  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 data sets. 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.
