Figure 1 illustrates the components and interconnections of the Smart Door Lock System, showcasing sensors, actuators, control units, and power sources. The Light Dependent Resistor (LDR) sensor detects light signals emitted by a user’s smartphone flashlight. These signals are then processed by the ESP32 microcontroller, which analyzes their patterns for authentication. Once verified, the microcontroller instructs the actuators to unlock the door. The actuators translate these electrical signals into mechanical actions, allowing the lock to function. Power sources supply electricity to all components, ensuring continuous operation. By utilizing VLC and synchronizing these elements, the system effectively prevents unauthorized access, enhancing security for smart homes and facilities.

Figure 2 illustrates how the Light Fidelity (Li-Fi) smart door lock system operates. The system assumes that the user has a smartphone, which turns on its torch when it is turned on. The door lock mechanism receives light from the torch in specific patterns. The LDR in the lock detects these modulated light signals from the smartphone and sends them to the ESP32 microprocessor for processing. By studying the timing and pattern of the light, the microcontroller determines whether the input is acceptable. By delivering an unlock order to the door upon authentication, it guarantees that only approved persons are able to enter. The system employs VLC as an additional security feature to reduce the likelihood of unauthorised access because light cannot flow past barriers. This approach is ideal for safe facilities and smart homes because it is also simple to implement, affordable, and environmentally friendly.

The system hardware is implemented using components as shown in the included schematics (Figure 3). The schematics comprehensively detail all components, connections, and pin assignments. Key parts include:

The schematics illustrate the wiring between the ESP32’s ADC input and the LDR voltage divider, relay coil control pins, and solenoid connections including protective diodes. All component pin numbers and net labels are clearly marked for reproducibility.

The circuit diagrams and flowcharts are integral parts of this manuscript (see Figures 1, 3, and 4), providing full insight into the hardware architecture. This direct inclusion ensures transparency and allows readers to replicate the setup without the need for supplementary files.

The parts of the smart door lock system and their connections are depicted in Figure 3.

The following are the main parts of the system:

Here is the breakdown of voltage and current used by all components (Table 1).

Although certain smart door locks, especially those used in commercial or high-power applications, are connected to the home’s electrical infrastructure, most are battery-operated for convenience in residential settings.

The mobile application was developed using Kodular, a user-friendly, block-based platform designed for users with minimal programming experience. Kodular speeds up prototyping and the launch of working mobile apps by streamlining the development process. Additionally, it provides a variety of extensions that let users increase its functionality. Anyone can create apps more easily with Kodular’s intuitive environment, which fosters creativity and innovation. Complex application development is also made easier by pre-made components and templates, and valuable insights are provided by a vibrant community and abundant resources. Kodular democratises app development by empowering more people to realise their ideas by offering robust yet user-friendly tools.

At first, the smartphone app takes the user’s fingerprint. The flashlight flashes to indicate that the fingerprint is correct and the door unlocks if it matches the user’s fingerprint that is saved on the smartphone. Currently, the data encoding scheme being used is On-Off Keying (OOK) which turns the flashlight ON and OFF in precise time intervals.

If there are multiple failures in authentication, the system has a cooldown of 1 minutes before the next attempt. The maximum number of attempts until a lockout is 4.

The system implements a two-phase enrollment and authentication process:

Users must configure settings and register their fingerprints for authentication reasons during the mobile app’s initial setup procedure, as shown in Figure 5. The setup screen prepares the system for upcoming interactions by guiding users through each step to guarantee secure access. Only authorised users are able to complete the setup thanks to fingerprint authentication. Once the procedure is over, the system is completely operational, enhancing the smart door lock’s convenience and security.

Figure 6 shows the instant after a successful fingerprint verification. After the system verifies the user’s fingerprint, the flashlight of the mobile phone sends out a specific light pattern that serves as a signal for verification. Such a visual sign informs the user that their fingerprint has been verified, indicating that it is okay to proceed. The specific light pattern is an intuitive feedback mechanism providing assurance of a successful verification. Moreover, this visual cue boosts security since the user will be in the know regarding the outcome of authentication, which decreases the threat of illegal entry.

Figure 7 illustrates a situation where fingerprint verification is unsuccessful. Here, the flashlight on the mobile phone does not flash the anticipated pattern of light, indicating a failed verification process. Consequently, the system inhibits further advancement in the unlocking procedure, essentially thwarting unauthorized entry. The lack of the light signal unambiguously notifies the user that there was not successful authentication, suggesting they try again or get help if the matter recurs. Moreover, the failed process is registered for future examination, helping to ensure an ongoing improvement in security procedures. For better accessibility, users can also be provided with alternative ways of authentication, i.e., typing in a password or PIN. In the end, this authentication failure illustrates the robust security provision of the system aimed at dissuading unlawful access.

