Automated fuel usage and inventory monitoring

Purpose

1. Monitor, log, and report aircraft and vehicle fuel usage in real-time for optimized inventory management.
2. Automate fuel level alerts, threshold triggers, replenishment requests, and consumption analytics across multipoint supply chains.
3. Integrate telemetry with asset tracking, predictive maintenance, and regulatory compliance.
4. Eliminate manual data entry, reduce fuel pilferage, and enhance mission-readiness through continuous supply chain visibility.

Trigger Conditions

2.1. Deviation in scheduled or expected fuel usage detected via fuel sensor telemetry.
2.2. Fuel tank level falls below set percentage (e.g., 10%) or time-based thresholds.
2.3. Scheduled inventory reconciliation interval reached (e.g., daily/weekly/monthly).
2.4. Sensor, pump, or dispenser fault event detected.
2.5. Fuel request or transfer initiated from asset tracking database/API.

Platform Variants

3.1. AWS IoT Core
• Feature/Setting: MQTT Device Shadow; configure for ingesting fuel sensor payloads, rules engine triggers on threshold breach.

3.2. Microsoft Power Automate
• Feature/Setting: "When an HTTP request is received" connector; initiate workflow for real-time fuel alerts and database update.

3.3. Google Cloud Pub/Sub
• Feature/Setting: Fuel sensor event topic; subscriber triggers replenish event or maintenance workflow on message receipt.

3.4. ThingSpeak
• Feature/Setting: REST API for input channel; send fuel telemetry for visualization and alert set on field threshold.

3.5. SAP Leonardo IoT
• Feature/Setting: Thing Templates for fuel meters; trigger notifications, interface to SAP ERP for inventory deductions.

3.6. IBM Maximo
• Feature/Setting: Integration Framework with REST API; auto-create asset work order for supply if low fuel detected.

3.7. Oracle Autonomous Database
• Feature/Setting: Always Free Monitoring Agents; schedule SQL jobs to email anomalies or leaks in usage logs.

3.8. Siemens MindSphere
• Feature/Setting: Asset Manager Fuel Asset model; configure rule for low-level event and inventory notification.

3.9. Splunk
• Feature/Setting: HTTP Event Collector for sensor logs; real-time alert triggers via search queries and dashboard.

3.10. Tableau Server
• Feature/Setting: Live connection to fuel database/API; visualize tank level trends and audit usage.

3.11. ServiceNow
• Feature/Setting: Flow Designer; connect to IoT API, trigger operational task for re-supply ticket.

3.12. Twilio Programmable SMS
• Feature/Setting: Send SMS on workflow trigger; configure phone number, fuel type, level, timestamp in message body.

3.13. PagerDuty
• Feature/Setting: REST Events API; send alert incidents when critical fuel thresholds are breached.

3.14. Azure Logic Apps
• Feature/Setting: IoT Hub Event Grid trigger; start process to notify inventory team and update supply logs.

3.15. Snowflake Data Cloud
• Feature/Setting: External Function for real-time ingestion; scheduled query to generate low-fuel reports.

3.16. MongoDB Atlas
• Feature/Setting: Trigger on insert/update for fuel event log collection; notify via webhook to command center.

3.17. GE Predix
• Feature/Setting: Asset Services API; set alarm rules for equipment with abnormal fuel consumption patterns.

3.18. Grafana
• Feature/Setting: InfluxDB data source; panel trigger alerts, notify stakeholders on trend line breaches.

3.19. Cisco Kinetic
• Feature/Setting: IoT Data Engine; transform and route fuel sensor data to mission control system on rule trigger.

3.20. Slack
• Feature/Setting: Incoming Webhook; automated message on #logistics when tank level or pump issue detected.

3.21. Google Sheets
• Feature/Setting: API append row with new event; fuel usage log accessible for quick, mission-critical review.

3.22. Salesforce
• Feature/Setting: Process Builder; create fuel inventory case/ticket if fleet asset at risk due to fuel shortage.

3.23. Alteryx
• Feature/Setting: Scheduled workflow; enrich sensor data with predictive analytics and automated reporting.

Benefits

4.1. Twinned real-time monitoring and alerting reduce downtime and manual audits.
4.2. Centralized analytics support predictive maintenance and better budgeting.
4.3. Rapid replenishment and compliance with operational standards ensured.
4.4. Incident reduction by automating threshold detection and notification processes.
4.5. Improved transparency, accountability, and asset lifespan through automated documentation and workflows.