Intelligence Agencies (OSINT / HUMINT / SIGINT)
Anticipate threats and increase analytic confidence.
Here are 10 numeric, per-entity/per-incident variables that are high-value for intelligence agencies (e.g., CIA, DIA, NSA, allied intel, fusion centers) and well suited to visualize using Immersion Analytics:
| # | Variable | What it is (numeric) | Why it matters | IA mapping |
|---|---|---|---|---|
| 1 | Event Probability (%) | Likelihood of the assessed event occurring | Focus attention on the most probable scenarios | X-axis (higher → right) |
| 2 | Threat Credibility (0–100) | Composite of capability × intent × opportunity | Prioritize credible threats | Y-axis (higher → up) |
| 3 | Potential Impact (0–5 / $) | Expected severity or loss estimate | Balance probability with consequence | Size (larger = higher impact) |
| 4 | Recency (hours) | Hours since last corroborated signal | Fresher signals often carry higher urgency | Z-depth (closer = more recent) |
| 5 | Source Reliability (0–1) | Quantified reliability/confidence in source | Reduce false positives and bias | Transparency (more solid = more reliable) |
| 6 | Corroboration Count (#) | Independent sources supporting the claim | Confidence rises with multi-source agreement | Satellites (more satellites = more corroboration) |
| 7 | Chatter Velocity (#/day) | Mentions/posts/messages per day on the topic | Detect buildup and mobilization trends | Pulsation (faster = higher velocity) |
| 8 | Geo Proximity to POI (km) | Distance to protected site/asset/route | Drives protective posture and timing | Color (hotter = nearer) |
| 9 | Network Centrality (score) | Betweenness/degree within the entity graph | Identify key facilitators and hubs | Glow (brighter = more central) |
| 10 | Deception/Disinfo Risk (0–100) | Model score for manipulation/spoofing | Guard analytic confidence and response | Shimmer (stronger = higher risk) |
What threats could you anticipate—and how many false positives could you retire—by seeing all ten, simultaneously, across entities, indicators, and geographies?
National Defense
Integrated Air & Missile Defense (IAMD)
Prioritize threats and accelerate defensive response.
Here are 10 numeric, per-track/per-engagement variables that are high-value in IAMD C2/BM environments (e.g., joint/coalition air picture with multi-sensor fusion and interceptor management) and well suited to visualize using Immersion Analytics:
| # | Variable | What it is (numeric) | Why it matters | Good IA mapping (suggestion) |
|---|---|---|---|---|
| 1 | Range to Defended Asset (km) | Slant range from track to protected site | Drives reaction time and priority | X-axis (far → right) |
| 2 | Altitude (km) | Track geometric height | Differentiates threat class & envelope | Y-axis (higher → up) |
| 3 | Closing Speed (m/s) | Relative inbound velocity | Indicates immediacy/severity | Color (hotter = faster) |
| 4 | Time-to-Impact (TTI, sec) | Estimated time to defended area | Core urgency metric | Z-depth (closer = sooner) |
| 5 | Track Quality / SNR (dB) | Measurement quality of the track | Confidence in kinematics & ID | Transparency (solid = higher quality) |
| 6 | Sensor-Fusion Confidence (0–1) | Agreement/consistency across sensors | Reduces false tracks & ambiguity | Glow (brighter = higher confidence) |
| 7 | Engagement Probability (Pk, 0–1) | Modeled probability of successful intercept | Guides weapon-target pairing | Shimmer (stronger = higher Pk) |
| 8 | Interceptor Availability (#) | Ready rounds in coverage for this track | Constrains shot doctrine choices | Satellites (more satellites = more available) |
| 9 | Engagement Time Margin (sec) | Slack vs. recommended fire timeline | Signals schedule risk | Pulsation (faster = low margin) |
| 10 | Sector Track Density (#/° or #/km²) | Nearby tracks within sector/window | Highlights saturation & deconfliction needs | Size (bigger = denser) |
What risk could you reduce—and how many seconds could you save in the decision loop—by seeing all ten, simultaneously, across the live air picture?
Multi-INT Fusion (ISR Common Operating Picture)
Here are 10 numeric, per-track/per-AOI variables that are high-value in Multi-INT fusion for an ISR COP (e.g., DCGS/IC COPs, Esri ArcGIS, Palantir, BAE GXP, Raytheon Solipsys) and well suited to visualize using Immersion Analytics:
| # | Variable | What it is (numeric) | Why it matters | Good IA mapping (suggestion) |
|---|---|---|---|---|
| 1 | Multi-INT Corroboration Count (#) | Distinct INT sources confirming a track (e.g., SIGINT/IMINT/GMTI/AIS/ADS-B/HUMINT/OSINT) | Higher corroboration = higher evidentiary weight | Satellites (more orbiters = higher count) |
| 2 | Track Confidence (0–1) | Fused probability that the track/ID is valid | Reduces false tracks and rework | Transparency (more solid = higher confidence) |
| 3 | Priority / Risk Score (0–100) | Fused threat/mission priority score | Directs scarce analyst and asset time | Glow (brighter = higher priority) |
| 4 | Time Since Last Contact (min) | Minutes since last detect/confirm | Highlights stale vs. active tracks | Pulsation (faster = more recent) |
| 5 | Pattern-of-Life Deviation (σ or %) | Deviation from entity/site baseline | Surfaces abnormal behavior quickly | Shimmer (stronger = larger deviation) |
| 6 | Dwell Time in AOI (min) | Cumulative minutes inside AOI/box | Indicates loitering/surveillance behavior | Size (larger = longer dwell) |
| 7 | Heading Change Rate (°/min) | Maneuver rate over window | Rapid course changes can signal intent | Color (hotter = higher rate) |
| 8 | Speed Anomaly (Δ% vs class) | Speed vs. typical for entity class | Flags out-of-profile movement | X-axis (right = larger anomaly) |
| 9 | Proximity to Protected Asset (km) | Distance from track to HVA/critical site | Drives alerting and ROE thresholds | Z-depth (closer = nearer) |
| 10 | Cross-Cue Latency (sec) | Time from sensor cue to confirm (e.g., GMTI→FMV) | Measures sensor orchestration efficiency | Y-axis (up = faster/shorter latency) |
What mission insight—and decision speed—could you unlock by seeing all ten, simultaneously, across your theater-level Common Operating Picture?
