DaScient, LLC — DaScient Intelligence, Inc. | Version 2.2.0
ARES-E is a comprehensive, vendor-agnostic evaluation harness for benchmarking AI autonomous systems across the Critical Quad:
| Module | Domain | Focus |
|---|---|---|
| EWIS | Energy & Weather | Grid operations, PUE monitoring, AI workload efficiency |
| WOIK | Water Operations | Hydraulic systems, SCADA interoperability, water quality |
| PHIAK | Public Health | ED/ICU capacity, syndromic surveillance, privacy-first design |
| Data | Data Center Optimization | Capacity planning, PUE, assisted attribution, cooling optimization |
- LOE 1 — Autonomous Infrastructure Monitoring & Alerting
- LOE 2 — Human-Machine Teaming for Crisis Decision Support
The analytics dashboard provides a single-pane-of-glass operational view across all three modules with:
- Real-time streaming telemetry (synthetic data engine at 0.5 Hz)
- 18 configurable threshold alert rules with deduplication
- 8 interactive Chart.js visualizations (dual-axis, radar, area, bar)
- LOE composite benchmark scorecard
- 12-week score forecasting with 95% confidence intervals
- DDIL simulation results summary
- 100% client-side — zero backend, zero tracking, zero PII/PHI
ARES-E/
├── index.html # Dashboard entry point (GitHub Pages)
├── css/
│ └── dashboard.css # Design system — tokens, layout, components
├── js/
│ ├── synthetic-data.js # Synthetic telemetry generator (PRNG + signal composition)
│ ├── charts.js # Chart.js lifecycle manager (8 chart types)
│ ├── alerts.js # Rule-based alerting engine (18 threshold rules)
│ ├── forecasting.js # OLS regression, EMA, SMA, confidence intervals
│ └── dashboard.js # Main controller — orchestrates all modules
├── worker.js # Cloudflare Worker — interactive terminal interface
├── LICENSE # MIT License
└── README.md # You are here
┌──────────────────────────────────────────────────┐
│ ARES-E Evaluation Orchestrator │
│ (Dashboard Controller) │
├─────────────┬─────────────────┬──────────────────┤
│ EWIS │ WOIK │ PHIAK │
│ Energy │ Water │ Health │
├─────────────┴─────────────────┴──────────────────┤
│ Synthetic Data Engine (Mulberry32 PRNG) │
│ └─ Diurnal cycles + Gaussian noise + anomalies │
├──────────────────────────────────────────────────┤
│ Alert Engine (18 rules) + Forecast Engine │
├──────────────────────────────────────────────────┤
│ Chart.js Visualization Layer │
├──────────────────────────────────────────────────┤
│ GitHub Pages / Cloudflare Workers Runtime │
└──────────────────────────────────────────────────┘
Synthetic Telemetry → Normalization → Anomaly Injection
→ Alert Evaluation → Chart Rendering → KPI Updates
→ Forecast Projection → Operator Decision Support
| Technology | Purpose | Educational Value |
|---|---|---|
| Chart.js 4 | Canvas-based charting | Real-time streaming, dual-axis, radar charts |
| Mulberry32 PRNG | Seedable random numbers | Reproducible synthetic data generation |
| Box-Muller Transform | Gaussian noise | Converting uniform → normal distribution |
| OLS Linear Regression | Trend extrapolation | Normal equations, R² coefficient |
| EMA / SMA | Signal smoothing | Exponential vs simple moving averages |
| Ring Buffers | Time-series storage | O(1) append with bounded memory |
| Rule Engine | Threshold alerting | Declarative rules with dedup cooldowns |
| CSS Custom Properties | Theming | Single source of truth for design tokens |
| CSS Grid + Flexbox | Responsive layout | Desktop-first with graceful degradation |
# Option 1: Python's built-in HTTP server
cd ARES-E
python3 -m http.server 8080
# Open http://localhost:8080
# Option 2: Node.js (npx, no install needed)
npx serve .
# Option 3: VS Code Live Server extension
# Right-click index.html → "Open with Live Server"- Push all files to the
mainbranch - Go to Settings → Pages
- Set source to Deploy from a branch →
main→/ (root) - The dashboard will be live at
https://<username>.github.io/ARES-E/
- PHIAK: Zero individual patient data — all metrics are population-level aggregates
- HIPAA Safe Harbor: 45 CFR §164.514(b) compliant by architecture
- No tracking: No cookies, no analytics, no external API calls
- Client-side only: All computation runs in the browser
- Content Security: CSP headers in worker.js, X-Frame-Options, no-referrer
MIT License — see LICENSE for details.
DaScient, LLC — Systematically addressing deep tech issues in critical infrastructure