Brain-Computer Interface (BCI) is an approach for connecting human brain and a computer or any other type of electronic devices such as the robot and automated wheelchair, etc. The main purpose of BCI is not to trust only on peripheral nerves and muscles for communication because sometimes they are not in the condition to perform tasks or giving signals to devices, so that's why BCI is directly connected to the brain for activity recording. The BCI based system needs to record brain signals to perform operations, these signals can be recorded with Electroencephalogram (EEG) technology. EEG signals are recorded neural activity of the brain, which occurs when a user is performing some type of task like focusing on something or trying to give motor imagery signals to muscles. The purpose of this research is to enable the user to send motor imagery movements commands to the computer and make sure that the computer will perform these motor imagery movements correctly and consume less time for real-time processing. For ensuring all these things an algorithm (not only algorithm a way for BCI systems to record, filter and process signals smartly) is designed. In the proposed approach, major electrodes dealing with motor imagery movement are selected and others are eliminated, which make proposed system more effective light and fast after eliminating extra electrode signals are passed by the band-pass filter for eliminating contaminated signals. Results show that proposed system is increasing the accuracy of motor imagery movement detection. Eliminating the extra data efficiently, which is making the system more light and fast. By making the number of electrodes less proposed system is optimizing the signals which enabling real-time processing much better, fast and accurate. The main purpose of the proposed approach is to make BCI based motor imagery movement detection, better, fast, efficient and performing real-time operations. Proposed work has many avenues for the future.