Abstract- Efficient utilization of energy has become increasingly essential in recent years because of environmental issues such as climate change and global warming. Environmental problems are very important issues and these problems are largely caused by the excessive use of energy Thus our aim is to develop such a system which not only reduces unwanted wastage of energy but is also user friendly and hassle free.
INSPIRATION:The per capita average annual domestic electricity consumption in India in 2009 was 96 kWh in rural areas and 288 kWh in urban areas for those with access to electricity, in contrast to the worldwide per capita annual average of 2600 kWh and 6200 kWh in the European Union. India’s total domestic, agricultural and industrial per capita energy consumption estimate vary depending on the source. Two sources place it between 400 to 700 kWh in 2008’2009. As of January 2012, one report found the per capita total consumption in India to be 778 kWh.
frame separation,morphological filtering
Its primary function is to reduce the electricity consumption to a greater extension.by using background image comparison techniques and frame separation technique which detects the moving human body from the background image in video sequences, and target classification, the human body tracking and behavior understanding, By real time moving object detection we can capture real time images from our static camera and compare it with the already stored reference image if there is any humanly presence detected on the camera by background subtraction algorithm we can turn on any electrical appliance we desire and if there is no one in the room(no human) that is the real time image and reference images are same then electrical appliances are switched off hence saving a ton of energy.
The generalized block diagram is shown below The block diagram can be divided into two parts first one is Software block and second is Hardware block. Software consist of following blocks:-
Similarly Hardware block consists of following blocks:-
III.HARDWARE UNIT :
As soon as the image is corrected and processed, it is given to the Arm processor7. The programmable device will receive a user defined character and fan ,light or other devices in that particular area are switched on. If the user defined character is not received then fan light other appliances are switched off .Thus unwanted energy consumption can be reduced to a greater extent .The microcam sunrom we use is a highly integrated serial camera module which can be attached to any host system As that requires a video camera or a jpeg compressed still camera for embedded imaging applications.
HARDWARE UNIT BLOCK DIAGRAM
The pre-defined image is the reference image which is already stored , this image is compared to the continous real time image we capure through the camera by using the background subtraction algorithm we compare the refrence and real time image,the comparison is done in the arm 7 processor block it will evaluate the difference between both the images if the value is higher than agiven threshold it will detect the presence of the object and will give a appropriate command to the control unit wheter to turn on or off the electrical appliance if suppose the threshold is greater than 1 turn on if less then 1 turn off this depends on the presence of human entity in the room covered by the camera hence ensuring energy saving when the person exits the room.If the real time and reference images are the same then no action is taken.
IV.SOFTWARE UNIT :
Actually input video taken from Real time camera is also possible and we can also apply pre defined video (matlab support only .avi format video) In this project we need to convert input video to frame’s by using matlab. Combination of frame’s is called as video.Each and every video have no of frames, by using that value we can take the no of frame’s. After converting video to frames first frame (image) is called background image, and other then first image are current image and these images are not similar at the time of moving object detection video. And also these current images are similar at the time of non moving object detection.Background image comparison means we just subtract the current image and background image, and the current image is updated in each and every time, background image is constant. by using these technique we can easily find the moving object.For ex background image pixel ‘ current image pixel If the output is 0 means no moving object detected. If the output is 1 means moving object detected. Pre-processing & Shape analysis these are included in control action block By using this technique we can identify the shape of the moving object ( if there is any variation in background image and current image ). otherwise no moving object is detected if there is no variation in background image and current image.
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