wia.io

IoT energy monitoring is the practice of connecting meters, building management systems (BMS) and other energy data sources to a software platform so that electricity, gas and water consumption streams continuously — typically down to one-minute data — instead of arriving as monthly manual reads. It suits portfolios that already have meters and BMS in place but no single view of how each building consumes and produces energy. The practical payoff is earlier detection of waste, ranked savings opportunities and reporting-grade data for frameworks such as CSRD, EPBD and SECR.

How the data flow works

IoT energy monitoring is best understood as three stages: ingest, intelligence, output.

1. Ingest — every source, every country

Data comes from wherever it already exists:

• IoT meters and retrofit sensors
• BMS systems
• Manual uploads and spreadsheets
• Cloud sources and utility invoices

Retrofit metering is fitted on live meters by site staff or a local electrician, with zero downtime. That matters because it means you do not have to wait for a building shutdown or a full metering replacement to start collecting data.

2. Intelligence layer — normalise and monitor

The platform unifies fragmented inputs into one view, then applies monitoring and analysis on top:

• Real-time visibility across electricity, gas and water, down to one-minute data
• Anomaly detection and KPIs
• Forecasting and capex modelling
• Solar yield and battery ROI calculations

3. Output — what your team actually uses

The intelligence layer produces the day-to-day artefacts an energy team acts on: alerts, forecasts, ranked opportunities and reports.

What it enables in practice

Once data is flowing, the outputs are concrete rather than abstract. From the platform view, these include:

The ranking is the part that changes decisions: instead of a list of alerts, you get opportunities ordered by annual value and payback, so capex can be directed where the data supports it.

Deployment: what to expect

• Sources are reused, not replaced. The platform ingests from meters, BMS, spreadsheets, cloud sources and invoices you already have.
• Retrofit is non-disruptive. Fitting happens on live meters with zero downtime, carried out by site staff or a local electrician.
• Coverage is portfolio-wide. Multi-utility monitoring spans electricity, gas and water across every building.
• Control can be included. Heating, cooling and lighting schedules are set in the dashboard and run on site through controllers you already have.

How it differs from traditional energy management software

Traditional energy management software tends to work from periodic reads and manual data entry, which limits how quickly you can see a problem and how granular the picture is. IoT energy monitoring keeps the continuous data feed as the foundation, then layers monitoring, optimisation and reporting on top. The difference shows up in three places:

1. Timeliness — anomalies and ghost loads surface as they happen, not at the next billing cycle.
2. Granularity — one-minute data makes out-of-hours waste and schedule drift visible.
3. Reporting readiness — reporting-grade data for CSRD, EPBD and SECR, pre-built certification reports, and a direct push to the ESG platform your team already uses.

Deciding whether it fits

IoT energy monitoring is a reasonable fit if you operate a portfolio with existing meters and BMS, need multi-utility visibility across countries, and have reporting obligations such as CSRD, EPBD, SECR or MEES tracking. It is less obviously a fit if you have a single small site with no reporting pressure, where the overhead of a platform may exceed the value of continuous data.

If the goal is to know where energy goes, catch waste early and direct capex with evidence, the ingest–intelligence–output model above is the mechanism to evaluate.

CSRD's ESRS E1 disclosure standard requires you to report total energy consumption broken down by source and by renewable versus non-renewable, plus energy intensity, your energy mix, and the Scope 1, 2 and 3 emissions tied to that consumption. The practical challenge is rarely the reporting template — it is producing figures that are complete, granular and traceable enough to survive limited assurance when your data sits in meters, BMS systems, invoices and spreadsheets across multiple countries. This explainer covers what the standard asks for, why data quality decides how hard your first report is, and how to build a collection process that also serves EPBD and SECR.

What CSRD actually asks for on energy

CSRD is the EU Corporate Sustainability Reporting Directive; the detailed requirements live in the European Sustainability Reporting Standards (ESRS), and energy sits in ESRS E1 (Climate change). The energy-related disclosures you need to be able to populate include:

• Total energy consumption, in MWh, split by source (electricity, gas, fuels, district heating/cooling, self-generated).
• Renewable vs non-renewable split of that consumption, and the share of renewables in your total mix.
• Energy intensity — consumption normalised against a measure of activity or output, so it can be compared over time.
• Scope 1 and Scope 2 GHG emissions derived from your direct fuel use and purchased energy, plus material Scope 3 categories where relevant to your value chain.
• Consumption and production where you generate your own energy (for example on-site solar), since self-generated and self-consumed energy is treated differently from purchased energy.

Two things follow from this. First, you need consumption data at source level, not a single blended total — a portfolio-wide kWh figure cannot be split into renewable and non-renewable or converted into Scope 1 and 2 without it. Second, you need the same underlying data to reconcile against your emissions figures, because assurance teams will test whether the energy numbers and the emissions numbers tell a consistent story.

