New Articles

The Effects of AI on Fleet Management

emission drive battery fleet

The Effects of AI on Fleet Management

AI or artificial intelligence is buzzing in just about every industry. It is greatly changing the trucking industry, from driving to office resources. This article will discuss the future of transportation, AI in the trucking industry, and fleet intelligence.

Future of Transportation

Artificial intelligence is changing the future of transportation in many ways. There are several upcoming trends and new ways of transportation on the horizon. It is as if the Jetsons had the future of technology and transportation right all along. It is time to embrace the future of transportation as we know it. Here are some vehicles that may be just around the corner and some may be a bit further away.

Delivery drones

Delivery drones are unmanned aerial vehicles designed to distribute lightweight packages in the last-mile delivery process. AI is used to autonomously drive the delivery drones or they are remotely controlled. These vehicles are rechargeable, flying robots that can navigate routes and drop-off points. They use GPS, sensors, and computer vision systems to help with navigation. The first commercial drone delivery in the United States took place in 2016. It transported frozen slurpees, donuts, coffee, and chicken sandwiches. Delivery drones are available abroad now and deployed in select US cities.

Driverless vehicles

Driverless or self-driving cars are operated autonomously without human input. There are sensors throughout the vehicle that enable the car to be aware of its surroundings. There are several mapping tools used to operate driverless vehicles. These include cameras, radar, LiDAR, ultrasound or sonar, GPS, odometry, and inertial measurement units. These tools work together to compute a three-dimensional model of the vehicle’s surroundings. They inform the vehicle of traffic controls, merging opportunities, and obstacles en route. 

Flying hotel pods

Flying hotels are only a theory at this time. Flying hotels are aircraft designed to remain in flight while housing passengers for an extended stay.  Guests could check in to their own pods and have access to common areas in the facility. Flying hotels can be thought of as a sort of cruise ship in the clouds or low-orbit, traveler-friendly space station. 

Flying taxis

Flying taxis or air taxis are small commercial aircraft that can transport passengers regionally on demand. These aircraft would be used for short-distance commutes. This would be a faster method of transportation because it would bypass any ground traffic congestion. Flying taxis are the perfect candidate for all-electric, zero-emissions air travel, with the first generation of battery-powered planes likely to serve as airport transit services, cargo vehicles, and training planes for new pilots.


A hyperloop is a high-speed, ground-level transportation system that uses magnetic levitation and electromagnetic propulsion to transport passengers or goods through a vacuum tunnel at jet-like speeds. It is essentially a futuristic train. A hyperloop is composed of three parts which include sealed, low-pressure tubes, pressurized coach pods, and terminals. 

AI in the Trucking Industry

Managing a fleet can be tricky. Managers are required to wear multiple hats and juggle responsibilities and tasks. AI has made this job much more streamlined and efficient. There are many benefits of AI fleet management software. 

Real-time analytics

Real-time analytics is essential to having a smoothly operating fleet. Data is collected and analyzed in real time. This includes your vehicles’ location, status, and movement. AI fleet management systems can monitor your vehicles in real-time and identify potential issues, improve fuel efficiency, and even detect vehicle misuse. When a problem is detected it can alert you so you can immediately take corrective actions.

Vehicle maintenance 

You do not have to wait for a vehicle to show signs of breakdown. Using AI algorithms, you can analyze vehicle use patterns and real-time data from sensors installed in vehicles. This is helpful in identifying small signs of wear and tear before they become bigger, more expensive problems. Also, AI software can help prevent breakdowns and reduce the risk of accidents on the road.

Route planning  

Route planning can become overwhelming. This is especially true when you are managing a large fleet. There are many factors to consider including traffic patterns, weather conditions, and vehicle availability, to ensure your vehicles operate efficiently and on time. AI can analyze real-time data from various sources, such as GPS trackers and weather and traffic alerts, to automatically optimize routes for maximum efficiency.

Driver safety management

Driver safety is the top priority for many fleet managers. However, monitoring and improving driver behavior while staying on top of other fleet tasks can require a massive amount of effort. AI-powered telematics devices, such as dash cams and speed sensors, can automatically record, detect, and alert you to unsafe driving behaviors such as speeding, harsh braking, and distracted driving. 

