🤖
Artificial Intelligence
EfficientNet B2 & Vision Transformer models for species classification
EfficientNet B2 & Vision Transformer models for species classification
React Native, Node.js, Tailwind CSS, PhpMyAdmin
Cross-platform React Native with TypeScript
Arduino UNO, ESP32, Environmental Sensors
SQL injection prevention, XSS protection
Real-time visualization and species analysis
A comprehensive technology solution addressing wildlife conservation challenges through innovative IoT monitoring, AI-powered detection, and digital engagement platforms.
Protecting diverse wildlife species at Semenggoh Wildlife Centre through advanced monitoring and threat detection systems, addressing the critical need for real-time conservation management.
Real-time poaching detection using IoT sensors with GPS precision, enabling rapid response to protect vulnerable wildlife populations from illegal activities.
Interactive digital platforms educating visitors about wildlife conservation while providing real-time species sightings and supporting donation-driven conservation efforts.
Comprehensive suite of tools for wildlife conservation and visitor engagement
AI-powered camera traps with motion sensors capturing and analyzing wildlife footage for instant species identification and behavioral analysis.
IoT sensors detecting unauthorized activity with GPS coordinates, sending instant Telegram alerts to rangers for rapid response.
Real-time map visualization showing wildlife sightings with educational content and conservation status for enhanced visitor engagement.
Streamlined donation process with automated certificate generation and transparent fund tracking for conservation initiatives.
Comprehensive data visualization for administrators showing species trends, site activity, and habitat analysis for informed decision-making.
Platform for publishing conservation events, tracking engagement metrics, and promoting community participation in wildlife protection.
Intelligent virtual assistant with Natural Language Processing, context-aware conversations, and 24/7 automated support for booking guidance and system help.
Live equipment status updates with conflict detection, instant availability notifications, and calendar integration for visual scheduling.
Automated email and in-app notifications for booking confirmations, reminders, overdue equipment alerts, and maintenance scheduling.
Comprehensive reporting with visual charts, usage analytics, booking trends, and exportable PDF reports for data-driven decisions.
Role-based permissions with encrypted data storage, secure authentication protocols, and comprehensive audit trails.
Mobile-first design ensuring seamless experience across desktop, tablet, and mobile devices with consistent functionality.
Verification of core system features and user workflows
System performance under various load conditions
Comprehensive security vulnerability assessment
User experience validation with real stakeholders
Multiple users accessing the same equipment simultaneously created conflicts and inconsistent data states across different user interfaces.
Implemented real-time conflict detection with immediate booking validation, live status updates using database triggers, and optimistic locking mechanisms to prevent double bookings while maintaining data consistency across all interfaces.
Different permission levels required for students, lecturers, IT admins, and super administrators with varying access to system functionalities.
Developed comprehensive role-based access control (RBAC) with granular permissions, middleware authentication, and dynamic UI rendering based on user roles.
Mid-development requirement to migrate from initial PHP/HTML setup to React.js frontend with Laravel backend for better maintainability.
Successfully migrated the entire system architecture while maintaining all functionality, implementing component-based React structure and RESTful API design patterns.