Fuse ISR and readiness to accelerate decisions.
Here are 10 numeric, per-mission/per-target (or per-area-of-operations) variables that are high-value in defense C2/ISR environments (e.g., JADC2-aligned C2 stacks, DCGS, TAK/ATAK, Palantir Gotham/Foundry, Esri, service-specific ops dashboards) and well suited to visualize using Immersion Analytics:
| # | Variable | What it is (numeric) | Why it matters | IA mapping |
|---|---|---|---|---|
| 1 | Threat Density (emitters/km²) | Count of hostile emitters/sensors per area | Prioritizes high-risk sectors | Y-axis (higher → up) |
| 2 | Blue Asset Readiness (%) | Mission-ready status of available platforms | Feasible tasking and risk posture | Transparency (more solid = higher readiness) |
| 3 | Time-to-Target (min) | Travel or engagement time from current position | Urgency and sequencing | Z-depth (closer = sooner) |
| 4 | Endurance Remaining (min) | Fuel/time-on-station left | Determines coverage gaps and swaps | Color (cooler/greener = more endurance) |
| 5 | Track Confidence (0–1) | Quality of identification/track continuity | Reduces false tracks and rework | Glow (brighter = higher confidence) |
| 6 | EW/Jamming Intensity (J/S dB) | Interference against comms/GNSS/radar | Impacts comms, nav, sensor performance | Shimmer (stronger = more interference) |
| 7 | Comms Latency (ms) | Round-trip delay across links/relays | Affects C2 timeliness and control | Pulsation (faster pulse = higher latency/instability) |
| 8 | ISR Coverage Assets (#) | Number of ISR assets tasked/overhead | Drives revisit rate and fidelity | Satellites (more satellites = greater coverage) |
| 9 | Civilian Density (persons/km²) | Population near activity/targets | Deconfliction; minimizes collateral risk | Size (bigger = denser) |
| 10 | Deconfliction Distance to Friendly (m) | Nearest friendly force distance | Prevents fratricide and air/ground conflicts | X-axis (left = closer) |
What mission risk could you retire—and how many minutes could you save in planning and execution—by seeing all ten, simultaneously, across every mission, target, and AO?
Critical Infrastructure & Emergency Response
Here are 10 numeric, per-incident/per-site variables that are high-value in emergency operations and critical infrastructure protection (e.g., EOCs, PSAPs/911 CAD, mass-notification, facilities ops) and well suited to visualize using Immersion Analytics:
| # | Variable | What it is (numeric) | Why it matters | Good IA mapping (suggestion) |
|---|---|---|---|---|
| 1 | Incident Severity (0–100) | Composite risk score | Drives triage and command focus | Y-axis (higher → up) |
| 2 | Asset Criticality (0–100) | Business/mission impact of the site/asset | Prioritizes what to protect first | X-axis (higher → right) |
| 3 | Time to Impact (min) | Minutes until hazard affects asset/people | Urgency and action window | Z-depth (closer = sooner) |
| 4 | Population Exposure (#) | People within defined radius/footprint | Life-safety scale of the event | Size (bigger = more exposed) |
| 5 | Response Time (min) | MTTA/MTTR or ETA of first units | Outcome predictor; SLA pressure | Color (hotter = slower) |
| 6 | Route Accessibility (% open) | Open routes vs closures/degradation | Feasibility of reaching the scene | Transparency (solid = more open) |
| 7 | Resource Gap (# units) | Needed − available teams/equipment | Reveals shortfalls to fill fast | Glow (brighter = larger gap) |
| 8 | Shelter Utilization (%) | Current occupancy vs capacity | Prevents overload; directs evacuees | Shimmer (stronger shimmer = nearer capacity) |
| 9 | SLA Breach Risk (min remaining) | Minutes until target response window is missed | Prevents penalties & harm | Pulsation (faster = nearer breach) |
| 10 | Nearby Incident Cluster (#) | Related incidents within X km/time | Signals cascade/secondary effects | Satellites (more satellites = larger cluster) |
What risk could you reduce—and how many response minutes could you save—by seeing all ten, simultaneously, across every site and incident?