Dashcam video analysis

Dash cams are a way to monitor a driver’s behavior. This protects your drivers against false incident claims and ensures compliance with safety regulations. You can use AI-powered dash cam software which can automatically flag and categorize footage relevant to unsafe driving behavior. This allows you to review your driver’s performance more easily and gives you insight into the kind of training you need to provide.

Fleet Intelligence 

Artificial intelligence is revolutionizing the trucking industry. Telematics devices can be installed in the vehicles and make accurate predictions based on the data collected. Some telematics devices include GPS trackers, dash cams, and sensors that can provide a wealth of information on your vehicle’s status, including data on its movement, speed, location, and fuel consumption.

Fleet intelligence is a cloud-based fleet management solution designed for heavy equipment fleet operators and managers. Key features include an automated maintenance scheduler, layered map views, asset tracking, and real-time alerts.

Fleet intelligence allows managers to monitor their entire fleet in real time and in one place. It provides critical data such as location, DTC alerts, geofencing, oil scans, and preventative maintenance issues.  Fleet intelligence can also identify and reassign underutilized machines, automate maintenance schedules, and analyze the fleet by job, timeframe, foreman, and location.

Fleet intelligence software can send messages and alerts to mobile devices to track vehicles. It can do an oil scan, geofence, and other related events in order to track vehicles.  Also, a support team is available so users can submit tickets online for any support inquiries or reach out to the support team via phone and email.

Finally, AI is rapidly changing and transforming fleet management. With AI’s ability to collect and analyze vast amounts of data, it is making the industry even more efficient. AI will only continue to transform how fleets are managed.

AI market platform edge

Edge AI Market Poised to Reach $70 Billion by 2032: Unleashing the Power of Decentralized Intelligence

In a world increasingly reliant on data-driven decision-making, Artificial Intelligence (AI) has emerged as the linchpin of technological advancement. One of the most transformative facets of AI is Edge AI, which brings the processing power of AI algorithms closer to the data source. This paradigm shift has not only accelerated the pace of innovation but also opened up new horizons for industries across the board. Recent market research indicates that the Edge AI market is set to explode, with projections estimating a worth of $70 billion by the year 2032.

The Edge AI Revolution

Edge AI represents a quantum leap in the evolution of AI applications. Unlike traditional AI models that rely on cloud computing for processing, Edge AI shifts the computational burden to local devices or on-premise servers. This decentralized approach not only reduces latency but also enhances privacy and security, making it ideal for real-time applications like autonomous vehicles, industrial automation, healthcare, and more.

 Factors Driving Edge AI Market Growth

  1. Real-time Decision Making: Industries such as autonomous vehicles, healthcare, and manufacturing require instantaneous processing for mission-critical applications. Edge AI’s ability to make split-second decisions without relying on a distant server is a game-changer.
  2. Data Privacy and Security: With an increasing emphasis on data privacy and stringent regulatory frameworks, Edge AI offers a compelling solution. By keeping sensitive information on-premise, it mitigates the risks associated with transmitting data to the cloud.
  3. Bandwidth Optimization: Edge AI alleviates the strain on network bandwidth by processing data locally. This is especially crucial in scenarios where transmitting large volumes of data to the cloud is impractical or cost-prohibitive.
  4. IoT Proliferation: The Internet of Things (IoT) has witnessed explosive growth, and Edge AI is the perfect complement. By embedding AI capabilities into IoT devices, they can make intelligent decisions autonomously, reducing the need for constant connectivity.
  5. Customization and Personalization: Edge AI enables the tailoring of AI models to specific use cases. This level of customization ensures that solutions are finely tuned to the unique requirements of different industries and applications.

