Download Home Automation with Intel Galileo, by Onur Dundar

Download Home Automation with Intel Galileo, by Onur Dundar

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Home Automation with Intel Galileo, by Onur Dundar

Download Home Automation with Intel Galileo, by Onur Dundar

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About the Author

Onur Dundar Onur Dundar is a software engineer who graduated from the Computer Engineering Department of Bogazici University. He started working on embedded systems while he was at the university, and in his senior year project, he worked with wireless sensor networks for security and health monitoring. Onur started his career at JPMorgan Chase & Co. Then, he worked at Intel Corporation for 4 years as a software application engineer. He has specialized in embedded Linux and mostly worked on IPTV platforms, Android, as well as IoT platforms, such as Intel Galileo and Edison, and has developed applications for them. He has also helped software developers enhance their applications on these platforms. He has attended many conferences and developer events to introduce Intel Galileo and Edison. He developed the first application and wrote the public collaterals of Intel Edison when he worked at Intel Corporation. Onur is continuing his career at Invent Analytics, implementing algorithms for data analytics.

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Product details

Paperback: 179 pages

Publisher: Packt Publishing - ebooks Account (March 30, 2015)

Language: English

ISBN-10: 1785285777

ISBN-13: 978-1785285776

Product Dimensions:

7.5 x 0.4 x 9.2 inches

Shipping Weight: 15 ounces (View shipping rates and policies)

Average Customer Review:

5.0 out of 5 stars

2 customer reviews

Amazon Best Sellers Rank:

#4,977,635 in Books (See Top 100 in Books)

"A very nice book to follow up basic home automation projects and develop a complex home gateway on a Linux platforms. All code is working well and easily portable to raspberry pi and other platforms. I recommend the book both people who are are into a professional smart home project and DIY projects."

Great book, good content coverage and the best is I managed to run the examples on Raspberry Pi without much effort!

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