Smart Glasses (P-0009) (MFN 8644)

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dc.contributor.author Fahad Ali, 01-132152-007
dc.contributor.author Usama Ilyas, 01-132152-045
dc.contributor.author Muhammad Waqas, 01-132152-025
dc.date.accessioned 2020-08-06T11:26:23Z
dc.date.available 2020-08-06T11:26:23Z
dc.date.issued 2019
dc.identifier.uri http://hdl.handle.net/123456789/9820
dc.description Supervised by Mr.Waleed Manzoor en_US
dc.description.abstract Security is one of the major threats from a past few years. To protect the sensitive areas, the steps which has been taken in the pasture not effective, especially facial recognition by using CCTV Cameras. It is time to reconsider that what measures should be taken to make the security of sensitive areas more secure? One of the challenges for the facial recognition is that while running on CCTV cameras it struggles a lot due to blurriness of the picture and by the time target will be identified as, the suspect might already move on. What if we have Smart Glasses which are capable of detecting unauthorized entries in the sensitive area? The Smart glasses will be given to the security person so they have the ability to check anyone on the spot. With Machine Learning at the back end to identify the suspect, you will get accurate and instant feedback on the Android Application so that the security person can decide immediately what the next interaction is going to be. Smart Glasses will have the IP Camera attached at the front for capturing the live video stream. The live video stream will be further sent to the back end system. Facial Detection and Recognition algorithms is used to identify the unauthorized entries. The security person will get instant alerts on the Android Application including the suspect image. en_US
dc.language.iso en en_US
dc.publisher Computer Engineering, Bahria University Engineering School Islamabad en_US
dc.relation.ispartofseries BCE;P-0009
dc.subject Computer Engineering en_US
dc.title Smart Glasses (P-0009) (MFN 8644) en_US
dc.type Project Report en_US


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