Verticals Poised for Disruption

  1. Autonomous Vehicles: Edge AI is a linchpin in the development of self-driving cars. Real-time processing is vital for making split-second decisions in complex traffic scenarios.
  2. Healthcare: From wearable devices to medical imaging, Edge AI is transforming healthcare by providing faster diagnostics, personalized treatment plans, and even remote patient monitoring.
  3. Manufacturing and Industry 4.0: Edge AI is revolutionizing the manufacturing sector by enabling predictive maintenance, quality control, and process optimization in real time.
  4. Smart Cities and Infrastructure: Edge AI is instrumental in creating intelligent urban environments. From traffic management to energy optimization, it is pivotal in building sustainable cities of the future.
AI market platform edge

AI as a Service Market revenue to cross USD 75 Bn by 2032 

As per the report by Global Market Insights, Inc. “Worldwide AI as a Service Market was valued at USD 6 billion in 2022 and will surpass a revenue collection of USD 75 billion by 2032 with an annual growth rate of 25% over 2023 to 2032.”

Increasing data availability and advancements in cloud computing are cited as chief drivers of the industry. The proliferation of data and the rise of cloud computing are stimulating AI models as businesses are now generating vast volumes of high-quality data to train effectively. Cloud computing platforms provide the necessary infrastructure to store, process, and analyze this data, making it easier for AIaaS providers to offer their services at scale. Moreover, the ease of integration with existing systems facilitates the adoption of AI across various industries and is contributing to market growth.

The AI as a Service market from the large enterprises segment accounted for a significant revenue share in 2022, attributed to fluctuating demands for AI services based on the business cycles, seasonal variations, or specific projects in these organizations. AI as a service offers scalability and flexibility, allowing organizations to adjust their AI usage based on their needs. In addition, the ability to offload the burden of AI development, deployment, and maintenance to specialized providers aids large firms to save costs & effort.

The AI as a Service market from the private cloud segment will depict a considerable growth from 2023 to 2032, owing to greater control and customization over AI solutions. Private cloud services enable businesses to tailor AI models and algorithms to their specific needs, ensuring compliance and security of proprietary information. Moreover, it allows organizations to deploy AI services closer to their data sources, reducing latency and ensuring optimal performance. 

Asia Pacific AI as a Service market is projected to amass substantial gains by 2032. Countries such as China, Japan, South Korea, and Singapore invest heavily on AI R&D, pursuing digital transformation initiatives across various sectors such as healthcare, finance, manufacturing, and retail. This transformation provides intelligent solutions for automation, data analytics, customer engagement, and personalized services, which will spur the regional market progression in the upcoming years.

Some of the leading companies operating in the AI as a Service market include Alphabet Inc. (Google LLC), Alibaba.Com, Amazon Web Services, Inc., CognitiveScale, Inc., Baidu, Craft.AI, IBM Corporation, DATAIKU SAS, Intel Corporation, Oracle Corporation, Microsoft Corporation, Inc., and SAP SE. These companies engage in a range of product diversification tactics and strategic partnerships to stay ahead in the industry.

In March 2023, Oracle Corporation, an IT services company, partnered with Nvidia to roll out new AI technology. The new cloud computing service based on Oracles chips and software offerings, intended to aid Nvidia in expanding its AI generative chip product line.

In March 2023, Baidu, a Chinese IT behemoth, launched its AI bot in response to ChatGPT by Open.AI. The ERNIE Bot service will help the company to remain at the forefront in the AI services market and attain a competitive edge in the country.

How AI can Aid the EHS Manager in Identifying Potential Safety Hazards in the Workplace

Since Artificial Intelligence was invented, how people work and live has changed significantly. While AI effortlessly learns and processes a huge amount of data, it has become an undeniable favorite tool for corporations across the globe. From personal to business uses, the options are endless. In a bid to automate multiple business procedures, identifying safety hazards has become a new addition.

An Environmental, Health, and Safety (EHS) Manager must be present for these processes to occur. As described by ProtexAI in a guide, an EHS manager develops and implements effective safety programs to enhance the well-being of employees in a workplace. From training initiatives to recycling programs, the applications are numerous. They usually work with facility managers, but AI is fast becoming a new application.

