While a lot of efforts have been on outdoor intelligent systems, internal living environment system that suits the occupancy’s behaviour has not received much attention. The intelligent living environment designed in this study has three components; the physical world (environment), the database and the decision maker. The study sought to design a model that senses ever changing home conditions such as lights, doors and windows. Other variables that were looked at include, but not limited to the number of people in the room and inside thermodynamics and human activity. Global information such as temperature, gas or electricity usage and time of the day will also be received by the system through various sensing facilities. The information will be sent to a rules engine for a decision on an appropriate action to be taken. The action may include just turning off the lights, in the case of a mild abnormality or a high alert to an emergency response unit in a most severe case. The study proposes a context aware and proactive neural networks control system to control a living environment with a main focus on the aged citizens living alone. The proposed living environment was not developed to an actual or “mock” building containing a representation of subset of sensors, actuators and controllers as used in the actual systems due to lack of funding. However, the study will report on the modelling and simulation of the home system variables based on the chosen Artificial Intelligent technique using MATLAB/SIMULINK. These results indicate a possibility of implementing the designed living environment to increase the resident’s security. / Electrical and Mining Engineering / M. Tech. (Engineering: Electrical)