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Electricity plays a pivotal role in today's world; life without electricity can never be imagined. We know most of energy is generated using non-renewable resources and the more we use them, the earlier they get depleted. So everyone should take responsibility to save the energy as much as possible. Many of us forget to switch off the electrical appliances while going out due to negligence usually. In educational institutes, most of the time students forget to switch off the lights and fans while leaving the classroom, which increases the wastage of electric energy as well as electricity bill. In this paper we present an idea to give power supply to classroom based on number of students present in the class using raspberry pi and face detection algorithm. It will turn off the lights and fans when the classroom is empty, which helps to reduce the wastage of electricity.

While hassle on video traffic over cell phone networks have been unpleasant the wireless link capability cannot keep up with the traffic exact. The space between the traffic demand and the link capability, all along with time-varying link position, results in reduced service excellence of video streaming over cell phone like as lengthy buffering time and blinking disturbance Leveraging the cloud compute technology, we suggest a new video streaming structure of mobile, AMES-Cloud dubbed, which has couple of parts: AMoV (adaptive mobile video streaming) and ESoV (efficient social video sharing). ESoV and AMoV create a private mediator to give video streaming services capably for every mobile client. For a particular client, AMoV lets her secret agent/mediator adaptively alter her/his streaming pour with a scalable video coding procedure depended on the response of link superiority. As well, efficient social video sharing observes the social network acquaintances among mobile clients and their personal mediators try to share video pleased in advance. We realize the AMES-Cloud framework prototype to reveal its presentation. It is shown that the confidential agents in the clouds can efficiently provide the adaptive streaming, and based on the social network learning achieve video sharing.