To be an aide to the EHS (Environmental, Health, and Safety) Manager, AI has to identify, improvise, and mitigate safety risks in the workplace. Apart from the traditional approaches of audits, which can be time-consuming and inaccurate, AI can automate the process better. It works by analyzing data sources effectively to pinpoint patterns and improvement opportunities. This allows the EHS manager to focus on problem areas to establish efficacy-driven measures.

Here are some ways how AI can help EHS managers improve workplace safety:

Identify Patterns in Data

For AI to pick up patterns of equipment behavior, analyzing large data sets from machine sensors is vital. AI can easily highlight a potential safety hazard by using a data-driven approach to identify discrepancies, abnormalities, and disparate patterns. From overheated machines to unusual sounds from internal machinery, nothing is undetectable. In addition, employee feedback on production floors can also be incorporated. Not just limited to machines, slippery floors, poor lighting, and ventilation can also be noted. As long as data can be coordinated and consolidated, AI can use it for EHS managers to take preventive or corrective actions.

Potential Hazard Prediction

Through historical data, AI can swiftly detect consistent or probable recurring patterns. With this additional information, identifying the root causes of accidents is simple. By knowing the reasons behind different incidents, EHS managers can establish preventative measures to stop history from repeating itself. One of the best aspects is predictive modeling. It is a methodology that analyzes data using statistical algorithms to predict future outcomes. AI can instantly predict potential safety risks as long as a wide range of data sources is included, such as weather and machine data.

Empower Safety Training

Employees must be adequately trained and informed of the latest safety procedures to cultivate a safe workplace. AI can help analyze data from employee training programs. Struggling employees can be pulled aside and given a personalized approach to help improve. By addressing their pain points, employee safety awareness can be maximized to reduce the probability of accidents.

Drive Regulatory Compliance

With data, AI can be a potent ally for workplace safety. AI can instantly pinpoint areas lacking regulatory compliance through employee feedback, machine and environmental data. By being aware of areas that lack compliance, EHS managers can develop and implement measures for damage control. In some cases, corrective measures can be executed to ensure each area complies with the state’s regulations.

In Summary

AI is a powerful aid for EHS managers to identify potential safety hazards in the workplace by analyzing a vast range of data sources. Not just to prevent accidents, it is a helpful ally in ensuring the corporation is compliant with the state’s regulations to avoid legal implications. Despite AI’s many uses, it is not a direct replacement for human judgments but a tool for providing actionable insights to help EHS managers make informed decisions.

supply lending edge coriolis intelligence AI lenders

Edge AI Market Expected to hit US$70 Bn by 2032 

As per the report by Global Market Insights, Inc. “Worldwide Edge AI market was valued USD 5 billion in 2022 and will surpass a revenue collection of USD 100 billion by 2032 with an annual growth rate of 35% over 2023 to 2032.”

Global Edge AI Market size is predicted to expand considerably throughout the forecast period 2023 to 2032 due to the rising consumer inclination towards smart homes.

Integration of supports monitoring of temperature, gas density, humidity, and home security. Increased customer expectations and a rise in the availability of such advanced gadgets are predicted to boost the market share for edge AI. Furthermore, the growing demand for consistent data access and low latency across industries is fueling the need for powerful infrastructure. Using technologies, businesses can achieve significant cost and performance savings.

In April 2021, multinational technology company, Intel, introduced third-generation Xeon scalable CPU which allows for the implementation of a flexible and scalable infrastructure. It can enhance workloads related to 5G, AI, and other high-performance computing, network security, and clouds.

Moreover, the increased acceptance of remote working since the COVID-19 outbreak is another factor influencing the industry’s growth. Edge AI enables businesses to securely grant access of internal resources to their distant workers. Additionally, it lowers the price and maintenance expenses related to physical network infrastructure.

Based on component, the services segment of the market is anticipated to grow at a rapid pace during the forecast period resulting from the global development of edge-based technology. Further, the subdivisions comprising training and consulting, system integration and testing, and support and maintenance make up the service market segment.

Due to the rising demand for dependable and low-latency data access throughout all companies, the system integration and testing segment will continue to expand. Furthermore, the expansion of the support and maintenance segment is attributed to its capacity to help organizations give speedy remote assistance for reducing network outages which will boost the overall market share.

