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Real-time Market Intelligence for Albion Online

Technologies: Flutter, Node.js (Express), Redis, SQLite, JWT, WebSockets, Google AdMob

Cross-platform Flutter application with Node.js backend, designed to deliver real-time market intelligence and trading optimization for Albion Online players across the Americas, Asia, and Europe.

Key Features: Real-time pricing and historical data visualization, Profit and crafting calculators with trade-route optimization, AI-powered insights via Gemini AI, User-to-user marketplace and messaging

Business Impact: Live production app serving active trading community with revenue generation through strategic ad placement and premium features.

Download for PC Download on Google Play

ILLBEON Economy App – Technical Architecture

System Overview

ILLBEON Economy is a three-tier architecture optimized for high-performance Albion Online market data processing and analysis.

Architecture Components

Flutter Mobile Application (Frontend)

Framework: Flutter 3.0+ (Dart SDK)
State Management: Provider pattern
HTTP Client: Custom ApiClient with authentication and retry logic
Local Storage: SharedPreferences (settings and cache)
Real-Time Communication: WebSockets
Charts: FL Chart for data visualization
Platforms: Android (primary), iOS supported

Node.js Backend (server.js)

Runtime: Node.js 14+ with Express.js
Authentication: JWT with bcrypt password hashing
Rate Limiting: Custom API protection
Compression: Gzip optimization
Validation: express-validator for sanitization
WebSocket Server: Real-time communication

Caching Infrastructure

Memory: NodeCache (15-min TTL)
Redis: Optional distributed cache for scalability
SQLite: Persistent local cache fallback
Strategy: Intelligent invalidation and refresh

Data Flow Architecture

Request flow: Client → Backend API → Cache Lookup → Albion Data Project API → Processed Response → Client

Endpoints: west.albion-online-data.com, east.albion-online-data.com, europe.albion-online-data.com

Request Pipeline

JWT validation
API rate limiting (≥2s between calls)
Cache lookup (Memory → Redis → SQLite → API)
Response normalization/optimization
Compressed JSON delivery

Core Services

Authentication Service: JWT management, secure storage, auto-refresh, persistent sessions
Server Service: Multi-region selection, URL routing, regional sync, change notifications
API Client: Auth integration, retry logic, request logging, timeouts, structured error handling

Performance Optimizations

Backend: Gzip compression, persistent HTTP connections, capped cache sizes (10k keys), graceful fallbacks
Frontend: Lazy loading, Provider-based persistence, asset/image caching, async background fetching

Security

Authentication: JWT, bcrypt, bearer token validation, auto-refresh
Data: Input validation, CORS restrictions, rate limiting, sanitized errors

Deployment

Backend: fetcher.illbeoneconomy.com, regional endpoints, dotenv env management, PM2 process control
Mobile: Google Play distribution, semantic versioning, release signing, bundled offline JSON assets

Monitoring & Analytics

Application: Google AdMob, custom analytics, error reporting, request/caching metrics
Operations: API stats, server health monitoring, query performance tracking

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Wildlife Collision Prevention with Real-Time Risk Analytics

Technologies: Flutter, Dart, Google Maps SDK, Google Assistant, RESTful API

Cross-platform mobile application that uses real-time analytics and machine learning to predict and prevent deer-vehicle collisions through GPS data, environmental factors, and crowd-sourced sightings.

Key Features: Dynamic risk scoring, Community sighting network, Voice integration with Google Assistant, Risk-aware route planning, Smart geofenced notifications

Business Impact: Shifts wildlife collision prevention from reactive to proactive, enabling data-driven safety decisions through adaptive machine learning.

