Case Study: Web-Based Face Recognition Software Solution by Next Olive Technologies

Objective Next Olive Technologies developed a cutting-edge Face Recognition platform designed to identify and remove intimate pictures of users that have been illegally published online without consent. The platform aims to protect user privacy and ensure security.

Unique Selling Points/Features

• MVP launched at Disrupt TechCrunch 2017 within just 6 weeks.

• Platform available in the US and Romania.

• Integrated Face Recognition with Two-Factor Authentication.

• Advanced face detection and recognition models using deep learning.

• Face detection implemented via Python API.

• Mobile ID verification leveraging computer vision and image processing.

• Two-way video verification using Twilio.

• Comprehensive Admin & Controller interface.

• Dashboard management including coupons, feedback, invoices, and tickets.

Technology Stack

• Frameworks & Languages: ASP.NET MVC, Entity Framework, WEB API with token-based authentication, C#, Angular, HTML, CSS, JavaScript, jQuery, Bootstrap.

• Database: PostgreSQL.

• Architecture: n-tier Architecture, MVC Repository Pattern.

Technical Implementations

• Implemented WebAPI-based n-tier Architecture.

• Utilized Ninject for dependency injection.

• Developed a Single Page Application (SPA) using Angular, Bootstrap, and jQuery.

• Applied OOP principles for code redundancy elimination and reusability.

• Created User Controls and Custom Controls for consistent application-wide use.

• Parsed database-stored templates for dynamic substitution.

• Integrated recurring and one-time payment methods.

• Enabled two-factor mobile authentication.

• Facilitated verification through video calls.

• Managed timezone settings for global use.

• Conducted unit testing and documented the User Manual.

Development Approach

• Followed the Software Development Life Cycle (SDLC) for design, development, and testing.

• Adopted Agile Project Methodology for flexible and iterative development.

• Employed third-party controls to enhance functionality.

• Supported Amazon Pay and PayPal for secure payments.

• Used Trello for project management and task tracking.

Achievements Next Olive Technologies successfully delivered a robust, secure, and user-friendly Face Recognition platform. The project not only met stringent timelines but also set a benchmark in the realm of digital privacy protection through innovative AI and machine learning applications.

This project highlights Next Olive Technologies' expertise in developing sophisticated web-based solutions using high-demand technologies and methodologies, ensuring top-notch security and user satisfaction.