With the ever-increasing number of diagnosed cases of Parkinson's Disease in the Philippines, there is a need for Ambient Assisted Living systems that will help improve the quality of life and independent living of patients with Parkinson's Disease. Currently, there are a lot of existing Ambient Assisted Living systems, such as the RAReFall Detection system, which incorporates various sensors, such as wearables, external sensors, and smartphone sensors to detect and recognize human activities. However, these existing systems are not easily accessible due to the costly and complex nature of the equipment being used. To address this problem, this project aims to create a cost-efficient, state of the art, accessible and user-friendly smartphone based Ambient Assisted Living system which incorporates the use of embedded smartphone accelerometer and gyroscope sensors in order to detect and categorize the daily activities and falls of patients with Parkinson's Disease, and at the same time employing new techniques to be able to provide a means for immediate response and to give appropriate advice in order to prolong the independent and active participation of patients in their communities.