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

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Elaine Wu Raspberry Pi Retail Applications: Transform Your Business with a Low-Cost Single-Board Computer
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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 books projects youll be able to determine the best way to quickly apply automation to existing systems and processes in your retail outlet with Raspberry Pi.
Youll 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, youll 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 Youll 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.

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Book cover of Raspberry Pi Retail Applications Elaine Wu and Dmitry Maslov - photo 1
Book cover of Raspberry Pi Retail Applications
Elaine Wu and Dmitry Maslov
Raspberry Pi Retail Applications
Transform Your Business with a Low-Cost Single-Board Computer
Logo of the publisher Elaine Wu Shenzhen China Dmitry Maslov Shenzhen - photo 2
Logo of the publisher
Elaine Wu
Shenzhen, China
Dmitry Maslov
Shenzhen, China
ISBN 978-1-4842-7950-2 e-ISBN 978-1-4842-7951-9
https://doi.org/10.1007/978-1-4842-7951-9
Elaine Wu, Dmitry Maslov 2022
This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This Apress imprint is published by the registered company APress Media, LLC part of Springer Nature.

The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A.

Any source code or other supplementary material referenced by the author in this book is available to readers on the Github repository: https://github.com/Apress/Raspberry-Pi-Retail-Applications. For more detailed information, please visit http://www.apress.com/source-code.

Table of Contents
About the Authors
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 an active article contributor at Seeed blog 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. He has 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.

About the Technical Reviewer
Massimo Nardone
has more than 22 years of experience in security webmobile development and - photo 3
has more than 22 years of experience in security, web/mobile development, and cloud and IT architecture. His true IT passions are security and the Android platform.

He has been programming and teaching others how to program with Android, Perl, PHP, Java, VB, Python, C/C++, and MySQL for more than 20 years.

He holds an MS in Computing Science from the University of Salerno, Italy.

He has worked as a project manager, software engineer, research engineer, chief security architect, information security manager, PCI/SCADA auditor, and senior lead IT security/cloud/SCADA architect for many years.

The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2022
E. Wu, D. Maslov Raspberry Pi Retail Applications https://doi.org/10.1007/978-1-4842-7951-9_1
1. Understanding the Applications of Automation in Retail
Elaine Wu
(1)
Shenzhen, China

What are some of the most pressing issues that owners of small- and medium-sized businesses currently face?

These concerns include the growing costs of supply chains, increasing costs of labor and capital, and increased spending on equipment upgrades and business strategy re-evaluations necessitated by competitors and changes in the business environment. It is very important for small business owners to have solid and practical solutions for saving money on manufacturing processes and labor. They need to increase efficiency and widen the margin in both directionsby eliminating unnecessary expenses and by increasing revenues.

With the development of Industry 4.0 , the automation of business retail applications has been gaining interest and popularity. Automation in retail applications reshapes the business models, from the backend supply chain to the frontend of business management, which not only helps business owners save on labor costs, but also helps with efficiency. With automation, customers can have a better experience in an easier way.

What Is Industry 4.0?
Industry 4.0, the fourth industrial revolution, refers to the ongoing digital transformation of industries, such as combining human machine interface (HMI) and cloud data to build digital solutions to make the industrial model more efficient (see Figure ). Compared to the preceding industrial revolutions, Industry 4.0 focuses on the digital, information-driven interconnectivity among people, devices, and systems, which enables enhanced decision making in industrial processes. At the same time, due to this digital transformation, customer expectations are rising. Retailers are striving to adapt and survive in a competitive environment. With Industry 4.0, a lot of new skills must be added to the development and manufacturing process , such as machine learning capabilities, edge computing, and remotely visualized dashboards using cloud businesses. Retail owners at the same time must use new technology to make solid decisions about hardware and software.
Figure 1-1 The four industrial revolutions Source Spectral Engines McKinsey - photo 4
Figure 1-1

The four industrial revolutions . Source: Spectral Engines

McKinsey & Company, COVID-19: An Inflection Point for Industry 4.0 is a survey of more than 400 global manufacturing companies. A full 94% of the respondents said that Industry 4.0 helped them to maintain operations during COVID-19 (starting from the end of 2019), and 56% of the respondents said that digitization was crucial to responding to the pandemic. See Figure .
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