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DeerHotSpot – Technical Architecture & Implementation

Platform Architecture

Mobile Application

Framework: Flutter (Dart)
Platforms: iOS and Android (shared codebase)
UI/UX: Material Design with custom dark theme
Build: Gradle (Android), Xcode (iOS)

Core Services

Location Services: Geolocator SDK, background tracking, reverse geocoding, fallback accuracy mechanisms
Mapping: Google Maps SDK, risk overlays, custom markers, polygons, route rendering, real-time map updates
Data Management: SharedPreferences for settings/cache, JSON serialization, StatefulWidget state handling, offline caching strategies

Backend Infrastructure

API: RESTful JSON over HTTPS, OAuth 2.0 with JWT tokens, modular endpoints (sightings, risk, user)
Security: Bearer tokens with automatic refresh
Processing Services: Risk calculation engine, anti-spam sighting validation, geofencing alerts, push notification delivery

Voice Integration & Accessibility

Google Assistant: Custom App Actions, deep linking, voice commands ("Get deer risk," "Report deer sighting"), contextual TTS responses
Accessibility: Screen reader support, audio feedback, high-contrast dark theme, scalable text

Real-Time Features

Background Processing: Continuous location monitoring, geofencing, push notifications, adaptive battery optimization
Live Data Sync: WebSocket or polling, conflict resolution, offline fallback, client/server validation

Security & Privacy

Location Privacy: Runtime permissions, minimal data retention, HTTPS transport, local risk calculations when possible
Anti-Abuse: Rate limiting, geospatial validation, duplicate filtering, confidence scoring for community reports

Development & Deployment

Workflow: Git version control, Android Studio/VS Code, widget/integration testing, hot reload debugging
Deployment: Automated APK/IPA builds, signed releases, dev/staging/prod configs, performance monitoring and crash reporting

Performance Optimization

Mobile: Efficient widget lifecycle management, intelligent polling, compressed/batched requests, async UI responsiveness
Scalability: Service-oriented modular design, multi-level caching (device, CDN, DB), load balancing, optimized database queries

Integration Capabilities

Third-Party: Weather APIs, traffic services, emergency reporting, navigation app export
Extensibility: Plugin-ready architecture, public API, webhook support, standardized data export formats

This architecture enables DeerHotSpot to deliver reliable, scalable, and secure wildlife collision prevention while ensuring performance and accessibility across platforms.

Download VST3

Professional Audio Plugin for Smooth Volume Automation

Technologies: C++, JUCE Framework, VST3 SDK

Advanced gain/volume automation plugin engineered to deliver artifact-free, continuous curves superior to industry-standard tools. Developed in collaboration with a professional mastering engineer for optimal DAW integration.

Key Features: Continuous volume automation, Zero stepping artifacts, Optimized for Ableton/FL Studio, Professional mastering-grade precision

Business Impact: Addresses critical gaps in commercial plugins, providing smoother automation than 90% of existing gain tools.

EdsVolumeZoom - Technical Overview

Background & Problem Statement

Most VST3-based volume processors and DAW-native faders implement automation as stepped values rather than smooth, continuous curves. This creates limitations for precision mixing and introduces audible artifacts during dynamic automation.

Technical Innovation

Our JUCE-based C++ VST3 plugin takes a fundamentally different approach: automation curves are handled as true continuous changes across the buffer rather than stepped increments.

Key Advantages

Smooth, natural curves without "zipper noise" or stepping typical in other plugins
Precise automation fidelity, particularly noticeable in long volume rides
No audible artifacts, even under demanding automation conditions
Superior performance compared to industry-standard tools including FL Studio's mixer faders, Kilohearts Gain, and Fabfilter Pro-Q

Current Implementation Status

The plugin successfully eliminates artifacts and produces continuous curves. Current optimization focuses on smoothing algorithm refinement to achieve analog-like curves regardless of buffer settings.

Performance Characteristics

Outperforms commercial products in A/B comparisons
Rivals StandardCLIP's output gain (2015) implementation
Optimized CPU usage with configurable buffer size handling

Installation Instructions

Download the VST3 file and place it in your VST3 directory:

Windows: C:\Program Files\Common Files\VST3\

Mac: /Library/Audio/Plug-Ins/VST3/

Industry Impact

By addressing overlooked quality issues in commercial plugins, EdsVolumeZoom demonstrates that high-quality, continuous automation is achievable without artifacts - setting a new benchmark for digital mixing and production fidelity.

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Kevin Shinkle

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