Why granularity, completeness and audit trail decide your effort

The reporting format is the easy part. The work is in the data layer beneath it, and three properties determine whether your first CSRD cycle is a few weeks of consolidation or a year of reconstruction.

Granularity. Monthly invoice totals are enough to state an annual figure, but they cannot support intensity metrics, renewable share, or the anomaly checks that explain an unusual year. Interval or near-real-time data — Wia's platform describes monitoring electricity, gas and water "down to one-minute data" — lets you attribute consumption to the right period, site and source, and defend it.

Completeness. A portfolio report is only as good as its weakest site. Missing meters, unmetered fuels, tenanted areas where you don't control the supply, and sites in countries with different utility structures are the usual gaps. You need a documented method for estimating or excluding anything you cannot measure directly, and that method has to be consistent year to year.

Audit trail. Limited assurance means an independent party checks your figures against evidence. Every number in the report should trace back to a source record — a meter reading, a BMS export, an invoice — with a clear path from raw data to reported value. If your process is "the regional manager emailed a spreadsheet," you have no trail.

Wia's framing of the problem is useful here: it describes ingesting "every meter, every source, every country" and outputting "reporting-grade data for CSRD, EPBD and SECR." The phrase reporting-grade is the operative one — the distinction between data you can look at and data you can attest to.

Where the data comes from, and why it's fragmented

In a large portfolio, energy data arrives from at least four kinds of source, and each has different reliability characteristics:

Retrofit metering matters because most existing buildings were not built with the sub-metering CSRD reporting rewards. Wia describes fitting sensors "by site staff or a local electrician on live meters, with zero downtime" — the point being that you can add measurement to an occupied building without shutting systems down. If you are weighing whether that investment is necessary, the test is simple: can you currently split consumption by source and by renewable share for every site in scope? If not, you need either more metering or a documented estimation method.

Aligning CSRD with EPBD and SECR

The reason to build one data layer rather than three reporting processes is that the underlying energy data overlaps heavily across frameworks.

• CSRD / ESRS E1 wants consumption by source, renewable share, intensity and the associated emissions.
• EPBD (the Energy Performance of Buildings Directive) is concerned with building energy performance — consumption and characteristics at building level.
• SECR (Streamlined Energy and Carbon Reporting, UK) requires energy use and associated emissions, with an intensity ratio, for qualifying UK organisations.

The same meter and invoice data feeds all three. What differs is the boundary, the normalisation and the disclosure format. If you collect once at the most granular level your sites allow, and tag each data point with the attributes each framework needs (site, country, source, renewable flag, period), you avoid re-collecting for each report. Wia's platform positions this as a single intelligence layer with reporting outputs for CSRD, EPBD and SECR, plus a "direct push to the ESG platform your team already uses" — the practical benefit being that your ESG team's system of record receives consistent data rather than a fresh reconciliation each cycle.

Practical steps from fragmented data to a CSRD-ready report

1. Define your reporting boundary. Which entities, sites and countries are in scope for the reporting year? Write this down before collecting anything, because it determines what "complete" means.
2. Inventory every data source per site. List meters, BMS points, invoices and any manual sources. Note the granularity and the responsible person for each. This inventory becomes your completeness checklist.
3. Close the metering gaps or document the estimates. For anything you cannot measure, record the estimation method and apply it consistently. Undocumented estimates are the most common assurance finding.
4. Ingest into one layer with consistent tagging. Every record should carry site, country, energy source, renewable flag and period. This is what makes source-level splits and intensity metrics possible without manual rework.
5. Reconcile consumption against invoices and emissions. Check that your metered totals and your billed totals agree within a stated tolerance, and that your emissions figures derive from the same consumption data.
6. Produce the ESRS E1 disclosures from that layer, and reuse the same data for EPBD and SECR outputs rather than rebuilding.
7. Keep the trail. Retain source records and the transformation steps so an assurer can follow any reported figure back to evidence.

Common sticking points

• Treating the report as the project. The disclosure is the output; the data layer is the work. Teams that start with the template usually end up rebuilding.
• Assuming invoices are enough. They cover cost and total consumption but rarely give you the source split, renewable share or interval detail the standard rewards.
• Inconsistent boundaries across frameworks. If CSRD, EPBD and SECR scopes differ, document why — don't let the difference look like an error.
• No owner per data source. Fragmented data stays fragmented until someone is accountable for each feed.
• Leaving assurance to the end. Limited assurance is easier when the audit trail is a by-product of collection, not a reconstruction exercise.

If your portfolio spans multiple countries and utility structures, the deciding factor is usually whether you can get every source into one tagged, traceable layer. Where you can, CSRD reporting becomes a query against data you already trust; where you can't, it becomes a manual reconciliation you repeat every year.

Retrofit metering means adding or upgrading measurement capability on meters and systems that are already installed and live, instead of replacing the electrical infrastructure itself. It is the practical route when a building has meters but no useful data, when sub-circuits are unmetered, or when consumption needs to be visible at finer granularity than the existing setup provides. The defining constraint is that the building keeps operating: sensors and gateways go onto live meters, fitted by site staff or a local electrician, with zero downtime.

