Photoplethysmography (PPG) is a cheap, non-invasive and effective method to measure various biological parameters, including blood pressure, although not directly. It is possible to obtain the PPG signal from smartphones, making measurement of important vital signs more accessible than ever. However, measuring using smartphones is very noisy and contains less information by nature thus posing many challenges. This project is a continuation of a previous projects performed in SIPL for measuring blood pressure using smartphones. In this project report, we briefly review the theoretical background and rationale for using PPG signals, and describe in detail the filtering and preprocessing procedures performed on raw pairs of PPG and blood pressure signals. In addition, the report includes details on the deep learning stage for predicting blood pressure from PPG signals from the MIMIC dataset. It should be noted that this project report reviews research activity in progress and not a final algorithm for blood pressure estimation using a smartphone camera.