Smart Security System Using Face Recognition on Raspberry Pi Privacy and Security are two of the most important universal rights. To ensure security in our daily life through technology, a lot of research is going on. Among them facial recognition is a popular and wellestablished technology. In this technology, faces are detected and identified out of images and with the help of Internet of Things (IoT), it becomes even more useful and precise. Using face recognition and IoT, we aim to create a smart door, which secures the gateway on the basis of who we are. In our proof of the concept of such a smart security system, we have used ViolaJones method to detect faces and Eigenfaces method to recognize people. A Raspberry Pi has been used as the microprocessor for ensuring lowcost and small size of the system. The door will open automatically for the known person upon receiving command from the processor. On the other hand, photo of the unknown will be uploaded to a webserver while an email is sent to the owner of the place containing a link to the image. From the website of the system, the owner can then allowblock entry and also trigger an alarm from anywhere in the world.

Identity Verification through Face Recognition Implemented on Raspberry Pi Framework The influence of identity verification in mobile application have attracted significant attention and growth to mobile technology development. So far, there are various methods involving identity verification in mobile application development, yet, it was still considered challenging and have been a primary study due to its limitation to memory allocation and the computing power.xc2xa0xc2xa0Subsequently, to address these issues there are different algorithms that were designed for identity verification to adopt the mobile environment and to resolve the arising challenges.xc2xa0In this paper, we proposed a novel,xc2xa0xc2xa0costeffective and energyefficient framework by introducing a mobilebased identity verification on offlinemode using the Raspberry Pi framework. A Raspberry Pi device is wirelessly connected to mobile phone to process the face detection and face verification.xc2xa0xc2xa0The proposed method is implemented on the latest version of Raspberry Pi 3 model B version run in Python 3.7 where the datasets and training sets images were experimented and tested using LBP algorithms for face detection and face verification. With the experimental test result using the confusion matrix in a multiclass classification,xc2xa0xc2xa0the proposed method showed a results of 87.5% accuracy score,xc2xa0xc2xa088% in terms of precision,xc2xa0xc2xa088% recall score and 86% F1 score.xc2xa0xc2xa0In addition, the experimental test were done using 3000 images in a controlledunconstrained environment, were 20% or 600 of the images were used as data sets. During the offline mode testing, the face detection and verification has resulted to an average timing of 4.98 seconds. Thus, it concludes the feasibility to implement face verification system in the Philippine government services such as the voting system, road checkpoint, driverxe2x80x99s ID verification to name a few.xc2xa0          Keywords: Raspberry Pi, Local Binary Pattern (LBP), Face Detection, Face Verification, Mobile Application, Identity Verification