In terms of end user, the government segment is anticipated to exceed USD 3 billion by 2032 owing to the increasing adoption of helping government offices to consolidate and centralize their IT resources to enable users to access the system anytime from anywhere. The growing digitization and need for robust wireless connectivity across government agencies are fueling market growth. For instance, MEA governments are digitalizing all of their departments and services, improving their infrastructure, and providing new services like e-applications that speed up administrative processes.

Depending on application the market the segmented as video surveillance, remote monitoring, predictive maintenance, and other segments. The adoption of telemetry in the healthcare industry is covered in the other category. This technology aids in the automatic detection of abnormalities in the operation of telemedicine devices. Telemetry in medical equipment also helps with patient management, diagnosis, and treatment from a distance. Such a wide range of edge AI applications will promote industry growth.

Regionally, the Middle East edge was valued at over USD 500 million in 2022 as several telecom operators are increasingly emphasizing on trials and deployment of 5G across the region accelerating revenue growth. Soaring demand for edge computing and data centers owing to the development of smart cities in Saudi Arabia and the UAE has led to massive investments in the IT sector, especially in GCC countries like Saudi Arabia, the UAE, and Qatar will push the market growth further.

The Edge AI market consists of Anagog Ltd., Amazon Web Services (AWS), Dell, Google (Alphabet Inc), Gorilla Technology Group, Huawei Technologies Co., Ltd., IBM Corporation, Imagimob AB, Intel Corporation, Microsoft Corporation, MediaTek Inc, 

supply lending edge coriolis intelligence AI lenders

How to Successfully Incorporate AI in Procurement

People looking to optimize their procurement processes sometimes turn to artificial intelligence (AI). This option is not yet widespread, but it’s becoming more common, especially as decision-makers explore new technology investments. Here are some things for individuals to keep in mind before and during their use of AI in procurement. 

Know That AI Does Not Replace Human Input and Expertise 

Artificial intelligence is a subject with much hype surrounding it. The excitement and buzz are not wholly unwarranted. When used well, the technology can change business processes and results. However, people must remember that even the most advanced AI cannot and should not replace human judgment and knowledge. 

The best approaches involve AI supporting human input and helping them make better, faster decisions. Decision-makers mistakenly believing AI can work unattended without ongoing supervision from humans will almost certainly end up disappointed due to unrealistic expectations. 

A good starting point is to consider any areas of procurement that need improvement due to a high probability of errors and inefficiencies. Taking a closer look at those shortcomings can help people understand what causes the issues and how AI might help resolve them. 

Moreover, it’s helpful for people to designate individuals or teams who will oversee the AI deployment process and solve issues that arise. Carefully planned tech implementations are more likely to proceed with fewer problems, but people should still expect a few surprises. Having a point person or team to solve those mishaps will prevent the matter from getting out of hand. 

Work With Experienced Service Providers

People at many organizations are still relatively new to using AI in procurement or for any other reason. That’s why it’s smart for them to find and hire companies or individuals with the experience to guide them through the project from start to finish. It’s ideal if these selected service providers have direct expertise in applying AI to similar use cases or at least have worked with other clients with procurement needs. 

In one case, the U.S. Department of Health and Human Services (HHS) worked with an external consultant as part of a larger procurement improvement process. The service provider combined microservices and AI to meet the department’s goals. An AI algorithm enabled the department to compare and contrast previous purchases. It analyzed the content of more than 2 million current contracts and assessed 5-7 billion words. 

Since the AI used language directly from existing contracts, it allowed procurement professionals to more effectively enter into new agreements with suppliers or to extend current partnerships. 

The tool’s design and functionality kept user-friendliness at the center. People interacting with it don’t need to know the exact terms to search for. Instead, they go through a guided process that helps them find the most relevant information quickly and easily. 

This example shows why it often makes sense to seek providers with the expertise to create solutions that fit specific needs. Finding a company with the right experience often speeds the development process and improves the chances of the AI product working as expected. 