The ESP32 maintains a local authentication database in 4 KB flash memory containing user pattern hashes, each associated with unique 16-bit User IDs and access privileges (admin/user/guest). Users enter enrollment mode through a 5-second button sequence or administrative mobile app interface. During enrollment, the ESP32 captures and stores the cryptographic signature of transmitted patterns rather than raw patterns themselves, ensuring security even if device memory is compromised. Pattern verification involves real-time SHA-256 hashing and comparison against stored signatures with additional timestamp validation.

The Li-Fi smart door lock system prioritizes user safety through comprehensive compliance with international optical safety standards and emerging Li-Fi communication protocols.

The system was tested indoors with a smartphone flashlight as the transmitter and the LDR sensor connected to the ESP32 microcontroller as the receiver. Ambient light conditions varied between 100 lux (dim room) and 500 lux (typical fluorescent lighting). Trials included different distances between the smartphone and the LDR receiver ranging from 0.2 to 1.5 m.

Spoofing attempts involved using unauthorized smartphones to mimic the authorized light pattern. Twenty spoofing trials were performed by replicating the OOK modulation timing of the legitimate pattern. One hundred spoofing trials were performed using programmable LED drivers to precisely replicate authorized OOK patterns. The system successfully detected and rejected 99% of unauthorized transmissions through cryptographic validation and timestamp verification.

Replay attacks tested whether the system could be deceived by retransmitting previously recorded valid light patterns. One hundred replay attack trials were conducted using captured authentication sequences retransmitted within various time windows (1 second to 24 hours delays). The system rejected 100% of replay attempts through rolling-code authentication with 60-second token validity and cryptographic nonce verification, preventing any successful unauthorized access through signal recording and retransmission.

Reflection attack trials involved transmitting valid light patterns indirectly by reflecting the smartphone’s flashlight off mirrors or other reflective surfaces towards the receiver. Fifteen reflection attempts were performed at varying distances and angles. Two successful unauthorized unlocks were observed when reflections occurred within 20 cm of the sensor, resulting in a 13% attack success rate limited to close proximity scenarios.

This ethical framework ensures responsible development and deployment of the Li-Fi smart door lock technology while protecting user privacy and maintaining research integrity.

The lock state is demonstrated in Figure 8 following a failed authentication or no attempt at authentication. The lock remains locked in this state and does not allow illegal access. To serve as a visual signal, a specific LED pattern or colour indicates to the user that the lock is secure. In addition to this, the user may select another form of verification or attempt again because the system remains ready for a new authentication attempt. A warning tone or beep, as an auditory alert, could be triggered to notify other people of the failed attempt in order to enhance security further. Ultimately, having the lock in a safe state protects against any possible security threats and ensures the safety of the building and its occupants.

The door unlock is shown in Figure 9 after biometric fingerprint recognition is successful. After the system authenticates the user’s fingerprint, the door lock opens to permit authorised access. The image serves as visual evidence that the user has been given entry and demonstrates the dependability and effectiveness of the smart door lock system. The door opening signals the completion of a secure verification process and validates the improved security features built into the Li-Fi technology. The system is the greatest choice for homes, workplaces, and other applications since its smooth lock mechanism also improves its access control capabilities.

Figure 10 illustrates a detailed quantitative comparison of security and operational parameters across access control technologies, consolidating data from experimental measurements and literature benchmarks. The comparative analysis replaces subjective ratings with empirical data derived from controlled laboratory testing as described in Section “Experimental Validation.” Each parameter represents measurable performance characteristics. The following metrics were evaluated:

Table 2 contains the values:

Figure 11 demonstrates the Proposed Design’s competitive temporal performance and reliability characteristics compared to benchmark technologies. The analysis focuses on user experience factors and system responsiveness under controlled laboratory conditions. The following performance metrics were measured:

Figure 12 reveals the Proposed Design’s substantial economic advantages and scalability characteristics within the access control technology landscape. The analysis encompasses total cost of ownership and deployment capacity considerations. The following factors were evaluated:

Figure 12 employs dual y-axes with independent scales to accommodate the disparate value ranges between implementation cost (left axis: INR) and scalability (right axis: maximum users), ensuring optimal visualization clarity for both metrics (Table 4).