The iViu Insights Platform
How It Works, Use Cases & Simulations
A complete guide to the iViu Insights signal intelligence and consumer analytics platform — the sensing technology, the real-time processing pipeline, the analytics it produces, the industries it serves, and the interactive simulations that demonstrate it in action.
Table of Contents
One sensing platform.
Two families of intelligence.
iViu Insights has been developing scalable indoor and perimeter positioning technologies since 2013. The platform delivers real-time, high-accuracy intelligence supporting safety, security, analytics, and business decision-making across critical infrastructure and commercial environments. It is engineered for straightforward deployment: install patented iDTag™ sensors, connect them to a network, and the platform does the rest — no site surveys, no fingerprint databases, no recalibration cycles.
Every capability is built on the same foundation: iDTag sensors passively detect Wi-Fi-enabled devices — smartphones, tablets, wearables — hundreds of times per second, at position accuracy under one meter. That single stream of anonymous device observations powers two product families: Signal Intelligence (SIGINT) for perimeter protection and threat detection, and Consumer Journey Analytics for understanding how people move through and engage with physical spaces.
The platform at a glance
What makes it different
Self-Calibrating
- Adapts automatically to environmental changes — moved fixtures, new walls, seasonal layouts
- No fingerprinting surveys or manual recalibration, ever
- Sensors are plug-in devices: power plus network is all that is required
Passive & Anonymous
- No app installs, no beacons, no opt-in required from visitors
- Device identifiers are anonymized and encrypted at the point of collection
- Defeats MAC randomization without ever identifying a person
Real-Time & Historical
- Proximity alerts published within one to three seconds of detection
- Live occupancy and positioning views for operations teams
- Deep historical analytics — dwell, journeys, conversion, repeat visits
From raw RF signal to intelligence,
in six stages.
Every insight the platform produces — a security alert, a conversion metric, a heatmap — begins as a radio-frequency observation made by an iDTag sensor. The pipeline below runs continuously, at every monitored location, processing hundreds of millions of samples per day.
A layered, service-oriented architecture.
The platform is composed of independent, horizontally scalable services organized in five layers. Each layer communicates through well-defined interfaces — message queues, databases, and REST APIs — so capacity can be added exactly where a deployment needs it, from a single store to a national sensor network.
Infrastructure & operations
SIGINT — real-time proximity
detection and threat response.
The SIGINT platform turns the sensor field into a continuous perimeter-intelligence system. Sensors at a protected location passively observe every RF-emitting device nearby — each identified by an anonymous device identifier, estimated distance, signal strength, and first/last-seen timestamps. The platform evaluates those observations against rules configured per location: minimum signal strength, proximity thresholds, dwell time, and device classification.
When rule conditions are met, a structured alert is published to connected security systems within one to three seconds. There is no polling and no REST round-trip — alert delivery is pure machine-to-machine messaging over encrypted MQTT, authenticated with mutual-TLS client certificates issued by iViu. A fully automated integration completes the entire detect → alert → resolve loop in under one second.
The alert lifecycle
Resolution message types
| Resolution | Effect on the platform |
|---|---|
| clear_alert | Closes the alert with a named operator action; no change to the device's future treatment. |
| authorize_device | Closes the alert and marks the device as authorized — suppressing future alerts for that device at the location. |
| bad_actor_device | Closes the alert and flags the device as a known bad actor, elevating future detections. |
| register_event | Records a security event against the device without changing its classification. |
| alert_event_reg | Combined operation — closes the alert and registers the event in a single message. |
Collective threat intelligence
Devices flagged as bad actors contribute to a collective threat intelligence network. A device flagged at one participating location can be recognized when it appears at another — turning isolated deployments into a shared early-warning system for organized retail crime, critical-infrastructure reconnaissance, and repeat offenders.
Understand every visit —
without identifying anyone.
The analytics side of the platform answers the questions physical businesses have always envied online retailers for: How many people came in? How many walked past? Are they new or returning? Where did they go, how long did they stay, and did they buy? Because de-randomization produces stable anonymous device identities, these measurements are accurate over time — repeat-visit and loyalty metrics actually work.
Analytics are computed continuously and delivered through the Foot Traffic Analytics dashboards, the partner portal, summary data feeds, and REST APIs. Every metric is available per location, per zone, per hour, and per day — with journey playback for individual anonymous visits.