Agree on the Primary Objectives 

People should not apply AI in procurement solely because they know competitors already have. Instead, they must develop several concrete reasons why they want to use artificial intelligence and what they’ll achieve in the best-case scenarios. 

One way to do that is to figure out how AI fits in with a company’s main business goals, whether those milestones occur in the short or long term. All organizations have specific priorities, but sustainability is an issue coming to the forefront more often lately. That’s true in terms of procurement and throughout the wider supply chain. For example, AI might identify suppliers with the lowest environmental impacts or those with less waste than competitors. 

It’s not always easy to zoom in on those finer details without technological assistance. The beauty of AI is it can process huge quantities of data much faster than humans working independently. A well-trained algorithm might confirm whether a company has a long history of operating sustainably or could uncover some previously unnoticed red flags. 

Everyone involved must agree about the AI’s primary functions, regardless of whether a company’s goals relate to sustainability or other matters. Ironing that out early will make it easier to get executive buy-in and ensure top-down support for the technology from the beginning. 

Seeing how similar companies and industries have used AI in procurement could provide some necessary inspiration. For example, a hospital will have different procurement processes than a government agency.

Assess How Using AI Could Boost Resilience 

COVID-19 and numerous other factors have made supply chains far less stable than they once were. There’s no easy fix for that challenging situation, but AI could reduce some uncertainties. 

For example, people have successfully used supply chain AI tools to improve demand forecasting. Companies are then less likely to run out of the supplies they need or have too many of certain items on hand. 

However, AI could increase resilience in other ways, too. Perhaps a company has previously had issues with counterfeit parts or supplies. Artificial intelligence is excellent at spotting deviations from the norm, picking up on things people can’t. 

One product developed to screen for fake luxury handbags assesses anywhere from 500 to 1,500 features per item. It then gives the results of a check in as quickly as 60 seconds, although it sometimes takes an hour, depending on the brand. The tool also gets smarter with use. 

Even the most sharp-eyed and conscientious people can’t check such minute details so fast. There’s also a high likelihood of individuals getting fatigued and missing out on flaws or fakery. AI is not foolproof but does not get tired or distracted like humans.

These are a couple of the many ways companies can and have depended on AI in procurement to become stronger and less vulnerable to problems. People should set key performance indicators (KPIs) related to the changes they want to make in the organization with the help of AI. That will make it easier to see if the AI is working as expected or needs further tweaking. 

Using AI in Procurement Requires a Careful Strategy

Artificial intelligence-related procurement applications certainly have potential. However, people cannot expect to have AI deployed within their organizations in a matter of weeks. It could take months to figure out the best ways to use the technology and get people accustomed to working with it. That’s K. It’s far better to take care when using AI than to rush the rollout and risk experiencing frequent setbacks.

Author’s Bio

Emily Newton is an industrial journalist. As Editor-in-Chief of Revolutionized, she regularly covers how technology is changing the industry.

AI market platform edge

Implementing AI in Workforce Training Techniques

Food Safety is considered as one of the most important functional aspects of the food industry; it is estimated that the food industry loses over $110 billion in revenue and productivity due to medical expenses and brand reputation damages caused by food-borne illnesses. However, the industry is also infamous for being one of the most labor-heavy industries in the world, which subsequently leads to the biggest food safety challenge: Food Safety Training. Training all employees within the food industry regardless of management level is essential to allow food safety culture to grow within a business and to ensure that all products manufactured by a facility are safe to consume.

But with all the talk regarding food safety and hygiene training, another important question arises: How does an employer determine what kind of training is important for their employees? The answer is not always straightforward, but it is crucial for employers to keep in mind that basic food safety and hygiene topics should be covered for all employees through on the-job-training or through a classroom set-up; these topics can range from basics like Cross Contamination and Hazard Identification to more advanced topics such as HACCP and ISO 22000:2018 awareness. With the rise of AI or Artificial Intelligence in the Food industry, there are various tools such as Vision AI and Machine Learning which have proven to be effective in improving various processes within a food business, one of the more important ones being food safety and hygiene training.

