Use Cases (Enterprise)

This page shows real-world, enterprise-grade scenarios where MapexOS delivers measurable value. Each use case is presented as an isolated block containing:

• Problem (business impact)
• Solution (how MapexOS solves it)
• Event sources (what generates data)
• Stateful business rule example (complex logic with Redis-backed state)
• Actions / Triggers (automation outputs)
• Persistent logs (audit + search + observability)
• Outcomes (what improves in the operation)

Recommended reading

To understand how stateful conditions, groups (match all/any/not), triggers, and persistent logs work internally, see:

• Architecture Overview
• Rule Engine Overview

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Beyond IoT: MapexOS as a Universal Event Processing Platform

Although MapexOS is designed for high-throughput IoT ingestion, it is fundamentally an event platform. Any third-party system that can produce events (webhooks, message buses, APIs) can be integrated and processed through the same enterprise pipeline:

Ingest → Validate → Transform → Route → Store → Automate → Audit

This means MapexOS can unify IoT telemetry and business events under one operational backbone—enabling consistent governance, automation, and observability across your organization.

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1) Vaccine Freezer Monitoring (Cold Chain)

Problem

Vaccine storage requires strict temperature control. A few minutes above threshold can destroy an entire batch. Most systems fail due to:

• noisy alerts (spam during door opens)
• lack of escalation logic
• missing audit trail for compliance

Solution (MapexOS)

MapexOS turns freezer telemetry into a stateful incident workflow:

• correlates temperature with door state
• suppresses duplicate alerts with cooldown
• escalates only when persistence confirms a real violation
• persists a complete audit record of every match

Event sources

• Temperature sensor (periodic readings)
• Door sensor (open/closed)
• Power status (optional)
• Compressor status (optional)

Stateful business rule example (enterprise)

Intent: Alert only when the freezer is actually failing, not during normal door openings.

Condition Group: MATCH_ALL

• eventType == "temperature.reading"
• data.tempC >= THRESHOLD_HIGH
• state.door_state == "closed"
• MATCH_ANY (cooldown)
  • state.last_notification_at does not exist
  • OR now - state.last_notification_at >= COOLDOWN_MIN
• NOT_MATCH_ANY (suppression window)
  • state.suppress_until exists AND now < state.suppress_until

State Triggers

• increment("violation_streak")
• set("last_notification_at", now)
• set("suppress_until", now + 10min)

Action Triggers

• Slack / Teams: send High Severity alert
• Webhook (ITSM): open incident when violation_streak >= 3
• NATS/Kafka: publish coldchain.violation.detected

Persistent Log Store an immutable log entry containing:

• tempC, threshold, door_state, violation_streak
• org/site/zone context
• rule version + businessRule id
• custom metadata (batch ID, freezer model, etc.)

Outcomes

• fewer false positives
• faster response times via escalation policy
• compliance-grade traceability (auditable logs)

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2) Legionella Risk Control in Hospitals (Water Safety)

Problem

Hospitals must prevent Legionella growth in water systems. The risk is not just low temperature—it is low temperature + stagnation + persistence over time. Compliance requires evidence, not just notifications.

Solution (MapexOS)

MapexOS detects risk conditions using multi-signal correlation, maintains risk duration state, and opens incidents only when the condition persists.

Event sources

• Hot water temperature sensors
• Flow sensors (or inferred usage)
• Chlorine level sensors (optional)

Stateful business rule example (enterprise)

Intent: Trigger only when a critical zone remains in risky conditions long enough to require intervention.

