Cafeteria Management System and computer vision

Computer Vision Introduction:

Cafeteria Management System: Since the 1960s humans have been fascinated by the idea of creating a system that moves, thinks and responds to the environment the same way a human does like a computer vision.

Basically, the desire is to create a machine that can replicate a human being. But for this to happen these machines need to see the world the way we do.

One such example is to have a system that can perform all the functions of a human eye. This requirement created a new field of science -‘Computer Vision’. In this system, the computer has to perceive, identify and process the image in the same way a human eye does.

It mainly concerns itself with an artificial system that extracts information from an image or a series of images or footage from multiple cameras.

Computer vision involves three basic steps:

  • Image Acquisition
  • Image Processing
  • Image Analysis

Image acquisition involves getting data from a still camera or a video camera.

The processing step involves the conversion of the image or the part of the image into a useful or meaningful form.

The last step analysis involves decision making that is usually based on the converted form of image and the requirement in hand.

Cafeteria Management System:

In this modern lifestyle where a man is always in a dearth of time, wasting time waiting for food is not something that one looks forward to. This is the problem that our Cafeteria Management System aims to solve.

It counts the number of vacant chairs and tables in a cafeteria and provides this information to the user so that they are aware of the availability of chairs before they come into the cafeteria.

Not only that, but it also accumulates this data over time so that an analysis can be performed to determine during which time of the day the cafeteria is swamped with people. so, that a person can plan their day accordingly to save their time.

This system can improve the productivity of any office as the employees won’t have to wait for their turn in the cafeteria. Rather they can just check the availability of seat before coming to the cafeteria and save themselves some time.

It can also be useful for the apps that pre-books tables in a restaurant as they will not have to rely on the hotel management to update their tally every time a customer walks in.

Cafeteria Management System Design

Cafeteria Management System requires multiple cameras depending upon the size of the cafeteria, a server for processing and local area network.

The cameras are placed in such a way that they cover all of the cafeterias. These cameras are connected to local area network which connects them to the server where all the processing happens.

Processing of the system undergoes three steps:

Data Acquisition: This system uses multiple cameras to cover all the cafeteria that is connected to the server using routers and switches. These cameras are processed by the server using the Round Robin Scheduling algorithm.

Here the feed from the first camera is processed then the next camera is processed and so on till the feed from the last camera is processed. After which it circles back to the first camera.

Data Processing: First the system uses neural networks to get the features associated with the entities like chair and table. Then using the learning algorithm it determines the number of entities present in the cafeteria.

Data Analysis: After the determination of the number of entities it identifies the vacant as well as occupied entities and puts the tally for display as well as stores it in the database.

Computer vision and cafeteria management system 2

Fig: Architectural Representation

Way Ahead

Since all the industries in this world are in a race to be the best at what they do. They, cannot afford their employees wasting time waiting for their chance to have lunch just cause the cafeteria is full.

This is where our Cafeteria Management System will help. Along with the currently vacant seat status, the system will also tell the user when the cafeteria will be empty so that they can plan their day accordingly.

This will also help the management team of the cafeteria as they will know when the rush hour is and make suitable adjustments.

 

Read also:

Video Analytics and its scope in solving real-world problems

Video Analytics: Applications in Industrial Operations Optimisation.

Face Recognition | Facial Recognition using Deep Learning

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