The problem Facial-Identity-Verification-on-Blockchain-with-Ml solves

1. Addressing Ambiguity and Counterfeit Entries: The solution tackles the critical issue of ambiguity and counterfeit entries in facial recognition technology.

2. Recording Unlock Events on Blockchain: Each unlock event is recorded as a state in the blockchain, empowering users to distinguish between authentic and fraudulent accesses.

3. Ensuring Integrity of Facial Recognition Data: By providing a transparent and immutable record of each interaction, the approach guarantees the integrity of facial recognition data.

4. Enhanced Security and Trust: Administrators can easily monitor and verify the legitimacy of access attempts, thereby enhancing security and trust in facial recognition systems.

5. Propagation of State with Each Unlock: Every new unlock propagates the state, and this transaction is recorded on the blockchain, ensuring transparency and verifiability of any system changes.

6. Bolstering Security and Trustworthiness: This mechanism further bolsters the security and trustworthiness of the facial recognition system by ensuring transparent and verifiable transactions.

7. Administrator Access to Log and Previous States: Administrators have the capability to access the log and review all previous states whenever a person unlocks the facial recognition tool.

8. Comprehensive Monitoring: This comprehensive access enables administrators to track the complete history of interactions, ensuring transparency and facilitating the detection of any unauthorized access attempts or suspicious activities.

9. Insight into State Changes: By having insight into every state change, administrators can effectively monitor the system's integrity and promptly address any security concerns that may arise.

Challenges I ran into

1.Developing statefull 1satordinal contract with custom transaction builder
2.Understanding concept of machinelearning and models to use for this project.