Condition Group: MATCH_ALL

• eventType == "water.temperature"
• zone.isCritical == true
• data.tempC < 50
• MATCH_ANY (stagnation indicators)
  • data.flowRate == 0
  • OR data.flowRate < MIN_FLOW
• Persistency confirmation:
  • increment("low_temp_duration_min")
  • match only if low_temp_duration_min >= 15

Cooldown logic

• now - state.last_alert_at >= 30min OR state.last_alert_at missing

Triggers

• Teams/Slack: send critical alert to Facilities + Compliance
• Webhook: open a maintenance task / incident
• State:
  • set("incident_open", true)
  • set("last_alert_at", now)
  • set("suppress_until", now + 30min)

Persistent Log Save:

• tempC, flowRate, duration, critical_zone
• recommended action (flush loop, temperature raise, inspection)

Outcomes

• prevents silent high-risk conditions
• reduces operational noise
• creates defensible compliance evidence via persistent logs

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3) Air Quality (CO₂ / Humidity) with Occupancy + HVAC Correlation

Problem

CO₂ spikes are common, but alerts are meaningless without context. A room with high CO₂ but no occupancy may not require immediate action. Enterprise environments require context-aware escalation.

Solution (MapexOS)

MapexOS correlates air quality events with occupancy and HVAC state, then escalates only when conditions persist and matter.

Event sources

• CO₂ + humidity sensors
• Occupancy sensors (people count)
• HVAC/BMS integrations (optional)

Stateful business rule example (enterprise)

Intent: Alert only when CO₂ is high AND the room is occupied AND ventilation is ineffective.

Condition Group: MATCH_ALL

• eventType == "air.quality"
• data.co2ppm > 1000
• state.occupancy_avg_5m >= 3
• MATCH_ANY (ventilation ineffective)
  • state.hvac_state == "off"
  • OR computed.co2_trend == "increasing"
• Persistency:
  • increment("co2_violation_streak")
  • match only if co2_violation_streak >= 10

Cooldown

• allow alert when now - last_alert_at >= 60min

Triggers

• Teams/Slack: notify operations with recommended action
• Webhook: trigger HVAC adjustment (if integrated)
• State:
  • set("last_alert_at", now)
  • set("suppress_until", now + 10min)

Persistent Log Save:

• co2ppm, occupancy, hvac_state, trend, duration
• business impact tags (comfort, productivity, safety)

Outcomes

• contextual alerts with actionability
• reduced alert fatigue
• insights for ventilation optimization over time

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4) Predictive Maintenance (Vibration + Temperature + Trend)

Problem

Fixed thresholds alone do not prevent failures. Most industrial failures emerge as trends: rising vibration, temperature drift, repeated anomalies. Enterprise teams need predictive signals and traceability.

Solution (MapexOS)

MapexOS maintains computed state windows (rolling averages, slopes) and triggers incidents when trend + severity align.

Event sources

• Vibration (RMS / spectrum)
• Motor temperature
• RPM / load (optional)

Stateful business rule example (enterprise)

Intent: Open a predictive maintenance incident when vibration trend indicates impending failure.

Condition Group: MATCH_ALL

• eventType == "motor.vibration"
• data.rms > RMS_MIN
• Computed state window:
  • set("vibration_sum_10m", sum(last 10 minutes))
  • set("vibration_avg_10m", vibration_sum_10m / count)
  • set("trend_slope", slope(last N points))
• Trend confirmation:
  • vibration_avg_10m > BASELINE * 1.5
  • trend_slope > SLOPE_LIMIT
• Cooldown:
  • now - last_alert_at >= 120min

Triggers

• Webhook: create maintenance work order
• Slack/Teams: notify maintenance team
• NATS/Kafka: publish predictive event
• State:
  • set("last_alert_at", now)
  • set("incident_open", true)

Persistent Log Save:

• baseline, avg, slope, rms, window details
• recommended action (inspection, bearing check, shutdown plan)

Outcomes

• earlier detection of failures
• reduced downtime and emergency maintenance cost
• measurable reliability improvement (MTBF increase)

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5) Energy Anomaly Detection (Out-of-Hours + Exception Windows)

Problem

Energy waste is often invisible until the bill arrives. But naive alerts create noise during planned maintenance or exception windows. Enterprise needs exception-aware anomaly detection.

Solution (MapexOS)

MapexOS detects abnormal consumption outside business hours while respecting maintenance mode and cooldown suppression.

Event sources

• Power meters (kW, kWh)
• Maintenance window schedule (system event / webhook)
• Site operational calendar (optional)

Stateful business rule example (enterprise)

Intent: Alert on abnormal consumption when the site should be idle and no exceptions are active.

