Laboratory of electronic media

Indeed, one of the distant goals of media lab at Massachusetts Institute of technology which was founded by Nicholas Negroponte is designing machines that can distinguish peoples' methods of communication and imitate them. People do not use the language only but they also use a rich and complicated body language that is composed of a wide scope of signals to communicate with one another including eye contact, facial expressions, gestures, arm movements, tone of voice, and body postures.

The design of the smart room represents an important step in this direction where the room is unable to recognize people only, but it can also recognize their signals and emotions as well.

The example of media lab using smart rooms in the future in the words of Micheokako in his book "future visions" is a place equipped with small cameras placed in the ceiling and with a huge screen on the ground.

Alex Pentland wrote about media lab in Massachusetts Institute of technology saying: Imagine a house that continuously knows where your children are and always tell you if they are facing any problem. Imagine a desk tells you about important appointments and protect you from delaying. Imagine a car that feels if you are tired or not and warn you when to stop.

However, there is a very important fact in this regard which is: Computers today cannot recognize reliably the face of a specific person from different angels.

Faces are the most difficult things for computers to recognize. However, the computer of media lab cuts the way by storing the faces and when a new person comes, it registers him in memory and later on it can recognize him easily. The recognition percent can reach about 99% in a group of hundreds of people.

Scientists have found out that it is easily to recognize emotions by computers as a result of the face expressions. A smile can lead to the spread of muscles and causes eyebrows to go up, anger can cause the eyebrows to narrow, and disgusting can affect the expression of the entire face.

Therefore, when the computer focused on the face parts, it could recognize in tests the expressions of the face easily and could define the emotional status of a person in about 98%.