Infrared (IR) scanning has long been a cornerstone of preventive maintenance, allowing facilities to detect early signs of failure in electrical and mechanical systems. While traditional IR scanning methods have been effective, they have been plagued by labor-intensive processes and significant reporting delays. Now, AI-powered thermography is revolutionizing the field, turning what once took weeks into a matter of minutes.
Case Study: 4-year comparisons
From 2022 to 2024, the facility maintenance teams relied on traditional IR cameras, scanning 550 to 900 devices in a 10-day period. The process required two technicians, a trained IR thermographer, and a qualified electrician to inspect and document findings manually.
However, the real challenge arose after the scanning was complete. The massive backlog of images needed to be sorted, analyzed, and compiled into reports. An office personnel member dedicated several weeks to organizing images, identifying problem areas, and generating reports. On average, it took 30 minutes to complete the report for each flagged device. With specialists earning an average of $100-$250 per hour, the cost of reporting for just 200 devices could reach $75-$200 per device. More critically, this delay in reporting meant increased risk to the facility until information could be used to identify where corrective actions were needed.
A New Era of Efficiency
The breakthrough came in 2025 with the introduction of the FotricAI infrared camera and its integration with REALTIMEais.com. This advanced setup redefined IR scanning by eliminating manual inefficiencies and drastically improving response times.
This innovation’s core is the REALTIMEais.com “API” (Application Programming Interface), which enables the automatic generation of reports, auto-naming, and filing of all images. The new workflow is remarkably streamlined:
- Each device’s scan is uploaded to REALTIMEais.com with a bulk loading interface that can be done in just a few minutes.
- Reports are automatically generated and categorized into the appropriate REALTIMEais.com device “shell,” eliminating the need to sort and file images manually.
- Clients receive instant access to critical information, including NETA priority levels and alert reports.
“REALTIME” Insights, “REALTIME” Action
With instant access to data, maintenance teams can proactively address potential issues before they escalate.
The new REALTIMEais.com API provides:
- Automated NETA Delta T analysis, prioritizing devices that require immediate attention.
- Seamless integration with the REALTIMEais.com EMP Optimizer, ensuring NFPA 70B compliance and automatic task scheduling updates.
- A dashboard that provides a clear overview of issues, scans completed, and outstanding maintenance actions.
Instead of manually reviewing reports, maintenance managers can now access real-time alerts and analytics to prioritize tasks efficiently.
Quantifiable Cost and Time Savings
| Metric | Traditional (2022-2024) | Advanced (2025) |
|---|---|---|
| Devices Scanned | 550 – 900 in 10 days | 1,100 in <2 weeks |
| Time per Device | 30 min reporting (only on issues) | <2 min reporting (for every device) |
| Total Reporting Time | Avg. 30 days post-scan | Same-day reporting |
| Reporting Labor Cost | Added costs for reporting and image sorting | Eliminated manual reporting cost |
| Client Response Time | Delayed (30+ days) | Immediate action |
The transition to “AI”-powered thermography has led to substantial savings:
- The elimination of the device reporting cost on over 200 flagged devices.
- A drastic reduction in post-scan processing time from weeks to minutes.
- Early problem detection to prevent costly failures and reduce energy waste.
- Enhanced safety by mitigating electrical fire risks.
- Improved regulatory compliance by ensuring real-time NFPA 70B adherence.
The Future of Facility Maintenance is Here
Integrating thermography technology with FOTRIC and automation platforms like REALTIMEais.com redefines predictive maintenance. The industry is shifting from reactive maintenance to a proactive, data-driven approach by reducing manual labor, cutting costs, and enabling real-time decision-making.
With AI-driven tools, maintenance teams can work smarter, not harder—ushering in a future where facility upkeep is intelligent, connected, and predictive.
