Raspberry Pi + surveillance camera

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Raspberry Pi – Surveillance WebCam in the Cloud

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Using the Raspberry Pi for camera surveillance using Motion and cloud storage

If you are looking for a cheap camera surveillance setup, the Raspberry Pi is a great solution.
It is small, easy to install and, most important, has low energy usage.
I own Model B (see the Raspberry Pi Wikipedia page for detail about the models) which uses 3.5 Watts.

There are several open source motion detection applications for Linux such as ZoneMinderand Motion.
Both programs are available through the Rasbian repository.
ZoneMinder looks like a real security control center with all those nice cam screens, but it’s too bloated and too CPU heavy for the Raspberry Pi.
Motion is more lightweight and doesn’t stress the CPU too much when processing 320×200 camera data.
With 2 IP camera’s my average load is less than 0.50 on my RasPi, which also serves as an caching DNS server.

For storage of the AVI video files which contain the captured motion frames, I use a free Box.com account.
Box.com provides the same service as the popular Dropbox.
The reason for choosing Box.com is because Dropbox has no open source client. The Dropbox Linux client is closed source and has, at the moment, no support for ARM devices like the Raspberry Pi.
Furthermore the free Box.com account gives you 5 GB of storage. Way enough to store home camera data for a couple of months.

BoxFS is the weapon of choice to mount your Box.com account as a drive partition on your Raspberry Pi.
Some basic Linux knowledge is preferred.

Setting up BoxFS

Read the Compiling page on the BoxFS site carefully 
From release 63 of BoxFS libapp is used for parsing config files. Be sure to compile and install this first.

When libapp is compiled and installed properly, install the rest of the BoxFS prerequisites:

sudo apt-get install subversion libxml2-dev libfuse-dev libcurl4-gnutls-dev libzip-dev

I recommend using the latest commit of BoxFS in the repository.
The latest release, version 0.7, does not support user/group id’s and file/directory permissions. The latest commit (>=release 63) does.

svn checkout http://boxfs.googlecode.com/svn/trunk/ boxfs-read-only

After checking out the BoxFS source code, go to the boxfs-read-only directory to compile and install BoxFS:

sudo make install

The BoxFS binary will be installed in /usr/local/bin.

Mounting your Box.com account using BoxFS

I found out that running BoxFS as root gives the best results. I tried running BoxFS as a non-root user and it gave me some curious and unpredictable results.

Create a configuration file (for example boxfs.cfg) first.
A valid configuration file looks like this:

#This is a comment line
username   = me@domain.com
password   = mystrongpass
mountpoint = /path/to/folder
# from version 0.6:
verbose    = yes
secure     = no
# from version 0.7:
largefiles = yes
# from commit r86
uid        = 1000
gid        = 1000
fperm      = 644
dperm      = 755

The mount point must be provided in either way.  This can be an empty directory called /motion for example.

To start the BoxFS client, simply run this command as root:

boxfs -f boxfs.cfg

To check if everything is doing what it should be doing, go to your BoxFS mount point and try to create or copy some files.
For debugging I recommend to be logged in to your Box.com account with your browser to see if things are actually written in to the cloud storage.

I noticed that the BoxFS partition doesn’t appear when you run the df command as a non-root user. When you run the df command as root (or something like sudo df), the BoxFS partition is shown.
Just keep that in mind.

Installing and configuring Motion

To install Motion just run this command:

sudo apt-get install motion

Be sure that your camera’s and/or webcams output a 320×200 (or 240) image and Motion is configured with the same resolution.
I’ve tried a resolution like 640×400 pixels, but the CPU load went sky high on the RasPi, so I’ve settled for a lower resolution.
The images generated by my camera’s are quite clear and useful, so I’m happy.
I have no experience over clocking the Pi in combination with Motion, but if you do, please share your findings in the comments.
Same goes for solving the above resolution problem 

Further configuring Motion is something you have to do on your own.
The on line manual is quite clear about the numerous settings which can be done.
Mailing an image snapshot or a simple message when motion is detected is just one of the many possibilities.
Oh, and don’t forget to set the path to your BoxFS mount point to store your videos 

When you’ve got an mobile device, you can use the Box.com app to download an AVI file and watch it using a movie player which supports the file format.
Great when you’re on holiday for example, and want to know what’s going on at home.
And all of this without tampering  your firewall, keeping your home network closed and secure.

I hope this post helps you to set up your own budget camera surveillance system.
For less than 180 euro (that’s 2 decent IP camera’s and a RasPi) you’re all set to go.

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基于树莓派实现的开门君

#yishanju 2013/02/27 18:07
#import web
import sesameurls = ("/","index",)
app =web.application(urls,globals())class index:def GET(self):sesame.k()return "Open sesame."if __name__ == '__main__':app.run()

#!/bin/env python
#coding=GB18030
#yishanju 2013/02/27import wiringpi
from time import sleeppin=6
t=1io=wiringpi.GPIO(wiringpi.GPIO.WPI_MODE_PINS)
io.pinMode(pin,io.OUTPUT)def Open ():io.digitalWrite(pin,io.HIGH)if io.digitalRead(pin):return 1def Close():io.digitalWrite(pin,io.LOW)return io.digitalRead(pin)def k():Open()sleep(t)Close()if __name__=='__main__':k()

2. 

The Dark Pi Rises

To use it, let's install some required programs:

There are several ways to stream the webcam output to the network, but I settled on GStreamer because 1) I couldn't get VLC to work, 2) ffserver, motion and mjpeg consumed more CPU when I tried them. The following command gives me 10fps at 320x240, at only 25-30% CPU usage:

UPDATE: The Raspberry Pi Foundation has updated the firmware to enable H.264 encode on the GPU - I'll be working on getting this working as this could enable phenomenal improvement in the webcam streaming while using *less* CPU!

To open the Raspberry Pi's stream on your desktop, just fire up VLC and click 'File->Open Network Stream' and type in 'tcp://192.168.1.135:5000' in the location bar (replace the IP address with your Raspberry Pi's IP address!).

Now you should have 'live' streaming from your Raspberry Pi!

3. 

Object Tracking on the Raspberry Pi with C++, OpenCV, and cvBlob

Frame-rates on the Intel processor-based Ubuntu laptops easily performed at or beyond the maximum 30 fps rate of the webcams, at 640 x 480 pixels. On a positive note, the Raspberry Pi was able to compile and execute the tests of OpenCV and cvBlob (see bug noted at end of article). Unfortunately, at least in my tests, the Raspberry Pi could not achieve more than 1.5 – 2 fps at most, even in the most basic tests, and at a reduced capture size of 320 x 240 pixels. This can be seen in the first and second screen-grabs of Test #1, above. Although, I’m sure there are ways to improve the code and optimize the image capture, the results were much to slow to provide accurate, real-time data to the robot’s targeting system.

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