Before delving into the benefits of AI in the food industry it is prudent to understand: What IS Artificial Intelligence? AI or Artificial Intelligence is an umbrella term used for various kinds of technology which includes but is not limited to: Vision AI, Machine Learning and Text AI. Among the many benefits these diverse sub-divisions of AI can provide food professionals globally, some of them are:

Personalized Training Modules & Integrated Training Experience

When training employees in food safety and hygiene, it is prudent to understand every employee may require different kinds of teaching methodologies to be implemented to ensure maximum effectiveness; but in a company dealing with 1000+ employees, how does one ensure this? The answer to this question is the use of Vision AI: As on-the-job training is the most common form of food safety training today, Vision AI allows employers to create simulations of various real-life scenarios where food safety is at risk and subsequently train employees on how to handle them in real time, with the added benefit of not allowing any customer-facing products to be at risk. If required, this technology also allows employers to create customized scenarios in accordance to the employee skill, thereby allowing said employee to have a fully integrated experience as compared to regular classroom training.

Focused Training Activities & Organized Training Programs

The most common form of food safety and hygiene training is on-the-job training, followed by classroom training; however, one of the greatest challenges faced by any training professional is the creation of a stringent training program and organizing training activities in accordance to topics, all the while ensuring each and every employee, even in large scale companies, is trained. In these instances, the use of AI has created an opportunity for food safety training professionals to create effective training programs that can take into account various factors such as number of employees, management level, training levels and even language. Building on this, creating focused training activities such as on-the-job simulations as described previously, can also be created using Vision AI and Machine Learning capabilities.

Effective Data Collection and Feedback

In an industry that encounters possibly hundreds of food safety risks and/or incidents in a day, collating all the data received on a daily basis into a workable database can prove to be challenging. This is where Text AI comes in: Text AI and other such technologies allow food professionals to store and collate food safety incident data on a real time basis and organize it in such a way that recognizable statistics or data can be extracted from it in a fraction of time. This data extraction, for example, allows food professionals to make accurate predictions in regards to the next big food safety incident to look out for in their food spaces. This kind of data can also be applied to collating customer feedback and generating statistics which may prove helpful in terms of organizing a training program or even help chefs upgrade their menu items.

Building on these aspects, there are various kinds of AI software out in the market that can be used to target food and beverage employees and streamline their training sessions, such as:

Fujitsu’s Computer Vision Model

One of the more difficult aspects of a food safety professional’s job is on-the-job training which needs to be conducted for employees regarding personal hygiene, i.e., handwashing, uniform upkeep, etc.  Predicting these challenges, Japanese IT giant Fujitsu is developing a software designed to observe handwashing techniques of food workers and alert supervisors when an effective handwashing procedure is not being followed. The software also has features such as a physical display monitor demonstrating each step of the handwash procedure as it is being done by a food worker.


Intenseye is a company that uses Vision AI to ensure that food workers are kept safe from workplace and food safety related accidents; one of the more interesting aspects of this technology is the ability to identify whether a worker is wearing appropriate PPE. This technology can be used to monitor food workers in real time, and by extension, be used as a learning tool to demonstrate to food workers what kind of personal hygiene policy aspects are expected out of them, by using real-life examples of their colleagues in question.


A great example of using AI tools to demonstrate hand washing techniques is Pathspot, an AI technology that recognizes the number of contaminants found on a food worker’s hands. This technology can be used as an additional learning tool when training food workers on essential food safety and hygiene aspects such as handwashing, cleaning and sanitization techniques as well.

Thus, it is obvious that technological advancements are an inevitable part of the food industry; the integration of AI technology to aspects of the food industry such as workforce training can help streamline the process throughout a facility, ensuring that all food workers are trained in food safety and hygiene in an effective manner, thereby subsequently giving rise to a healthy Food Safety culture within the workplace, a task that as all food safety professionals know, is notoriously difficult to accomplish. Taking all these factors into consideration, it is thus imperative that food business owners eventually incorporate AI technology into their facilities in order to step up to the place and ensure business continuity in the long run.