A Smart, IoT Enabled Fuel Tank Monitoring System

A scalable IoT data collection platform that enables you to access data rapidly from a vast array of sensors, machines and devices. Integrated GSM and GPRS along with a host of other communications technologies delivers a comprehensive fuel tank monitoring system.

Start Collecting Your Data
Scroll to discover
Scroll to discover

Flexible Selection of building Blocks

MetronView is compatible with a vast assortment of input sensors and probes. Our smart fuel tank monitoring system integrates with a myriad of communications technologies to gather all your IoT data in one cloud-based database, where you can view current and historic data on customisable dashboards, with the ability to send alarms for triggered scenarios, remotely manage your input devices and controls devices and perform mathematical and logical operations, such as anomaly detection.

Comprehensive APIs and well-crafted documentation allow integration to software like Navision, SAP, SCADA and platforms like IBM Watson, Microsoft Azure, AWS and Miimetiq. It also you to develop application-specific portals, that serve purposes unique to your business's operations, for example, you could power a custom bulk delivery and collection application for oyur company.


MetronView may be used globally for tank level monitoring and for vendor managed inventory, where the product is delivered or collected to multiple bulk tanks.

Get creative with all sorts of customisable dashboards, communicate timeously by sending alarms and alerts as well as remotely manage various telemetry devices in the field.

Customisable Fuel Tank Theft Alarm System

Our fuel tank theft alarm can utilise a Metron4 gauge (or other sensor and tank level monitoring device), mains supply with battery back-up, relays for connection to external alarms and inconspicuous housing.

With this configuration linked to MetronView, you will have a wealth of current and historic data to simulate any scenario that will form your alarm system trigger, a data-based model for determining when something is wrong.