By using Facial Recognition with the combination of Azure Cloud Services or Amazon Web Services etc, if a police officer is wearing a helmet with a webcam and scanning a crime scene, he can identify suspects who have a past criminal history. It would need immense computing power but that would compensate through the use of cloud servers and connectivity on the go wherever the officers are. The biggest advantage of this would be to identify any suspects based on past criminal activity and detain them for questioning. Another advantage of Facial Recognition would be to identify the suspect through police offer's inquiry. If the suspect is not carrying his ID and tells the police officer a fake name, the wearable headset or glasses worn by the police officer would inform him about the person's actual identity.

Major advancements are being made in the field of Facial Recognition but the technology is still in the early stages of development. Right now, it is possible to accurately identify persons from a series of images provided if we have a small database from which the algorithm has to search from but if the database goes extensive with images of many persons, the time for the person to be identified can exceed by a huge margin. And in practical scenarios, we need results in a matter of seconds or so. Therefore it is not convenient to deploy this tech right now but it still presents a promising future in the area of crime fighting and tracking of fugitives. By using Facial Recognition with the combination of Azure Cloud Services or Amazon Web Services etc, if a police officer is wearing a helmet with a webcam and scanning a crime scene, it is possible for him to identify suspects who have a past criminal history.