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Sensor Projects with Raspberry Pi (Record no. 62387)

MARC details
000 -LEADER
fixed length control field 03861nam a22004935i 4500
001 - CONTROL NUMBER
control field 979-8-8688-0464-9
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251030112848.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240810s2024 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9798868804649
-- 979-8-8688-0464-9
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/979-8-8688-0464-9
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TS171.57
072 #7 - SUBJECT CATEGORY CODE
Subject category code UB
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM067000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UBM
Source thema
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Guillen, Guillermo.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
9 (RLIN) 82192
245 10 - TITLE STATEMENT
Title Sensor Projects with Raspberry Pi
Medium [electronic resource] :
Remainder of title Internet of Things and Digital Image Processing /
Statement of responsibility, etc. by Guillermo Guillen.
250 ## - EDITION STATEMENT
Edition statement 2nd ed. 2024.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Berkeley, CA :
Name of producer, publisher, distributor, manufacturer Apress :
-- Imprint: Apress,
Date of production, publication, distribution, manufacture, or copyright notice 2024.
300 ## - PHYSICAL DESCRIPTION
Extent XVIII, 241 p. 168 illus.
Other physical details online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
490 1# - SERIES STATEMENT
Series statement Maker Innovations Series,
International Standard Serial Number 2948-2550
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Chapter 1. Theoretical Fundamentals -- Chapter 2. Alarm System -- Chapter 3. Gas Leak Alarm -- Chapter 4. Weather Station -- Chapter 5. Digital Image Processing with Python and OpenCV. - Chapter 6. Animations With Python And Pygame -- Chapter 7 -- Homemade Spectrometer -- Chapter 8 -- Object Classification Using Edge Impulse on Raspberry Pi.
520 ## - SUMMARY, ETC.
Summary, etc. Use Python to develop Rasperry Pi projects to solve common digital image processing and IoT problems. Using a free IoT server you’ll tackle fundamental topics and concepts behind theses two areas. This second edition includes new content on Artificial Intelligence and updated sensor guidance to help you better explore virtual animations, create a homemade spectrometer, and master object classification with Edge Impulse. Start by creating a system to detect movement with a PIR motion sensor and a Raspberry Pi board. Use the MQ2 gas sensor and a Raspberry Pi board as a gas leak alarm system to detect dangerous explosive and fire hazards. Then train your system to send the captured data to the remote server ThingSpeak. You’ll also develop a weather station with your Raspberry Pi. Using the DHT11 (humidity and temperature sensor) and BMP (barometric pressure and temperature sensor) in conjunction with ThingSpeak and X, you can receive real time weather alerts from your own meterological system! Spectral sensers used with the Raspberry Pi include the AS7262 (six colors), and AS7263 (near infrared) for the construction of a filter spectrometer, sensing colored solutions, and assessing plant foliage health. Finally, expand your skills into the popular machine learning world of digital image processing using OpenCV and a Pi. Make your own object classifiers and finally manipulate an object by means of an image in movement. This skillset has many applications, ranging from recognizing people or objects, to creating your own video surveillance system. With the skills gained from Sensor Projects with Raspberry Pi, you'll be well-equipped to explore other applications in mobile development and electrical engineering as well. .
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 68064
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 68065
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9798868804632
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9798868804656
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9798868810855
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Maker Innovations Series,
International Standard Serial Number 2948-2550
9 (RLIN) 68066
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/979-8-8688-0464-9">https://doi.org/10.1007/979-8-8688-0464-9</a>
912 ## -
-- ZDB-2-CWD
912 ## -
-- ZDB-2-SXPC

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