see when or if a customer is placing an order, but are notified automatically. Further, this reduces possible mistakes of a manual ordering system. Furthermore, for some systems, this can capture sales order data where the order processing system can contain or refer to a businesses order processing system, and prevents the need for a company to constantly reenter information such as customer information or delivery locations. As well, the historical order data can be used by businesses for demand forecasting and provide better business decisions.

These delivery platforms and their automated order processing tend to offer restaurants a chance to track an order in real-time, regardless of where the customer places thereal order;time offerand automatic verification process for the ordering, and the data can be forwarded to the nearest applicable restaurant.

Food industry automation includes the use of software, sensors, advanced learning algorithms, and robotics to decrease the need for human labor in the food industry's supply chain, and to increase the efficiencies of the supply chain as well. This is a supply chain that begins with the growing of the food, to the processing and distribution of the food, to the warehousing and sale of food at grocery stores, and to the sale of food at restaurants. Many of these forms of automation can solve different challenges in the food industry, such as staffing, quality assurance, safety, and moving product, while providing SKU variety and related demand. However, the food industry, throughout the different points of the supply chain, is notoriously resistant to automation, although much of this has begun to change in the wake of the COVID-19 pandemic. Regardless of the sector of the food industry, automation offers a few generalized benefits:

Other than physical forms of automation, food processing software offers a software layer capable of uniting machine and production planning. This can automatically process orders to the production equipment and material consumption, with the number of produced items are further reported back to a producer's enterprise resource planning (ERP) system. Benefits of such a software system can include the following:

The ERP software provides a management tool for integrated applications for business process optimization. This software can offer an all-encompassing look at how a company and its employees are performing in different components of the business, in real time. For food-specific purposes, an ERP is designed to streamline processes unique to food and beverage manufacturing, and they offer an increased opportunity for automation, such as the monitoring and alerting to unique and perishable products, like shelf-life, safe ingredients, consistency, and product safety. These systems also help food and beverage companies adhere to labeling and packaging requirements, manage recipes, maintain product quality, and implement safety precautions.

AI and ML are both technologies that are almost buzzwords when it comes to any kind of automation. And accordingly, these technologies have been applied in various parts of the supply chain of the food industry. For food processing, AI can be used for either the proper ordering and packaging of food products, where AI can handle the task and reduce the chance of error. There have been some challenges of using AI-based sorting and packaging in food processing, based on the irregularities in shapes, color, and sizes of vegetables and fruits, although most of the time this can be accounted for with large amounts of data and proper training of the AI models and system.

The use of artificial intelligenceartificial intelligence and robotics in food processing offers a chance to decrease the number of foodstuff-related diseases. The Food Safety Modernization Act (FSMA) offers stricter hygiene rules applicable across a supply chan. Often the foods that do not require refrigeration, such as cereals, spices, and related food products, are the most prone to contamination. These had previously been one of the safer food products, but this has since changed, and AI has been suggested as a possible solution for the problem. Using robotics means a food processing plant can manage these foods without transferring possible illnesses carried by humans, and the maintenance of an AI system is easier and simpler than humans.

AutomationFood industry automation includes the use of software, sensors, advanced learning algorithms, and robotics to decrease the need for human labor in the food industriesindustry's supply chain, and to increase the efficiencies of the supply chain as well. This is a supply chain that begins with the growing of the food, to the processing and distribution of the food, to the warehousing and sale of food at grocery stores, and to the sale of food at restaurants. Many of these forms of automation can solve different challenges in the food industry, such as staffing, quality assurance, safety, and moving product, while providing SKU variety and related demand. However, the food industry, throughout the different points of the supply chain, is notoriously resistant to automation, although much of this has begun to change in the wake of the COVID-19 pandemic. Regardless of the sector of the food industry, automation offers a few generalized benefits, which include:

