Due to the speedy expansion in human community the energy consumption in the whole world has sharply raised. Prediction of energy consumption is very important because the produced energy from the electricity plants is consumed at a simultaneous rate. Below is a neural network model that employs the CNNLSTM network to forecast a power grid's power usage. The suggested neural network model can read aggregated and difficult to read variables linked to energy usage, according to research and testing. The LSTM (Long Term Short Memory) layer is good for modelling information in time series configuration while the CNN (Convolutional Neural Network) layer is good for reading features between different variables related to energy consumption. This combination has pulled off fantastic results than the subsisting methodologies. Furthermore, it stores the lowest number for RMSE for separatehouse energy consumption.

When it comes to social problems womenharassment and crimes against women are the biggest problem amongst all. Despite, strict laws and punishments such incidents happen every now and then, that’s because there is a drawback in the surveillance system used by the law enforcement officers for the sake of curtailing women safety and crimes. According to the report of National Crime Records Bureau (NCRB), 4, 05,861 lakhs transgression cases were reported against women in India in the year 2019. The further proposed work will help in lessening down the crime rates by ameliorating the surveillance system with the implementation of the Convolution Neural Networks (CNN).