Condition Group: MATCH_ALL

• eventType == "energy.reading"
• computed.isOutsideBusinessHours == true
• data.kW > state.night_baseline_kW * 1.3
• NOT_MATCH_ANY
  • state.maintenance_mode == true
  • OR state.override_mode == true
• Persistency:
  • increment("overuse_streak")
  • match only if overuse_streak >= 15 (15 minutes)

Cooldown

• now - last_alert_at >= 2h

Triggers

• Slack/Teams: send anomaly alert to facilities
• Webhook: open investigation ticket
• State:
  • set("last_alert_at", now)
  • set("suppress_until", now + 2h)

Persistent Log Save:

• kW, baseline, streak, time window, exception flags
• asset/site/floor context for analysis

Outcomes

• reduced energy waste
• fewer false alerts during maintenance windows
• actionable anomaly intelligence for facilities teams

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6) Retail Footfall + Incident Lifecycle Control

Problem

Retail operations must react to crowding (safety, staffing, queue management). A naive approach creates repeated incidents with no lifecycle control.

Solution (MapexOS)

MapexOS uses stateful counters and incident lifecycle gating:

• accumulate incremental counts
• open incidents only when none is active
• hold alerts while an incident remains open
• persist logs for analysis and staffing optimization

Event sources

• People counters (increment events every minute)
• Camera analytics (optional)
• Queue sensors (optional)

Stateful business rule example (enterprise)

Intent: Open an operational incident when cumulative footfall crosses a threshold, but never spam while incident is open.

Rule A: Create incident when threshold reachedCondition Group: MATCH_ALL

• eventType == "people.increment"
• increment("people_accumulator", data.increment)
• match only if state.people_accumulator >= 100
• state.incident_open != true

Triggers

• Webhook ITSM: create incident
• Slack/Teams: notify operations manager
• State:
  • set("incident_open", true)
  • set("people_accumulator", 0)

Persistent Log Save:

• accumulator, threshold, site/zone, incident id reference

Rule B: Gate repeated triggers while openCondition Group: MATCH_ALL

• state.incident_open == true
• state.people_accumulator >= 100

Triggers

• Persistent log only (no new incident), for audit and analysis

Outcomes

• controlled operational workflow
• fewer repeated incidents
• strong analytics foundation for staffing decisions

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7) Social / Webhook Events (Instagram as an example)

Problem

Operations and growth teams handle large volumes of inbound messages and comments. Manual triage creates delays and missed opportunities. Enterprise automation requires dedupe, routing, and tracking.

Solution (MapexOS)

MapexOS ingests webhooks and third‑party events as standardized events, applies stateful rules, routes data to downstream systems, triggers workflows, and persists logs for reporting.

Event sources

• Instagram webhook events (DMs, comments, keywords)
• CRM events (optional)
• Support platform events (optional)

Stateful business rule example (enterprise)

Intent: Create a lead and notify the team only once per conversation, with cooldown routing.

Condition Group: MATCH_ALL

• eventType == "instagram.message_received"
• MATCH_ANY (keyword routing)
  • message contains "price"
  • OR message contains "mentoria"
  • OR message contains "quero entrar"
• state.lead_assigned != true
• MATCH_ANY (cooldown)
  • state.last_route_at missing
  • OR now - state.last_route_at >= 5min

Triggers

• Webhook CRM: create/update lead
• Slack: notify sales/support channel
• State:
  • set("lead_assigned", true)
  • set("last_route_at", now)

Persistent Log Save:

• profile id, message id, detected keyword, routing action
• tags for later reporting (campaign, channel, intent)

Outcomes

• faster response time
• fewer missed leads
• consistent audit trail for reporting and SLA

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8) Enterprise Systems Integration (ERP / CRM / Payments)

Problem

Enterprise operations depend on multiple systems—ERP, CRM, billing, payment gateways, logistics, and support platforms. These systems often run as isolated islands, which creates:

