Adaptive Intelligent Controller for Household Cooling Systems

This paper presents a household cooling system controller which is adaptive and intelligent in nature. It is able to control the speed of a household cooling fan or an air conditioner based on the real time data namely room temperature, humidity and time i.e. duration, which are collected from environment. To control the speed in an adaptive and intelligent manner an associative memory neural network has been used. This embedded system is able to learn from training set i.e. the user can teach the system about his/her feelings through training datasets. When the system starts up it allows the fan to run freely i.e. at full speed and after certain interval it takes the environmental parameters like room temperature, humidity and time i.e. duration, as an input and after that system takes the decision and controls the speed of the fan.