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_aGuillen, Guillermo. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _982192 |
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| 245 | 1 | 0 |
_aSensor Projects with Raspberry Pi _h[electronic resource] : _bInternet of Things and Digital Image Processing / _cby Guillermo Guillen. |
| 250 | _a2nd ed. 2024. | ||
| 264 | 1 |
_aBerkeley, CA : _bApress : _bImprint: Apress, _c2024. |
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_aXVIII, 241 p. 168 illus. _bonline resource. |
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_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aMaker Innovations Series, _x2948-2550 |
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| 505 | 0 | _aChapter 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 | _aUse 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. . | ||
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_aMakerspaces. _968064 |
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| 710 | 2 | _aSpringerLink (Online service) | |
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_iPrinted edition: _z9798868804632 |
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_iPrinted edition: _z9798868804656 |
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_aMaker Innovations Series, _x2948-2550 _968066 |
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| 856 | 4 | 0 | _uhttps://doi.org/10.1007/979-8-8688-0464-9 |
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