Key performance indicators
Analytics views
Live Dashboard
- Live KPI cards with real-time visitor counts
- Daily visitor trend charting
- Period summary comparison tables
Heatmap & Zones
- Zone-by-zone visit volume with heat scoring
- Peak-hour identification per zone
- Per-zone dwell analytics by day
Journey Playback
- Anonymous per-device position playback on the floor plan
- Path, sequence, and dwell at each stop
- Customer journeys only — staff and equipment filtered out
Visitor Analytics
- New vs repeat stacked trends
- Dwell-time trend analysis
- Hourly traffic patterns by visitor type
Count Reports
- Daily visitor type breakdown tables
- Hourly traffic counts by classification
- Exportable for BI ingestion
Data Feeds & APIs
- Scheduled summary data feeds to cloud storage
- REST APIs for KPIs, traffic, heatmap, and journeys
- MQTT machine-to-machine integration for live events
Anonymous by default.
Encrypted end-to-end.
The platform measures devices, not people. No names, phone numbers, photos, payment data, or app accounts are ever collected — there is nothing to breach that could identify an individual. Device identifiers are anonymized and encrypted at the point of collection, and de-randomized identities remain purely statistical constructs used for counting and journey continuity.
Security follows the same discipline as the sensing: every transport in the platform is encrypted, every machine-to-machine connection is authenticated with mutual-TLS certificates, and every human-facing portal enforces token sessions with optional TOTP two-factor authentication and per-application authorization.
Privacy Commitments
- No personally identifiable information collected — ever
- Anonymized, encrypted device records at collection time
- Public self-service opt-out portal for any device owner
- Data retention windows configurable per deployment
- Designed to support GDPR/CCPA-aligned deployments
Security Controls
- Mutual-TLS certificate authentication for all M2M connections
- Encrypted MQTT (port 8883) — no password-only broker access
- Portal sessions with expiring tokens and TOTP 2FA
- Per-user, per-application authorization in the partner portal
- Automated backups with tested restore procedures
Twelve scenarios. One platform.
The same sensors and pipeline serve radically different missions depending on the rules and analytics enabled. These twelve scenarios — each with a corresponding interactive simulation (Section 08) — span the security-to-analytics spectrum.
See the platform work —
before a single sensor ships.
The iViu use case simulations are interactive, browser-based recreations of live platform deployments. Each simulation renders a realistic site — a store, a cell tower compound, a border segment, a dealership lot — with iDTag sensors placed exactly as they would be in a real installation, and animated devices moving through the space the way real visitors, staff, vehicles, and intruders do.
As synthetic devices move, the simulation shows precisely what the platform would do at every moment: sensors detecting devices in range, positions resolving on the floor plan, classification decisions, KPI counters accumulating, and — in the security scenarios — proximity rules firing live alerts with dwell timers and distance readouts. It is the full sense → detect → alert → resolve lifecycle from Section 04, made visible.
What each simulation demonstrates
Sensor Coverage
- Real sensor placement geometry for the site type
- Detection range and overlap visualization
- How few sensors a deployment actually needs
Live Detection
- Devices appearing, moving, and dwelling in real time
- Visitor vs staff vs vehicle classification
- Position tracking at sub-meter accuracy
Alerts & KPIs
- Proximity and dwell rules firing as thresholds are crossed
- Bad-actor recognition and re-identification
- Traffic and conversion KPIs accumulating live
The twelve simulations
All twelve industry scenarios from Section 07 are available as simulations at iviuinsights.com/simulations.html — Construction Site, Distribution Center, Big-Box Retail, Big-Box Interior, Shopping Center, Small Store, Car Dealership, Apartment Complex, Border Perimeter, Cell Site, Store Interior · Bad Actor, and Convenience Store. Each runs directly in the browser; no installation is required.
Access: Simulations are access-code protected. Codes are provided to customers, partners, and qualified prospects — contact sales@iviutech.com to request access. Once unlocked, all twelve simulations are available for the duration of your browser session.
From site survey to live intelligence.
Deployment path
Integration surfaces
Ready to see it on your site? Contact sales@iviutech.com for a deployment consultation, an evaluation unit, or simulation access — or reach the team via the contact form at iviuinsights.com.
iDTag™ sensor — hardware at a glance.