The production of food, or agricultureagriculture, and the distribution of food is the crucial first step of the food industry. And, toTo help modernize the field, industry leaders have invested a significant amount of money into robotics and automated technologies to improve efficiency and better meet the demands of the industry. A few critical areas of development of automated systems have included forinclude breeding, harvesting, fertilizing, and in irrigation. These solutions often focus on minimizing production costs while conserving fuel, water, and fertilizers, and they often provide efficiencies over previous technology while also replacing labor. And, as traditional farming techniques continue to be impacted by labor shortages, the ability to replace some of the labor with automated systems is crucial;, especially in regions where the labor shortages have come as a result of regulations around the COVID-19 pandemic, which have in. theseThese cases have further incentivized corporations to invest in and develop automated and robotic systems, such as driverless tractors and sprayers.

The management of food food wasteswaste in the growing, distributing, processing, and selling of food is an important place where the food supply chain can increase efficiencies. In a report published by the U.S. Department of Agriculture, it was found that food waste in the United StatesUnited States alone accountedaccounts for between 30 to 40 percent of the food supply. This estimate, which was also based on estimates from the USDA's Economic Research Service of 31 percent food loss at the retail and consumer level, corresponded to the approximately 133 billion pounds and around $161 billion worth of food consumed in 2010. AI has been proposed as one possible solution to these problems, by helping to identify and find solutions for food waste, ifand notby creating efficiencies prior to food production to limit overall waste. In the case wherein which food waste occurs, AI can help identify uses for the food waste, such as regenerative farming practices. Other possibleapplications benefitsof AI to food waste include the application of AI to food waste includesfollowing:

• Using itAI to understandgain an understanding of which microorganisms can boost fruit and vegetable development, and discoverdiscovering at which point and at what level of application can fertilizers can help or hinder
• Manufacturers canutilizing AI to acquire a ground examination to better understand what kind of soil deficiencies they may be dealing with
• A farm-based food supply chain can useusing computer vision to manage and examine each process to discover and resolve food waste points
• Using AI-based food tracking could alsoto allow for the sale of food, aheadinstead of it becoming waste

In food processing, automation can help reduce expenses in food processing plants, especially in an industry wherein which sacrificing quality in the product is not an answer for cutting costs or increasing margins. And, similarSimilar to other process industries, food processing companies are finding ways to improve productivity through the plant with use of various forms of automation. This can include different types of automated machinery, such as automated ovens, cutting and forming machines, sortation equipment, mixers and blending machines, filling equipment, wrapping equipment, and robotics whichthat be used in highly automated production lines. And automation has since become a necessity in the food industry to address the required levels of quality control, production speed, labor shortages, and overall profitability.

Other than physical forms of automation, food processing software offers a software layer capable of uniting machine and production planning. This can automatically process orders to the production equipment and material consumption with the number of produced items are further reported back to a producersproducer's enterprise resource planning (ERP) system. Benefits of such a software system can include the following:

The ERP software provides a management tool for integrated applications for business process optimization. This software can offer an all-encompassing look at how a company and its employees are performing in different components of the business, in real-timereal time. For food specificfood-specific purposes, an ERP is designed to streamline processes unique to food and beverage manufacturing, and they offer an increased opportunity for automation, such as the monitoring and alerting to unique and perishable products, like shelf-life, safe ingredients, consistency, and product safety. These systems also help food and beverage companies adhere to labeling and packaging requirements, manage recipes, maintain product quality, and implement safety precautions.

Using IoT, there are a myriad of solutions for automating and documenting food processing operations to help users meet different compliance and food safety requirements. In a food processing plant, using IoT can offer pathogen and contamination prevention. There are various apps and technologies whichthat can be used for warehouse inspection and maintenance; general inspection and compliance; quality, environment, and workplace safety management; control and visibility of critical operations; expiration date management software; non-toxic sanitizing for handheld devices.

The use of various connected sensors can help increase visibility into the transportation of goods, to better understand where food is coming from and where it is going, and offers traceability to help improve emergency planning and food defense to give customers a more transparent product. This can further include serial tracking tools; inventory management tools; layered process audits; quality assurance; supplier quality management; traceability and HACCP solutions; traceability and inventory management software for the food industry; process management software for batch and recipe/formulation-based manufacturing; invisible barcoding software, embeddable in everything, and supply chain managementsupply chain management and logistics elements; and transportation monitoring. This can all be used to ensure the quality of the product is maintained by tracing and promoting the safety of a product through its tracing.

