Filter lifecycle management driven by real data

Replace filters when they actually need it — not on arbitrary schedules. Real-time DeltaP monitoring extends filter life by 40% and eliminates unplanned replacements.

Data-driven lifecycle

Every filter has a unique story

Calendar schedules treat every filter the same way. In reality, loading speed depends on the environment, occupancy, season and upstream filter condition. TERA 360 tracks each filter bank's actual loading curve to trigger replacement at the right time — neither too early nor too late.

The result: filters used to their true end of life, energy consumption under control, and maintenance that anticipates instead of reacting.

+40 %

Filter lifespan

15 %

Energy savings

Unplanned replacements

Return on investment

The challenge

Fixed schedules waste money — or risk contamination

Replace too early, waste money

Calendar-based filter replacement ignores actual loading conditions. Filters operating in clean environments or low-occupancy periods may have months of useful life remaining when they are discarded. In a typical hospital or pharmaceutical facility, this means tens of thousands of euros in unnecessary filter costs annually.

Replace too late, risk failure

Conversely, filters in high-dust environments or during construction periods can overload between scheduled checks. A saturated HEPA filter means loss of containment, increased fan energy, potential bypass leakage, and in critical environments, production shutdown or compliance breach.

Energy impact is invisible

A loaded filter increases pressure drop across the air handling unit. Fans work harder, consuming more energy — but this gradual increase is invisible without continuous DeltaP monitoring. The energy penalty from deferred filter replacement often exceeds the filter cost itself.

No lifecycle visibility

Maintenance teams lack filter loading curves. They cannot predict when a filter will reach its terminal pressure drop, cannot plan procurement, and cannot coordinate replacements across multiple AHUs to minimize disruption. Every replacement is either premature or reactive.

How TERA 360 works

From pressure data to predictive scheduling

TERA 360 transforms raw DeltaP readings into actionable maintenance intelligence.

Continuous DeltaP tracking

Differential pressure transmitters installed across each filter stage — pre-filter, fine filter, HEPA — feed real-time readings into the platform. Data is logged at sub-minute intervals and correlated with airflow volume.

Loading curve modeling

The platform builds a loading curve for each filter bank based on historical DeltaP progression. Machine learning models account for seasonal variations, occupancy patterns and upstream filter condition to predict remaining useful life.

Predictive scheduling

Replacement recommendations are generated weeks in advance, grouped by AHU and building zone. Maintenance planners receive procurement lead times, estimated labor windows, and energy savings projections for each replacement event.

Sensors & systems

Instrumentation for filter intelligence

DeltaP transmitters

High-accuracy differential pressure sensors across each filter stage. Ranges from 0-250 Pa (pre-filters) to 0-1000 Pa (HEPA). 4-20 mA or Modbus output.

Airflow sensors

Duct-mounted airflow measurement for volume normalization. DeltaP alone is insufficient — the same pressure drop at different airflow rates indicates different loading states.

Energy meters

AHU fan power monitoring to quantify the energy impact of filter loading. Real-time correlation between DeltaP increase and kWh consumption enables cost-based replacement decisions.

BMS integration

Modbus or API integration with existing building management systems. TERA 360 reads fan status, damper positions and VFD frequencies to contextualize filter performance data.

Dashboards & alerts

Maintenance intelligence at every level

TERA 360 dashboard — HVAC filtration overview

Your entire filter fleet on a single screen

Filter fleet overview — All filter banks with color-coded health status: green (healthy), yellow (approaching replacement), red (replace now). Remaining life estimate in days, projected replacement date, and cost-to-delay metrics.
Loading curve visualization — Per-filter-bank DeltaP trends with projected trajectory. Comparison with manufacturer terminal pressure drop limits. Historical curves from previous filter sets for benchmarking. Anomaly detection flags unusual loading patterns.
Energy impact dashboard — Real-time display of energy penalty from filter loading. "What-if" scenarios showing savings from replacing specific filter banks today versus waiting. Annual energy cost attribution per AHU for budgeting.
Maintenance planning — Upcoming replacement schedule with grouping recommendations. Procurement list auto-generated with filter specs, quantities and lead times. Integration with CMMS systems for automatic work order creation.

Benefits

Filters last longer, cost less, and perform better

+40 %

Filter lifespan — By replacing based on actual loading instead of calendar schedules, filters are used to their true end of life. No more discarding filters with months of remaining capacity.

15 %

Energy savings — Timely replacement eliminates the energy penalty of overloaded filters. Optimized replacement timing keeps average DeltaP lower, reducing fan power consumption across the filter lifecycle.

Zero unplanned replacements

Predictive scheduling ensures filters are replaced before failure. No more emergency shutdowns, no bypass events, no compliance breaches from unexpected filter saturation.

3x ROI

Combined savings from extended filter life, reduced energy consumption, eliminated emergency replacements, and lower maintenance labor. Typical return on investment within the first year of operation.

40%

Extended filter life

15%

Energy savings

Unplanned replacements

ROI

Ready to optimize your filtration lifecycle?

We'll audit your filter fleet, instrument the critical banks, and build your predictive maintenance baseline.

Discuss your project