The iDTag™ is a compact, industrial-grade RF sensor engineered for continuous unattended operation. The specifications below summarize the production hardware; the complete datasheet is published at iviuinsights.com/spec-sheet.html.
Physical & environmental
Radio
Detection capabilities
Compliance & connectivity
The questions every evaluation team asks.
Detection & identification
The platform uses the 2.4 GHz band and extends coverage across the full Wi-Fi RF spectrum to trigger alerts. Sensors capture samples, and heuristics based on range, time-seen, sample count, time-of-arrival, and other features vet every sample before it is recorded as a RAW event. That vetting filters out multipath, reflections, and amplified or interfering signals — so only validated RF emissions progress to alert logic.
UDIDs originate from the radio emissions of nearby Wi-Fi devices. The platform derives a proprietary unique device ID from the device's emitted information elements — roughly 227 possible radio-level data elements including manufacturer and vendor fields and probe/management frame characteristics.
Because the UDID is computed from low-level radio characteristics rather than broadcast OS or app identifiers, it cannot be cloned or spoofed by copying an advertised name or leaving a device behind. The UDID is based on the radio hardware signature — not an app or OS-provided ID.
Proximity estimation and positioning depend on sensor density and geometry — three or more sensors provide the best accuracy, and inter-sensor spacing directly affects positioning quality. All positioning is RSSI-based at the core, but raw samples are processed with heuristic modeling similar to concepts used in UWB systems: time-of-arrival patterns, historical position models for each transmitter, and trilateration across as many data points as available, selecting the modal or most consistent result.
Accuracy is environment-dependent. Sites go through a burn-in period so the heuristic model can learn site-specific patterns and compensate for obstacles such as metal containers, scaffolding, or structural steel. Additional sensors may be added to meet tighter accuracy requirements.
Documented practical detection coverage is 1,200 ft in diameter — extending to over 1,500 ft in rural open space — with positioning accuracy generally within 3 ft, depending on sensor density.
Masking & access rules
Masking uses a combination of methods: whitelisting and authorized-device designations, virtual zones (fences), sample-count thresholds, RSSI (distance) filters, dwell-time rules, and other site- or customer-specific parameters. Templates for common site types are available out of the box.
Yes. Masking and authorization rules can be site-specific and role-specific — a security guard, subcontractor, general contractor, and delivery driver can each be handled as a different class of personnel and device. Sites can also carry open-hours rules and other site-specific policies, which substantially reduces false alarms across all deployments.
No names. No emails. No phone numbers. No PII. Ever.
iViu was built from the ground up on a single principle: location intelligence should never require collecting personal information. Sensors detect and analyze RF signal emissions from wireless devices in the environment — no user action, app installation, or account registration is required or possible. This section summarizes the full Privacy Policy published at iviuinsights.com/privacy-policy.html (effective January 1, 2024 · revised May 2026 · GDPR & CCPA aligned).
What the sensor platform collects
| Data element | Description | Stored? |
|---|---|---|
| Hashed Device ID | One-way cryptographic hash derived from the device's RF characteristics — cannot be reversed to identify the device or its owner | Yes |
| Signal Strength | RSSI, used solely for positioning calculations | Yes |
| Frequency / Channel | RF channel on which the signal was observed | Yes |
| Timestamp | Date and time of detection, for dwell-time and flow analytics | Yes |
| Sensor ID / Zone | Which iDTag™ detected the signal, mapped to a venue zone | Yes |
| Raw MAC Address | Discarded immediately upon receipt — never written to storage | Never |
What is never collected — by architecture
Architecturally impossible
- Names, usernames, email addresses, phone numbers
- Home addresses and government-issued ID numbers
- Financial account or payment card information
- Biometric, health, or demographic data
- Device contents — messages, calls, browsing, app data
- Location history outside the venue where sensors are deployed
How data is used — and never used
- Indoor positioning and aggregated foot-traffic analytics
- SIGINT security functions in critical-infrastructure deployments
- Internal calibration using de-identified aggregate datasets
- Never used for ad targeting or individual behavioral profiling
- Never resold to data brokers
- Never applied beyond the service contracted by the deploying partner
Retention & rights
The sensor platform detects presence and movement in a physical space. It does not know — and has no mechanism to learn — who you are. This is an architectural guarantee, not a policy preference.