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E-book: Raspberry Pi Retail Applications: Transform Your Business with a Low-Cost Single-Board Computer

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  • Format: EPUB+DRM
  • Pub. Date: 14-Mar-2022
  • Publisher: APress
  • Language: eng
  • ISBN-13: 9781484279519
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Raspberry Pi Retail Applications: Transform Your Business with a Low-Cost Single-Board ComputerLarger Image
  • Format: EPUB+DRM
  • Pub. Date: 14-Mar-2022
  • Publisher: APress
  • Language: eng
  • ISBN-13: 9781484279519
Other books in subject:

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Increase productivity and lower the operating cost of your business by automating crucial business processes with the Raspberry Pi. After completing this book's projects you'll be able to determine the best way to quickly apply automation to existing systems and processes in your retail outlet with Raspberry Pi.   

You’ll start by composing ideas to transform your business, and then gain practical, accessible methods for executing them. Find real-world ways to implement tech solutions to accelerate the growth of your business, and navigate the ever-changing landscape of retail automation with this book. Then see what automation can and cannot do at the current level of technical progress for retail businesses. By comparing the efficiency of machines with manual labor, you’ll be able to assess how open-source hardware performs in lowering operating costs and identify business components that can be improved with automation. 

Raspberry Pi Retail Applications features projects that are easy to dive into and will function readily in your day-to-day business right now.     

What You'll Learn
  • Identify business components that can be improved with automation  
  • Combine the existing array of Raspberry Pi hardware options to build customized solutions  
  • Implement tech ideas in a practical retail environment to reduce cost and streamline your business processes  
Who This Book Is For

