How is Computer Vision Improving QSR Operations?

By Liz Oz • May 05, 2022

happy customer receiving drive thru order

In recent years, computer vision has exploded in popularity across a variety of industries. One of these industries is quick service restaurants (QSR). Computer vision improves customer experience and in-store and drive-thru operations. 

In this article, we'll take a closer look at how computer vision is benefiting QSR and explore some of its most successful applications. We'll also discuss some challenges that come with implementing computer vision and offer advice on how to overcome them. If you're interested in learning more about how CV benefits fast-food chains, read on!

What is Computer Vision?

Computer vision is a subset of artificial intelligence (AI) that enables computers to detect and identify objects in an environment the same way humans do. Computer scientists have used research on human neural networks to replicate human sight in computer vision systems. They created artificial neural networks built on deep learning and machine learning to process this information. 

For QSR, camera systems can monitor both the interior and exterior of a store to gather data in real-time about all aspects of the business. CV applications can detect and track specific objects like people, cars, ingredients, and prepared menu items. These objects and actions taken by people are then automatically analyzed by AI. This provides instantaneous business intelligence that can be acted on immediately and drive long-term operational improvement. 

The Impact of Computer Vision on Quick-Serve Restaurants 

Computer vision applications for QSR have the potential to improve customer satisfaction, employee productivity, food preparation, and food safety and quality. However, before QSRs can take full advantage of these benefits, there are a few challenges that need to be addressed.  

  • Data Privacy – customers expect their private information to be kept secure. The images recorded and stored by computer vision present a potential security risk. But, facial blurring applications resolve this issue, keeping customers’ identities private while still providing real-time data.
  • Cost of Implementation – computer vision is not a small investment, so taking the time to ensure it presents positive ROI for a QSR is essential. 
  • Customer Acceptance – not all customers are comfortable with the idea of being on camera even if it benefits them. It is vital that customers know the reasons for using computer vision and that their data will not be used for marketing purposes. 

Despite these challenges, computer vision is expected to have a major impact on the quick service restaurant industry. It is predicted that by 2025, the restaurant management software market, including AI and CV, will grow by almost 15% annually and reach $6.95 billion by 2025. A computer vision platform like alwaysAI offers affordable and easily accessible AI solutions for the QSR space. A platform eliminates the large cost of developing a system in-house and provides the flexibility to update and adapt applications as needs change.

computer vision detects cars in drive through

How is Computer Vision Improving the QSR Customer Experience?

Quick service restaurant managers are always looking for ways to improve customer experience. After all, happy customers are more likely to come back and spend more money. Here are some ways computer vision keeps customers satisfied. 

  • Analyzing Store traffic – CV can track traffic throughout a restaurant, noting trends and peaks. This information can be used to make informed staffing decisions so more staff is on shift when a restaurant is busiest. 
  • Minimizing wait times – Customers expect to quickly order and receive their food at quick service restaurants. CV provides real-time data to streamline this process and meet immediate needs. For example, if a drive-thru is backed up, personnel can be moved around to help out. 
  • Maintaining the dining area - CV applications trained to detect objects like trays, cups, wrappers, and food boxes can identify when trash has been left at tables or when trays are stacking up. An alert can be set so that if waste items have been left for longer than 30 seconds, staff are alerted to check the dining room. 
  • Personalized recommendations - CV can create personalized dining experiences. It can identify a customer and provide them with a list of recommended items. The drive-thru experience can be improved by identifying the customer profiles of people in cars and automatically suggesting menu items or specific promotions to them. 

computer vision used to detect customers in a quick service restaurant

Computer Vision for Efficient, High-Performing Kitchens 

Efficiency is the key to success for QSR operations. Computer vision can improve kitchen productivity and overall speed of service. 

  • Inventory management – CV can identify and track ingredients used, making sure inventory is always up-to-date. This also prevents waste by knowing exactly how much to order for menu items. 
  • Order accuracy - CV can streamline the entire preparation process and ensure orders are delivered accurately. Humans tend to either be accurate or fast, rarely both. Computer vision can ensure accuracy without slowing down the preparation process. It can make sure orders are packaged correctly and then delivered to the right customers. 
  • Food safety - CV allows for potential safety issues to be identified and corrected before they become a problem. If a worker is not wearing gloves, computer vision can send an alert to the manager. CV can track if certain items or ingredients have been left out too long and need to be thrown away. 
  • Food quality - CV can be used to check food quality, identifying spoiled items or foreign objects in food. CV can make sure the food is being prepared the same way every time, increasing brand consistency. 
  • Track ordering trends - CV can predict customer demand. If a particular type of food is becoming popular, production can be adjusted accordingly. This helps minimize food waste by instructing kitchen staff on what to make and how much to make at different times of the day. 

How Can Investment in Computer Vision Drive ROI? 

Real-time data is the key to understanding how to improve your QSR operations. Computer vision is the easiest way to obtain this data and drive massive ROI. CV provides data to quantify the customer experience and find solutions to problem areas. For example, wait times are frequently an issue for quick service restaurants. The use of computer vision may reduce wait times, increasing throughput and profit. 

Although the cost of implementing a CV system may seem daunting, it provides quick service restaurants with the possibility of major savings. CV reduces food waste, increases staff efficiency, and streamlines inventory procedures. Each of these benefits offers substantial cost reductions. The most cost-effective way to implement CV in restaurants is with a computer vision platform like alwaysAI. alwaysAI offers businesses a seamless and powerful platform that helps businesses easily build and deploy computer vision applications on the edge.  

To learn more about how alwaysAI CV drives ROI for QSR, contact us for a free demo. 

Download our QSR solutions brief to learn more about these exciting applications! 

By Liz Oz • May 05, 2022

Developer stories to your inbox.

Subscribe to the Developer Digest, a monthly dose of all things code.

You may unsubscribe at any time using the unsubscribe link in the digest email. See our privacy policy for more information.

alwaysAI Ad
stylized image of a computer chip

Sign up today and start your project

We can't wait to see what you'll build!