• slow handoffs between teams
• manual reconciliation
• fragmented visibility and audit trails
• delayed reaction to critical business events (failed payments, urgent orders, SLA breaches)

Solution (MapexOS)

MapexOS treats third‑party system events the same way it treats IoT telemetry:

• receives events via HTTP webhooks or message buses
• validates and normalizes payloads into a standardized event
• routes events to multiple destinations
• applies stateful rules to coordinate workflows and reduce noise
• persists logs for traceability and compliance

Event sources

• Payment gateway webhooks (authorized, failed, chargeback)
• CRM events (new lead, stage changed)
• ERP events (order created, stock low)
• Support system events (ticket opened, SLA risk)

Stateful business rule example (enterprise)

Intent: Escalate high-value orders with payment instability, but avoid duplicate escalations.

Condition Group: MATCH_ALL

• eventType == "payment.event"
• data.status IN ["failed", "chargeback"]
• data.orderValue >= HIGH_VALUE_THRESHOLD
• MATCH_ANY (risk pattern)
  • increment("payment_fail_count_10m") >= 3
  • OR data.status == "chargeback"
• MATCH_ANY (dedupe / cooldown)
  • state.last_escalation_at missing
  • OR now - state.last_escalation_at >= 60min
• NOT_MATCH_ANY (manual review already started)
  • state.manual_review_started == true

State Triggers

• set("last_escalation_at", now)
• set("escalation_active", true, TTL=2h)
• set("manual_review_required", true)

Action Triggers

• Slack/Teams: notify Finance + Ops with full context
• Webhook: create a review task in ERP/ITSM
• NATS/Kafka: publish business.risk.escalation

Persistent Log Store:

• payment status, attempt counters, order value, customer id
• rule + businessRule ids, timestamps
• custom tags (region, channel, product family)

Outcomes

• faster reaction to revenue and fraud risks
• fewer manual handoffs and duplicated alerts
• end-to-end audit trail across business systems

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9) Security: Restricted Zone Intrusion (Event Correlation + Escalation)

Problem

Security systems often generate alerts with limited context. Enterprise environments require correlation and escalation when repeated behavior occurs.

Solution (MapexOS)

MapexOS correlates motion/door access events, maintains attempts counters, and escalates only when patterns indicate intrusion risk.

Event sources

• Door access control (granted/denied)
• Motion sensors
• Camera analytics (optional)

Stateful business rule example (enterprise)

Intent: Escalate only when denied access and motion occur in sequence, repeated within a short window.

Condition Group: MATCH_ALL

• eventType == "access.denied"
• zone.isRestricted == true
• State:
  • increment("denied_attempts_10m")
  • set("last_denied_at", now, TTL=10m)
• match only if denied_attempts_10m >= 3

Correlated escalation

• if motion.detected occurs and now - last_denied_at < 2min → severity increases

Triggers

• Teams/Slack: critical alert to security
• Webhook: activate escalation workflow
• State:
  • set("suppress_until", now + 15min)

Persistent Log Save:

• attempts, timestamps, zone, correlated motion flag, severity

Outcomes

• fewer false alerts
• faster security response to real threats
• auditable security event history

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Cross‑industry patterns (Reusable Stateful Automation)

These patterns appear across nearly all enterprise use cases:

• Cooldown / Deduplication: avoid sending the same alert repeatedly
• Persistency confirmation: trigger only after a condition remains true for N minutes/events
• Hysteresis: separate thresholds for entering/exiting alarm state
• Incident lifecycle gating: prevent re-opening incidents while one is still active
• Event correlation: combine multiple event types into a higher confidence decision
• Computed state windows: rolling averages, trends, and slopes for predictive signals
• Persistent logs as a product feature: auditability + search + reporting

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Data retention and search (per tenant)

Events and rule logs can be persisted for search and audit. MapexOS supports per-tenant retention policies (TTL) so each customer can control how long data remains available.

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Protocol roadmap

Available in v1.0.0

• HTTP
• MQTT

Coming next

Future versions will add additional protocol support, including:

• CoAP
• LoRaWAN

Please refer to the MapexOS Roadmap for details.