Face Recognition System Is Broadly Used For Human Identification Because Of Its Capacity To Measure The Facial Points And Recognize The Identity In An Unobtrusive Way. The Application Of Face Recognition Systems Can Be Applied To Surveillance At Home, Workplaces, And Campuses, Accordingly. The Problem With Existing Face Recognition Systems Is That They Either Rely On The Facial Key Points And Landmarks Or The Face Embeddings From FaceNet For The Recognition Process. In This Paper, We Propose A Hierarchical Network (HN) Framework Which Uses Pre-trained Architecture For Recognizing Faces Followed By The Validation From Face Embeddings Using FaceNet. We Also Designed A Real-time Face Recognition Security Door Lock System Connected With Raspberry Pi As An Implication Of The Proposed Method. The Evaluation Of The Proposed Work Has Been Conducted On The Dataset Collected From 12 Students From Faculty Of Engineering And Technology, University Of Sindh. The Experimental Results Show That The Proposed Method Achieves Better Results Over Existing Works. We Also Carried Out A Comparison On Random Faces Acquired From The Internet To Perform Face Recognition And Results Shows That The Proposed HN Framework Is Resilient To The Randomly Acquired Faces.
