Abstract
The proposed development intends to establish an autonomous bank locker using industry-standard innovative locker technologies to deliver more flexible and reasonably priced semi-autonomous bank security mechanisms with minimal human intervention. In this design, there are two layers of locker security. The system proposed in this effort is a better security system regarding the number of security tiers. Its primary base is facial recognition. The first level is implemented by asking the user to input a passkey. A matrix keypad and Python programming are both employed. The user is then authorized to continue to the subsequent stage if a match is confirmed to exist. The second level was implemented using Python programming, OpenCV software, and face detection and identification techniques. To make Windows compatible with third-party apps Putty and Xming, the Raspberry Pi was linked to the laptop using IEEE 802.3 Ethernet and X11 forwarding on the UBUNTU operating system. IEEE 802.11 USB Wi-Fi was used to connect devices to the Wi-Fi network. The HAAR OpenCV standard has been used for face detection because of its better Face Acceptance and Rejection Ratio. The EIGENFACES OpenCV standard is employed for face recognition due to its efficacy, robustness, and simplicity.
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