IoT can also be used in a mitigation strategy against intentional adulteration. This can include different applications and systems to help keep facilities and food safe from intentional or widespread harm. Any strategy can include visitor management and data collection systems;, cloud-based integrated security and access control for multi-site locations; offer, mobile access with smartphone integration;, identity credential and access control for smartphones;, and food fraud databases.

These systems can also tie into them audits, forms, and data managementdata management to help a food processing plant automate regulatory management and provide mobile forms and online databases to target needs and input and track data on devices that integrate across an operation. This could include the automation of mobile forms and surveys for audits and inspections; customized applications and forms for Food Safety and Process Control; streamlined audit applications; testing and analysis software; statistical analysis software; FSMA compliance applications and software; and branded food products.

AI and ML are both technologies that are almost buzzwords when it comes to any kind of automation. And accordingly, these technologies have been applied in various parts of the supply chain of the food industry. For food processing, AI can be used for either the proper ordering and packaging of food products, where AI can handle the task and reduce the chance of error. There have been some challenges of using AI-based sorting and packaging in food processing, based on the irregularities in shapes, color, and sizes of vegetables and fruits, although most of the time this can be accounted for with large amounts of data and proper training of the AI models and system.

In food processing, AI can also be used to ensure proper guidelines are followed for the handling, sanitization, and packaging of food. This can include the use of separate guidelines based on the expected destination of a given food product and the local guidelines. And the use of AI can be used to monitor and monitor individuals who are or are not following guidelines and to resolve issues to monitor individuals not following guidelines. And AI allows food processing to monitor all parts of the food processing system to manage everything, from price control and inventory management, and forecasting and monitoring the pathway of possessions, from where ingredients are grown all the way to where customers collect ingredients.

The use of artificial intelligence and robotics in food processing offers a chance to decrease the number of foodstuff-related diseases. The Food Safety Modernization Act (FSMA) offers stricter hygiene rules applicable across a supply chan. Often the foods whichthat do not require refrigeration, such as cereals, spices, and related food products, are often the most prone area ofto contamination. These had previously been one of the safer food products, but this has since changed, and AI has been suggested as a possible solution for the problem. Using robotics means a food processing plant can manage these foods without transferring possible illnesses carried by humans, and the maintenance of an AI system is easier and simpler than humans.

Two promising inventions in the food industry include next-generation sequencing (NGS) and electric noses (ENs). NGS is capable of replacing older generations of food securityfood security, with the introduction of AI-based systems and workflow helping formulate data acquisition and laboratory trials quickly and more accurately than traditional methods. The NGS can help find hazardous inclination quickly and work to prevent the possible spread of infectious epidemics before any group of people are impaired. While electric noses (ENs) are sensors that act as surrogates for human noses. These sensors can be used to identify a diversity of smells in itsthe surroundings, and by sendingsend the data to a data center, where algorithms can access the data and signal alarms to the manufacturing units to ensure product safety.

As food is processed, or as it is brought from a farm, the food is often kept in warehouses and distribution centers. These centers have already, in other industries, begun seeing the use of automated guided vehicles (AGVS) rather than traditional forklifts, and with AGVS capable of performing a range of tasks, including loading and unloading trucks, transporting large items across warehouses, and other related duties that previously could require multiple employees. And AGVS also, in terms of reducing food waste, are capable of conducting operations in harsh conditions, such as in cold storage environments, meaningenvironments—meaning a warehouse could be almost entirely chilled without concern for the health and safety of workers, as autonomous and robotic systems are capable of taking over.

