How to make the supermarket shopping more efficient?
Question:

  

 

 

PBL Design:How to make the supermarket shopping more efficient?

 

 

 

Introduction and Problem

 

 

 

It’s not uncommon in our daily life to see people wait in a long line in supermarkets to check out. Sometimes you go shopping with joyful mood on weekends but get annoyed by the long queues. Sometimes you just want to grab a sandwich but get stuck in the crowds at the check-out counter. To deal with the low efficiency of the traditional supermarket checking out process, unmanned systems emerge as the time require. However, the present solutions roughly are all limited by technology defects or high cost. Therefore, you are supposed to figure out one way to solve the problem with mature technology and reasonable cost so as to promote it widely. The future of supermarket shopping is in your hand now.

 

 

 

 

Guidelines for students

 

 

 

The students are divided into groups of 4-5 people. The task is divided into the following stages.

 

1. The first stage: identify a problem and form a preliminary idea (duration: 5 days)

 

Students need to find a problem from real world. Each group member put forward a solution and then choose the best idea by discussion. Through this process, students can develop their innovation ability and critical thinking ability.

 

 

 

2. The second stage: do market research (duration: 5 days)

 

Students need to do market research to know whether there are similar products and the market share of similar products. Market research can be conducted in three ways. One is to find relevant materials and data on the Internet, the second is field research, and the third is questionnaire survey. Through market research, students can understand the competitiveness of their products in the market and estimate the market share.

 

 

 

3. The third stage: build a model (duration: 10 days)

 

Students need to draw or build a model of the product Including the specific structure of the product. Through this process, students can improve their hands-on ability and creativity.

 

 

 

4. The fourth stage: production (duration: 20 days)

 

Students need to make products according to their own designs. In this process, there may be some errors, students need to continue to improve.

 

 

 

5. The fifth stage: Product presentation and group evaluation (duration: 1 day)

 

The last stage is product presentation. Before presentation, students need to make a preliminary estimate of their products' market prospects and estimated profits. Then students should express their innovation and market value of their products to all other groups. Other groups act as venture capital firms and give decisions about whether to invest and how much to invest. This process can exercise students' evaluation ability and expression ability.

 

 

 

 

 

Additional Information

 

 

 

Here are some technologies that may use.

 

 

 

1. Barcode or QR code scanning

 

Barcode or QR code scanning utilizes the concept of "0" and "1" bitstreams that form the basis of the computer's internal logic in code compilation, using several geometric shapes corresponding to binary to represent information. See the source imageSee the source image

 

These barcodes have been used throughout our lives, and we are already familiar with them. They are usually composed of black and white blocks with widely varying reflectance and only have the unique meaning.

 

Our commonly used bar code reading devices can be divided into different reading principles:

 

(1) Linear CCD Imager

 

In the CCD linear imager, an LED is used to illuminate the barcode, and tiny CCD sensors are aligned in a single row to read and decode the light reflected off linear barcodes. The device is like a camera that takes pictures having just a single row of pixels. Being linear, these devices could not read 2D barcodes.

 

See the source image

 

This kind of equipment is now often seen in supermarkets, libraries, etc.

 

(2) Image Reader

 

The barcode image is taken by the area array CCD camera to analyze and decode the barcode image, and the one-dimensional barcode and all types of two-dimensional barcodes can be read. This principle is also commonly used by our mobile phones.

 

 

 

2. RFID

 

Radio Frequency Identification (RFID) refers to a wireless system comprised of two components: tags and readers. The reader is a device that has one or more antennas that emit radio waves and receive signals back from the RFID tag.

 

See the source image

 

Tags, which use radio waves to communicate their identity and other information to nearby readers, can be passive or active. Passive RFID tags are powered by the reader and do not have a battery. Active RFID tags are powered by batteries.

 

RFID tags can store a range of information from one serial number to several pages of data. Readers can be mobile so that they can be carried by hand, or they can be mounted on a post or overhead. Reader systems can also be built into the architecture of a cabinet, room, or building.

 

See the source image

 

 

 

3. Image recognition

 

The major steps in image recognition process are gather and organize data, build a predictive model and use it to recognize images.

 

(1)    Gather and Organize Data

 

The human eye perceives the image as a set of signals that are processed by the visual cortex in the brain. Image recognition tries to mimic this process. Computer perceives an image as either a raster or a vector image. Raster images are a sequence of pixels with discrete numerical values for colors while vector images are a set of color-annotated polygons, which is showed below.

 

Vector vs Raster image

 

To analyze images the geometric encoding is transformed into constructs depicting physical features and objects. These constructs can then be logically analyzed by the computer. Organizing data involves classification and feature extraction. The first step in image classification is to simplify the image by extracting important information and leaving out the rest. For example, in the below image if you want to extract cat from the background you will notice a significant variation in RGB pixel values.

 

Image classification process

 

However, by running an edge detector on the image we can simplify it. You can still easily discern the circular shape of the face and eyes in these edge images and so we can conclude that edge detection retains the essential information while throwing away non-essential information. Some well-known feature descriptor techniques are Haar-like features introduced by Viola and Jones, Histogram of Oriented Gradients (HOG), Scale-Invariant Feature Transform (SIFT), Speeded Up Robust Feature (SURF) etc.

 

(2)    Build a Predictive Model

 

After converting an image to a feature vector, now we should take this feature vector as input and outputs of a class label (e.g. cat or background/no-cat like below). we need to train our classification algorithm by showing thousands of cat and non-cat images. And then we use neural networks to build a predictive model. The neural network is a system of hardware and software similar to our brain to estimate functions that depend on the huge amount of unknown inputs. A neural network is an interconnected group of nodes, which would also require one learning algorithm. After tons of inputs, we will get a database which is big enough to build a predictive model.

 

Images for training

 

(3)    Recognize Images

 

After completing the above two steps, it is very simple to identify the image. For example, if we want to judge whether the new picture is a cat, all we need to do is train a classifier that can take the measurements from the new test image and tells us about the closest match with a cat. The result of the classifier is the ‘Cat’ or ‘Non-cat’.

 

Expectation & Requirements

 

 

 

1. Identify problems from real world and propose practical solutions.

 

2. Each group member actively participates in the discussion, expresses the idea and criticizes each other.

 

3. Form a complete plan and express ideas logically.

 

4. Divide the labor according to the specialty of the team members.

 

5. Conduct detailed market research.

 

6. Express your creativity and market value to venture capital firms.

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