Small and medium business owners or technology officers looking for solutions to increase efficiency, lower operating costs, and drive up profits for their retail companies with automation. Familiarity with open-source hardware and programming skills is helpful, but not necessary.  
About the Authors ix
About the Technical Reviewer xi
Chapter 1 Understanding the Applications of Automation in Retail 1(18)
What Is Industry 4.0?
2(3)
What Is the Internet of Things (IoT)?
5(5)
Which Technologies Make the Internet of Things More Accessible in the Retail Industry?
5(3)
Amazon Go Grocery Store: Ambitiously Implementing Automation
8(2)
Why Choose a $35 Single-Board Computer to Automate a Retail Business?
10(2)
Identify the Targets for Business Automation
12(7)
To Automate or Not to Automate?
16(3)
Chapter 2 People Counting 19(22)
Problem Overview
19(1)
The Business Impact
19(1)
Related Knowledge
20(4)
Computer Vision and Its Applications
20(4)
Approaches to Object Detection
24(2)
Implementing Object Detection
26(13)
Install a 64-bit Raspberry Pi OS on Raspberry Pi 4
27(2)
Install the Necessary Packages
29(3)
Execute People Counting Code with a Pretrained MobileNet SSD Model
32(3)
Train and Optimize Your Own Neural Network Model
35(4)
Pro Tips
39(1)
Summary
40(1)
Chapter 3 Vending Machine 41(30)
Problem Overview
41(3)
Business Impact
44(1)
Related Knowledge
45(8)
Decide on PCB Manufacturer Beforehand
49(1)
Determine the Interfaces You Need
50(1)
Look at Third-Party Open Source Designs for Your elements
50(1)
Look at How Other People Have Solved the Same Problem
51(1)
Decide on Your Form Factor
52(1)
Determine the Location of Connectors and Headers
52(1)
Take Special Care of Heatsinks and Cooling Elements
52(1)
Implementation
53(15)
Implement Servo Control with Raspberry Pi 4
54(4)
Implement a Simple Web Server with Flask
58(6)
Add a PayPal Payment Processor
64(4)
Pro Tips
68(2)
Summary
70(1)
Chapter 4 Interactive Touchscreen Directory 71(22)
Problem Overview
71(2)
Business Impact
73(2)
Related Knowledge
75(4)
Implementation
79(11)
Basic Tkinter Usage
79(2)
Build an Interface with the PAGE GUI Generator
81(9)
Pro Tips
90(1)
Summary
91(2)
Chapter 5 Voice Interaction Drive-through Self-service Station 93(30)
Problem Overview
93(3)
Business Impact
96(3)
Related Knowledge
99(9)
How Does Deep Learning Work with Speech Recognition?
100(2)
Online Speech-Recognition Service Providers
102(3)
Offline Speech Recognition Frameworks
105(3)
Implementation
108(12)
Use the Pretrained Picovoice Model for Lights Control
109(3)
Train a New Speech-to-Intent Model for Ordering Fast Food
112(5)
Combine the New Speech-to-Intent Model with the Text-To-Speech Engine
117(3)
Pro Tips
120(1)
Summary
121(2)
Chapter 6 Employee Attendance Management System 123(30)
Problem Overview
123(3)
Business Impact
126(3)
Related Knowledge
129(6)
The Fingerprint Sensor
131(1)
The PIR Motion Sensor
132(2)
The Software for Interfacing with the Sensor and Storing the Data
134(1)
Implementation
135(13)
Wire the Modules
135(4)
Install the Software and Register the Fingerprints
139(4)
Combining the Motion Sensor with the Fingerprint Sensor
143(5)
Pro Tips
148(4)
Using a SQL Database
148(1)
What Is SQL?
148(1)
SQL vs. Excel
149(1)
What Is SQL in the Cloud?
149(1)
A Dedicated Raspberry Pi 4 Hat with a Fingerprint Sensor
150(2)
Summary
152(1)
Chapter 7 Advertisement Display 153(22)
Problem Overview
153(1)
Business Impact
154(3)
Related Knowledge
157(4)
What Is (Docker) Container?
158(1)
Container Orchestration
158(1)
Balena.io for Container Orchestration
159(2)
Implementation
161(11)
Install BalenaOS
161(3)
Deploy Container with Balena Dash to Your Device
164(7)
Set Up the Dashboard to Display PhotosNideos
171(1)
Pro Tips
172(2)
Summary
174(1)
Chapter 8 Cluster for a Web Application Hosting 175(36)
Problem Overview
175(1)
Business Impact
176(3)
Related Knowledge
179(5)
Main Benefits of Running a Cluster with Kubernetes
181(2)
Deploying Kubernetes on the Edge with MicroK8s
183(1)
Implementation
184(23)
Install Ubuntu Server 20.04 on Two Raspberry Pi 4s
184(5)
Install MicroK8s on Two Raspberry Pi 4s Running Ubuntu Server 20.04
189(1)
What Version of Kubernetes Is Being Installed?
190(1)
Deploy a Web Application to a Cluster
191(16)
Pro Tips
207(2)
Summary
209(2)
Chapter 9 Summary and Tips on Practical Implementation 211(28)
Successful Implementations
212(10)
Raspberry Pi Vending Machine
212(3)
Interactive Touchscreen Directory for a Smart City
215(2)
Raspberry Pi as a Retail Product Display
217(2)
A Multimedia Toolkit for Museums, Visitor Centers, and More Running on the Raspberry Pi
219(1)
Pendulum Wave Machine: A Museum Exhibit
220(1)
Raspberry Pi 4 Cluster for Hosting a Raspberry Pi 4 Website
221(1)
Technical Know-Hows
222(7)
Use Virtual Network Computing (VNC) to Remotely Control Everything You Want to Execute on the Raspberry Pi
222(2)
IoT Integration Platform for the People-Counting Project
224(2)
Microphone Options for Speech Recognition
226(1)
Cluster Server Carrier Board
227(2)
Retail Business Digitalization
229(10)
Index 239
Elaine Wu specializes in business partnerships and marketing in various tech industries, from software to embedded hardware. She is currently the marketing and partnership manager at Seeed (an open-source AIoT hardware platform) where she focuses on the global IoT solution ecosystem, making technology accessible for all. At Seeed, by aligning with partners and best hardware, she believes and strives on the path of the most reliable hardware platform, empowering everyone to achieve their digital transformation goals. She was also leading community partnerships, content marketing, new products' go-to-market strategies at Seeed before 2021. Elaine is also an active article contributor on a variety of industries topics, including but not limited to SBCs, microcontrollers, ML/AI, robotics, and SLAM. 



Dmitry Maslov works professionally in applied machine learning and robotics. Hes spearheaded a variety of machine learning projects, both for previous employers and as a freelancer. Proficient in Python and C/C++, Dmitry has an excellent knowledge of ROS and ROS-i. He speaks four languages with professional fluency in three. Dmitry is the owner of Hardware.ai, a YouTube channel where he publishes videos on creating intelligent systems with machine learning and ROS on single-board computers. 
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