WickeyTips

I'm sharing this with you because I have faced some difficulties when I try to get data from virtual serial ports to my backend in the project . It's easy Part 1 . Installation: Download the tty0tty package from one of these sources: http://sourceforge.net/projects/tty0tty/files/ clone the repo  https://github.com/freemed/tty0tty git clone https://github.com/freemed/tty0tty Extract it tar xf tty0tty-1.2.tgz Build the kernel module from the provided source cd tty0tty-1.2/module make Copy the new kernel module into the kernel modules directory sudo cp tty0tty.ko /lib/modules/$(uname -r)/kernel/drivers/misc/ Load the module sudo depmod sudo modprobe tty0tty You should see new serial ports in /dev/ ( ls /dev/tnt* ) Give appropriate permissions to the new serial ports sudo chmod 666 /dev/tnt* You can now access the serial ports as  /dev/tnt0  (1,2,3,4 etc) Note that the consecutive ports are interconnected. For example, /dev/tnt0 and /

With this series now we are moving some another path of Embedded Systems. So what you can think of deep learning, machine learning, and artificial intelligence. I'm sure you have followed some courses, books, articles regarding this subject. Me too followed these courses to learn this subject. We have followed a lot of mathematics modules and stuff with this subject. So, I would like to share my experience of applying deep learning frameworks to our daily embedded systems applications. That's why I started this tutorial series. Hardware? I thought about running a neural network to detect plant behavior using raspberry pi once :-).I tried it with my raspberry pi and totally lagged. Raspberry PI has an ARM processor consist of few cores optimized for sequential serial processing. This will not enough for real-time processing. A CPU consists of a few cores optimized for sequential serial processing - See more at: http://www.nvidia.com/object/what-is-gpu-computin