The food industry has a lot ofmany well-established brands and food outletsfood outlets, and for some the long-established businesses in the industry takes the luster off the idea of establishing a new business, due to the competition. However, through data sciencedata science and automated technologies, users can try and develop a competitive edge or stay ahead of the competition. One of these metricsmetric that can be measuredutilized is customer satisfaction., Thiswhich hascan beenbe used to help understand supply and demand metrics of customers, and has resulted. inCompanies with products such as ten-minute dinner kits, with more than tens of thousands of customers and different menu options, andcan offersutilize data on buying history, customer behavior, and feedback, and food preference of different time framespreferences to ensure the readiness to meet demands.

Having and understandingUnderstanding this data can be especially important in the case of a food processor or develop introducingdeveloping a new recipe for goods. As a single recipe can be cooked in numerous ways, and individual ingredients can be cooked to provide endless possibilities for various dishes, this technology can appraise which food components, based on an exploration of different recipes, and aggregations of different approaches to the same food product, to understand which components have a decent savor mark, and to mark a cuisine that is trendy by region. This basic understanding can permit an artificial intelligence-based algorithm to recommend different types of ingredient combinations for chefs that could result in a broadened menu and profits for either a food producer or for a restaurant.

For the restaurant industry, the level or capability to automate different systems is dependent on the type of restaurant. For example, front-end and back-end automation in a fast-casualcasual restaurant with a static menu and delivery options is often easier to automate on various levels, versus the level of automation for a more formal dining experience with a seasonally changing menu and with an increased focus on the quality and experience of the food and the restaurant. But even in the latter example, there are chances to automate, especially in time-saving ways that are not always immediately apparent.

There are various ways automation can assist the restaurant industry that are similar to the benefits offered by other forms of automation through the food industry. This can include the a reduction in employee turnover,. orAnd in the case of employee turnover, automation can save time, energy, and reduce overall training across an organization. Further, the automation can streamline various front-end and back-end systems, as well as automatingautomate back office tasks in order to eliminate mandatory and mundane tasks that operators deal with on a daily basis, such as forecasting, production, vendor ordering, receiving, and scheduling. This could include tasks such as plan purchasing, menu building, and staffing, and bringing greater efficiency to those functions.

As well, any automation promises to offer predictive ordering, automatic price menu adjustments based on demand, drone food delivery, automatic food preparation systems, and automated food or drink delivery for on-site for restaurant operations.

Restaurants have toyed with and developed AI and voice recognition systems for helping streamline incoming orders, and enabling fast-casual restaurants to process drive-thru, phone-in, and kiosk-based orders without need for human labor. And this kind of technology can connect restaurant POS systems to provide the kitchen with the orders without assistance. This type of automation lends itself to the fast-casual restaurants' use of ordering kiosks or the use of mobile applicationsmobile applications for order and pay. These different ordering systems provide different types of automation whichthat remove several steps and interactions from the ordering experience and has seen stores like McDonald's and Shake ShackShake Shack open stores with kiosk ordering only.

An example of this type of automation, paired with back-end automation, is Cafe X in San FranciscoSan Francisco, which offers a fully-automated cashless specialty coffee experience with customers either paying ahead through a mobile application or pay on tablets at the kiosk. These kiosks pair the automated ordering system with automatic coffee machines capable of brewing americanos, espressos, cappuccinos, cortados, lattes, and flat whites while offering customers choice of beans and milk types.

Product information management (PIM) platforms work to handle product information in one source for all channels, which can help restaurants or grocery stores to maintain the quality of the data and the amount of data in a single place. This could include to change the data for different changes in expectations, such as for digitization and digital innovations; changes in consumer behavior and increased customer expectations; globalization, laws, rules, and restrictions; CSR and sustainability; demographic changes; health, allergies, and diseases; and big databig data and smart data.

When talking about automation in grocery stores, one of the more talked about developments is in the B2CB2C store space, where e-commerce businesses such as AmazonAmazon or WayfairWayfair develop brick-and-mortar establishments, other than warehouse spaces, for shoppers to go and shop products. For example, Amazon has piloted cashier-less, and almost people-less, supermarkets, where a user can scan in to the store with an Amazon account, pick out whatever items at the supermarket, and leave. And these stores, a concept also piloted with Amazon-owned Whole Foods, charge the user for the items, which are tracked using computer vision.

