How to run a restaurant via neural networks ????

How to run a restaurant via neural networks..... Sound's like a funny idea right? Yeah, if this idea was pitched back in 70's, people would call me nuts. But in our current generation, A simple RNN is enough to run a food menu in Restaurants.

But in order to decide where it’s better to open a restaurant and how much money it could bring, you have to analyze multiple data. Artificial intelligence can easily do it. Neural networks process a huge amount of data and give recommendations to those who are willing to open a cafe.?

Crowd analysis:

Nowadays a bunch of companies are trying to implement ideas with the help of artificial intelligence. For example, in 2016 Placer.ai was founded in the US. It was meant to analyze pedestrian traffic in order to advise retailer what and where to place.?

Smart pizzeria:

The most popular example is Zume Pizza. The company didn’t rent a space for a pizzeria. Instead, cooks made food right in trucks. Zume pizza was seeking to make an intelligent platform that could identify where and when it’s going to be the highest demand for a pizza. Neural networks predicted where the car should go and when to turn on ovens to keep pizzas hot. However, not so many people have used the service, that’s why now the company sells protective masks.

Restaurant aid:

There is also a Russian company - Foodcast.ai. By means of neural networks, it analyzes loads of factors that affect restaurant demand: holidays, the weather, days off, etc. The most unexpected factor is abrupt drop in temperature. If it gets tangibly colder, the demand grows: home delivery gets more relevant.?

Besides, the system based on artificial intelligence helps a restaurant allocate resources properly. Neural networks answer essential questions: who cooks for clients in the restaurant, what number of waiters is needed at rush hour, and how many products are necessary to buy.

3 years ago McDonalds bought a startup Dynamic Yield that was engaged in technology for personal data analysis. The system was implemented in Miami restaurants right away. The algorithm analyzed the weather, traffic jams, the events held nearby, and collected data of sales.

Kiosks that Personalize Customer Experiences?

While ordering kiosks have become fairly common in a variety of restaurants, there are some eateries that are taking that experience a step further. Take KFC, for example, which is experimenting with kiosks with facial recognition technology that can recognize repeat visitors and tailor their experience based on their past orders and preferences.?

While facial recognition might not be accessible for all restaurants, there are many ways you can use AI to help personalize the dining experience for your guests. Online ordering and digital marketing are two places where restaurants are more commonly collecting guest data, and then using that data to provide personalized service, from dish recommendations to targeted marketing.

Optimized Delivery?Processes

Food delivery exploded in popularity during the COVID-19 pandemic, and that trend doesn't look like it's slowing down any time soon. That's why many restaurants are turning to AI technology to help them optimize their delivery processes.

AI can help delivery drivers find the best and fastest routes for making multiple deliveries in one trip, utilizing map data to avoid traffic and other hazards. AI can also keep guests in the loop about their orders—like how delivery platforms like DoorDash and Uber Eats allow customers to follow along on a map, and send them texts when their order status is updated

Cleaning and Maintenance

In food processing industries, proper cleaning and maintenance of processing tools are very much essential. Such a task can be easily handled by AI-based systems. For implementing this, various sensors and cameras are deployed to perform the task. One product of Whitwell and Martec muscularly suffers that it can decrease to only 50%, which permits large efficiency and a lesser amount of time. Presently, Martec is trying to justify its AI-based cleaning place model. For this approach, Martec employs ultrasonic sensing imaging methods and optical fluorescence methods to cultivate the obtained information to the AI system development. It measures the remaining amount of food and microbial debris inside the machine. After releasing the entire report of the testing phase, the system will take stand.

The above methodologies are used in various high end restaurants and by 2030, we can expect mobile robots to take over various automated works.