Scattered equipment data turned into clear dashboards for operational decisions
Custom ThingsBoard dashboards for device telemetry, industrial sensor measurements, equipment status, operational trends and alerts.
In industrial environments, sensor and equipment data is often spread across separate systems, local displays or even manual logbooks. To get an overview of a production line or a mining site, operations staff have to check several different sources.
Under these conditions, gradual trends such as a slowly rising temperature or vibration level are noticed late, and alerts are either too numerous or never reach the right person. A dashboard designed around the role and needs of each user can help close this gap.
This project focuses on designing custom dashboards in ThingsBoard. Telemetry reaches the platform via MQTT or other integrations, is organized into devices and assets, and is processed by the rule engine and evaluated for alarms.
Dashboards are designed on several levels: a site overview for managers, a line or area view for supervisors and a detailed device view for technical staff. Each level shows only the indicators needed for decisions in that specific role. The images on this page are conceptual and do not depict a system in production use.
Sensors and equipment that send data directly or through a gateway.
Lightweight, reliable delivery of telemetry and device attributes to the platform.
Devices, assets and their relations organized to mirror the site structure.
Data processing, derived values and threshold-based alarm creation.
Site, line and device views with time-series charts and status indicators.
A ThingsBoard dashboard is useful when it answers a specific question. Design therefore starts from the questions each role asks, not from the list of sensors: "Which equipment has a problem right now?", "How has this motor's temperature developed over the past week?", "Which devices have stopped sending data?". Every widget should answer one of these questions.
Data arrives in ThingsBoard via MQTT. Rule chains validate it, compute derived values such as averages or calculated states, and raise alarms when thresholds are crossed. Alarms have severity levels and can be acknowledged and tracked, which helps prevent a backlog of unanswered alerts.
For security and maintainability, each device has its own credentials, connections are encrypted, and user access is defined by role and site scope. Consistent naming of devices and telemetry keys makes it easier to add new equipment later. Because connectivity differs from site to site, the data model does not assume a particular network: whether devices report over a wired network, cellular or LoRaWAN, the dashboards work with the same telemetry structure.
The structure can be extended with periodic reports, equipment performance indicators and a connection to maintenance management systems. The same approach applies to industrial monitoring and smart mining projects.
ThingsBoard is an open-source IoT platform widely used for industrial monitoring. This article explains its data model, rule engine, alarms, dashboards, deployment options and security considerations.
A technical guide to MQTT for industrial IoT projects: publish/subscribe, topic design, QoS levels, retained messages, MQTT 5 features, TLS security and how MQTT compares with OPC UA and HTTP.
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Let’s discuss how this approach could be adapted to your equipment and requirements.
