Improving Smart Home Safety with Face Recognition using Machine Learning (ML)
Subuhi Kashif Ansari, Thippaluru Umamaheswari, Chamandeep Kaur, R. Sabin Begum, Dr Shaik Rehana Banu, Afsana Anjum · 2023
Programmers can improve prediction in their apps before all the essential foundational work has been done thanks to the branch of artificial intelligence known as machine learning (ML). The outside doors of a building require extra care because they are frequently used as the first point of access. These entries are now a target for the quickest and most effective security measures, or those that are simple and sufficient to give property owners peace of mind. Technology, particularly in the area of communication, has also made these entrances a focus for these measures. Household door-locking systems that employ face recognition technology have also been created and put into use; these systems are both user-friendly and efficient in recognising people based on their distinctive physical characteristics. Facial recognition is one of the most often used computer vision algorithms since it is easy to use and gets accurate results when identifying faces. Does your recommendation engine update its recommendations as soon as new products are released, or does it take some time? To be more precise, how do recommendations alter as users spend more time on the platform? If you want to understand the capabilities of each recommendation system, it’s critical to become familiar with the various types that are now accessible.