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Welcome to the official blog of the International Society of Automation (ISA).

This blog covers numerous topics on industrial automation such as operations & management, continuous & batch processing, connectivity, manufacturing & machine control, and Industry 4.0.

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Foundational Elements of Autonomous Remote Asset Monitoring Solutions

Industries such as manufacturing, construction, oil & gas, and healthcare rely on vital assets for their day-to-day operations. Inspecting the current state of such local and remote assets while tracking their utilization, health, and current location can be an overwhelming and time-consuming task. Still, assets cannot be left alone by their own devices—they need to be monitored. These asset-intensive industries need a solution that can keep control of and track their assets centrally. 

An IoT-enabled remote asset monitoring solution should centralize key activities such as monitoring, asset tracking, analytics, and management. It collects data from IoT-enabled assets deployed on equipment and machinery on-site and then integrates it into a single remote platform. 

The Five Foundational Factors for an Autonomous Remote Asset Monitoring Solution 

Organizations need the right set of integrated systems (hardware and software) with the optimal applications to achieve an effective real-time remote asset monitoring solution. 

Below are five factors or features that complete the asset monitoring solution: 

  1. Track assets and enforce geo-fences.
  2. Scalability and compatibility for multiple and different asset manufacturers.
  3. Provide a low-code to no-code for easier integration with third-party applications.
  4. Business-specific data analytics and aggregation.
  5. Predictive asset behavior and maintenance. 

Track Assets and Enforce Geo-fences 

Asset tracking is one of the fundamental features of any remote asset monitoring solution. It helps track assets to a precise geographical location using wireless or GPS technology and controls their movements with pre-defined virtual boundaries (geo-fencing). For instance, asset tracking may help identify the accurate geographic location of a truck with cargo on a map or even track smaller objects such as tablets or devices within the boundaries of a building. 

Asset tracking enforces asset control with geo-fencing. For example, an alert sets off or action is taken when the asset goes outside (or inside) the pre-defined geofence (a building, city, district, or county). 

Scalability and Compatibility for Multiple and Different Asset Manufacturers 

Internet of Things (IoT) and Industrial Internet of Things (IIoT) assets usually come with monitoring functionalities, which vary from vendor to vendor. The built-in monitoring features are not the same in terms of data formatting, protocols, systems, etc. 

A remote asset monitoring solution should consider these differences. It should be flexible, compatible, and highly scalable. The solution should have the scalability potential to keep track of a few assets from the same manufacturing vendor and scale up to hundreds of monitored assets from different vendors. 

Provide Easier Integration with Third-Party Applications 

A remote asset monitoring solution should provide seamless and effortless integration for sensors-based data and third-party generated data. A remote asset IoT-enabled monitoring solution will generally collect data using sensors or video cameras. It then uses an IoT gateway to integrate and forward collected data. Still, there are other systems, such as third-party applications like Customer Relations Management (CRMs), Enterprise Resource Planning (ERP), or Supervisory Control and Data Acquisition (SCADA) that can provide more control and richer and more valuable data. 

When integrating the sensors-based data with ERP or CRM-based data, the end-user may get richer value and more insights. In addition, integrating a ticketing system to the asset tracking solution can help improve business productivity and keep assets operational and healthy. 

Business-Specific Data Analytics and Aggregation 

A remote IoT-enabled asset monitoring system should provide a smart solution capable of adapting to current and specific business scenarios. IoT-enabled solutions collect specific data sets and perform derived analytics to help make better business-specific tailored decisions. Such a solution should help you monitor business specific or customized key performance indicators (KPIs) and metrics that ensure the operation and efficiency of your assets. In addition, aggregating data can also help reduce communication latencies and improve analysis. 

Predictive Asset Behavior and Maintenance 

An optimal remote asset monitoring solution should be capable of collecting data, transmitting it to a high-end (cloud or edge) server, and performing predictive analysis on specific asset metrics. Having a predictive maintenance schedule or plan helps organizations avoid unexpected breakdowns or failures that interrupt business productivity. 

The predictive maintenance solution provides behavioral analysis on the data and recommends equipment repairs, fixes, or part changes. Predicting assets or equipment failure and alerting you to fix it before a major downtime occurs can save you from expensive repairs and overhauls. 

Final Words

The five foundational factors for an autonomous remote asset monitoring solution presented in this post are essential. The comprehensive IoT-enabled monitoring solution for remote assets can help various vertical markets, including manufacturing, healthcare, power, utilities, oil & gas, mining, fleet, construction, industrial machinery, and more. It will not only help improve the performance and health of assets but will also enhance their productivity, efficiency, utilization, security, and even reduce operational and maintenance costs.

Maulik Upala
Maulik Upala
Maulik Upala is Product Marketing Manager at Intelligent Edge Computing business unit of Lanner Electronics Inc and is responsible for developing product positioning concepts, marketing strategies, decomposing commercial go-to-market plans and analyzing edge computing market trends.

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