Another growing trend in the automation of grocery stores, especially for stores working towards full automation, is the use of robots in the customer areas, rather than just in the warehouses. Robots have already been trialed for warehousing and stock areas in larger stores such as Amazon and WalmartWalmart, where the have been used to pick items or to move items from shelves to another robotic system capable of moving goods from one area to another. But these systems still require a larger amount of human labor. However, these systems have also grown in popularity due to the move towards delivery and BOPIS models, where more employee hours are spent on fulfilling orders, packing groceries, and delivering orders, rather than on the front end grocery work of talking to customers, cleaning possible spills, stocking retail shelves, and related duties.

A more common use of robotics in grocery stores has seen robots used for cleaning spills, cleaning floors, checking inventory, or directing customers. Most of these robotic systems are unable to perform multiple functions. Some examples include Marty, made by Badger Technologies, which is capable of alerting customers to spills in English and Spanish. Similarly, Tally, a robot manufactured by Simbe RoboticsSimbe Robotics, has been used in Giant EagleGiant Eagle and Shnucks, to monitor shelves and alert workers to out-of-stock items or problems related to merchandise presentation or merchandise out of place. Tally takes a predefined route through a store and transmits the collected data to employees.

Similar to Marty, Millie is a robot capable of detecting hazards, such as spills, and was trialed in a Woolworths in AustraliaAustralia. However, beyond alerting customers and employees to spills, Millie can also clean the spills it detects. During the robots trial, it was met with mixed customer reviews, with some customers finding the robot unfriendly and others concerned the robot would replace human workers.

An example of this type of automation, paired with back-end automation, is Cafe X in San FranciscoSan Francisco, which offers a fully-automated cashless specialty coffee experience with customers either paying ahead through a mobile application or pay on tablets at the kiosk. These kiosks pair the automated ordering system with automatic coffee machines capable of brewing americanos, espressos, cappuccinos, cortados, lattes, and flat whites while offering customers choice of beans and milk types.

When talking about automation in grocery stores, one of the more talked about developments is in the B2C store space, where e-commerce businesses such as Amazon or WayfairWayfair develop brick-and-mortar establishments, other than warehouse spaces, for shoppers to go and shop products. For example, Amazon has piloted cashier-less, and almost people-less, supermarkets, where a user can scan in to the store with an Amazon account, pick out whatever items at the supermarket, and leave. And these stores, a concept also piloted with Amazon-owned Whole Foods, charge the user for the items, which are tracked using computer vision.

A more common use of robotics in grocery stores has seen robots used for cleaning spills, cleaning floors, checking inventory, or directing customers. Most of these robotic systems are unable to perform multiple functions. Some examples include Marty, made by Badger Technologies, which is capable of alerting customers to spills in English and Spanish. Similarly, Tally, a robot manufactured by Simbe Robotics, has been used in Giant EagleGiant Eagle and Shnucks, to monitor shelves and alert workers to out-of-stock items or problems related to merchandise presentation or merchandise out of place. Tally takes a predefined route through a store and transmits the collected data to employees.

The food industry has a lot of well-established brands and food outletsfood outlets, and for some the long-established businesses in the industry takes the luster off of establishing a new business due to the competition. However, through data science and automated technologies, users can try and develop a competitive edge or stay ahead of the competition. One of these metrics that can be measured is customer satisfaction. This has been used to help understand supply and demand metrics of customers, and has resulted in products such as ten-minute dinner kits with more than tens of thousands of customers and different menu options, and offers data on buying history, customer behavior, and feedback and food preference of different time frames to ensure the readiness to meet demands.

