Visual speech Recognition or Lip reading is used for teaching differently abled persons to communicate with others. It has been determining speech by looking at the movement of the lips. There are many practical difficulties in traditional lip-reading recognition systems like complicated image processing, difficult to teach classifiers and recognition processes will take a long time. In our paper, we proposed the use of convolutional neural networks- Hidden Markov model (CNN-HMM) in lip reading. Since CNN will assign importance to an input image, it is easier to see a difference among the images. HMM used to handle the dynamics of the image sequence. First we convert the incoming video into images and these images selected for further operation. HMM provides a highly reliable way of speech recognition.

The display hardware concentrates on planning low power control gadgets due to the utilization of versatile battery-powered gadgets. Ultra low energy process of memory clusters has ended up undying due to its uses in low voltage calculation and communications. Stable SRAM process is valuable for the success of low-power due to parameter variations in scale-down technologies. In expansion to control utilization, the SRAM’s get to time is another complex parameter due to the inevitable exchanging exercises utilized for distinctive squares, say SRAM cell, get to NMOS transistors, NMOS preload transistors, a yield sense enhancer and both decoders. It has been appeared that the tail transistor-based 6T SRAM cluster comes up short to realize solid standby control and less delay process. The proposed inactive arbitrary get to memory (SRAM) plan gives an approach towards diminishing the standby control scattering. The design uses a sleep transistor which helps in limiting the standby power by preventing the whole cell from working for unwanted operations. It is eligible for low power applications due to the supply voltage being 1.8V. The designed SRAM cell has single-ended write and reads operations, which can also reduce the total power dissipation and the tail transistor reduces the short circuit energy consumption. The design is verified with Cadence (45nm) and the power estimated as 4.6789pW, which is 78.2% of ordinary 6T SRAM block.

Rainwater is a free and renewable source used for domestic purposes but due to storage constraints, 36% of rain water is used in India even though heavy rainfall occurs during monsoon months. Nowadays the roads and their development in city environments are incalculable. The outstanding backlog is that most of the time, the drainage is filled by rain that falls on roads lead to less possibility of rain water usage. This work describes of saving rain water via external sensor -equipped pipes attached to the roadside. Whenever rain water fall on sensors it will be sensed, so that the pipes will open and rain water will fall through the fitted pipes and further it is transferred to storage tank with the aid of servo motors and DC motors. Through this prototype construction the rain water quantity of 55% is getting saved and also supports for ground water recharge