The management of food wastes in the growing, distributing, processing, and selling of food is an important place where the food supply chain can increase efficiencies. In a report published by the U.S. Department of Agriculture, it was found that food waste in the United StatesUnited States alone accounted for between 30 to 40 percent of the food supply. This estimate, which was also based on estimates from the USDA's Economic Research Service of 31 percent food loss at the retail and consumer level, corresponded to the approximately 133 billion pounds and around $161 billion worth of food consumed in 2010. AI has been proposed as one possible solution to these problems, by helping to identify and find solutions for food waste, if not creating efficiencies prior to food production to limit overall waste. In the case where food waste occurs, AI can help identify uses for the food waste, such as regenerative farming practices. Other possible benefits to the application of AI to food waste includes:

Similar to Marty, Millie is a robot capable of detecting hazards, such as spills, and was trialed in a Woolworths in AustraliaAustralia. However, beyond alerting customers and employees to spills, Millie can also clean the spills it detects. During the robots trial, it was met with mixed customer reviews, with some customers finding the robot unfriendly and others concerned the robot would replace human workers.

These systems can also tie into them audits, forms, and data managementdata management to help a food processing plant automate regulatory management and provide mobile forms and online databases to target needs and input and track data on devices that integrate across an operation. This could include the automation of mobile forms and surveys for audits and inspections; customized applications and forms for Food Safety and Process Control; streamlined audit applications; testing and analysis software; statistical analysis software; FSMA compliance applications and software; and branded food products.

A more common use of robotics in grocery stores has seen robots used for cleaning spills, cleaning floors, checking inventory, or directing customers. Most of these robotic systems are unable to perform multiple functions. Some examples include Marty, made by Badger Technologies, which is capable of alerting customers to spills in English and Spanish. Similarly, Tally, a robot manufactured by Simbe RoboticsSimbe Robotics, has been used in Giant Eagle and Shnucks, to monitor shelves and alert workers to out-of-stock items or problems related to merchandise presentation or merchandise out of place. Tally takes a predefined route through a store and transmits the collected data to employees.

Product information management (PIM) platforms work to handle product information in one source for all channels, which can help restaurants or grocery stores to maintain the quality of the data and the amount of data in a single place. This could include to change the data for different changes in expectations, such as for digitization and digital innovations; changes in consumer behavior and increased customer expectations; globalization, laws, rules, and restrictions; CSR and sustainability; demographic changes; health, allergies, and diseases; and big databig data and smart data.

The food industry has a lot of well-established brands and food outlets, and for some the long-established businesses in the industry takes the luster off of establishing a new business due to the competition. However, through data sciencedata science and automated technologies, users can try and develop a competitive edge or stay ahead of the competition. One of these metrics that can be measured is customer satisfaction. This has been used to help understand supply and demand metrics of customers, and has resulted in products such as ten-minute dinner kits with more than tens of thousands of customers and different menu options, and offers data on buying history, customer behavior, and feedback and food preference of different time frames to ensure the readiness to meet demands.

Two promising inventions in the food industry include next-generation sequencing (NGS) and electric noses (ENs). NGS is capable of replacing older generations of food securityfood security, with the introduction of AI-based systems and workflow helping formulate data acquisition and laboratory trials quickly and more accurately than traditional methods. The NGS can help find hazardous inclination quickly and work to prevent the possible spread of infectious epidemics before any group of people are impaired. While electric noses (ENs) are sensors that act as surrogates for human noses. These sensors can be used to identify a diversity of smells in its surroundings, and by sending the data to a data center, algorithms can access the data and signal alarms to the manufacturing units to ensure product safety.

The use of various connected sensors can help increase visibility into the transportation of goods, to better understand where food is coming from and where it is going, and offers traceability to help improve emergency planning and food defense to give customers a more transparent product. This can further include serial tracking tools; inventory management tools; layered process audits; quality assurance; supplier quality management; traceability and HACCP solutions; traceability and inventory management software for the food industry; process management software for batch and recipe/formulation-based manufacturing; invisible barcoding software, embeddable in everything, and supply chain managementsupply chain management and logistics elements; and transportation monitoring. This can all be used to ensure the quality of the product is maintained by tracing and promoting the safety of a product through its tracing.