How retrofit metering differs from new-build or full meter replacement

The three approaches answer different questions, so the right choice depends on what is actually missing.

Retrofit is usually the appropriate choice when the physical infrastructure works but the information layer does not. Replacement becomes the better answer when the meter itself is the problem rather than the data path around it.

What retrofit metering captures

Retrofit deployments are not limited to electricity. The scope typically covers:

• Electricity — whole-building supply plus sub-metering of major circuits or plant
• Gas — heating and process consumption
• Water — supply and, where relevant, sub-metering
• Mixed sources — retrofit IoT, existing BMS, manual upload, cloud feeds and invoices, so legacy and mixed-vendor meters can sit in the same dataset

Granularity matters as much as coverage. Down to one-minute data is what makes anomaly detection, out-of-hours waste analysis and load profiling meaningful; coarser intervals will show totals but hide the events worth acting on.

How the installation works in practice

The sequence is deliberately lightweight:

1. Identify the meters and circuits to instrument. Existing meters, BMS points and panel locations determine what can be captured and where gateways need to sit.
2. Fit sensors and gateways on live meters. This is done by site staff or a local electrician, without taking the building offline.
3. Ingest every source into one layer. Retrofit IoT, BMS, manual upload, cloud and invoices are unified rather than left in separate systems.
4. Monitor and act. Electricity, gas and water across every building flow into one view, with anomaly detection and KPIs applied to the combined dataset.
5. Report from the same data. Reporting-grade output feeds CSRD, EPBD and SECR requirements, certification reports and the ESG platform the team already uses.

The expected result is that fragmented inputs become a single intelligence layer producing alerts, forecasts and reports — the work an energy manager would otherwise do manually.

Practical considerations before you commit

• Compatibility with existing BMS and meters. Legacy and mixed-vendor estates are the normal case, not the exception. Confirm what each system can expose before assuming full coverage.
• Sensor accuracy. Retrofit sensors measure indirectly in many cases, so accuracy depends on correct fitting and calibration. Treat readings as decision-grade only after validation against invoices or existing meters.
• Coverage gaps. Circuits that cannot be instrumented, or panels that are inaccessible, will leave holes in the picture. Map these early so they are known gaps rather than surprises.
• Data granularity versus cost. Finer intervals mean more devices and more data. Match granularity to the decisions you need to make — anomaly detection and scheduling need more resolution than annual reporting.
• Portfolio consistency. Deploying across many sites works best when the same ingestion and naming conventions apply everywhere, so sites remain comparable.

Where retrofit metering fits

Retrofit metering is the entry point for buildings that already exist and cannot be shut down. It supplies the consumption, savings-opportunity and solar-yield data that monitoring, optimisation and reporting depend on, and it does so without touching the underlying electrical infrastructure. The limits are real — accuracy, coverage and legacy integration all need managing — but for most occupied portfolios it is the only route that produces usable data without an outage.

Building energy intelligence is the layer that sits between the raw data your buildings already produce and the decisions your team has to make. It ingests every meter, BMS, spreadsheet, cloud feed and invoice across a portfolio, unifies them into one view of consumption and production, and outputs the things an energy manager actually acts on: anomalies, forecasts, ranked savings opportunities, KPIs and reporting-grade data. It is most useful when you operate many sites across multiple countries and utilities, where the problem is not a lack of data but the fact that it is fragmented across incompatible systems.

The core idea: fragmented data in, intelligence out

The Wia platform describes this as "fragmented data in, intelligence out." Every source you already have is ingested, run through a single intelligence layer, and returned as outputs your team uses daily. The value is not in collecting more data — it is in collapsing many sources into one pane so that a portfolio-level question ("where is energy being wasted right now?") has an answer.

What goes in

• IoT meters — retrofit sensors fitted to live meters by site staff or a local electrician, with zero downtime
• BMS systems — building management data pulled in rather than replaced
• Spreadsheets — manual uploads for sites or utilities without automated feeds
• Cloud sources and invoices — utility bills and cloud-connected data streams

Because ingestion is source-agnostic, you do not need to standardise hardware across a portfolio before starting. That matters for retrofit-heavy estates where buildings were built and wired at different times.

What comes out

• Anomaly detection — for example, a ghost load flagged at 02:00 running +248% against its expected band
• Forecasts — such as solar yield tracking against prediction
• Ranked savings opportunities — each with an annual euro value, payback period and confidence rating
• KPIs and real-time visibility — electricity, gas and water across every building, down to one-minute data
• Reporting-grade data — for CSRD, EPBD and SECR, plus pre-built certification reports

How the intelligence layer turns data into decisions

The distinguishing feature of building energy intelligence, as opposed to basic monitoring, is that outputs are ranked and quantified rather than just displayed. A dashboard that shows consumption tells you what happened. An intelligence layer tells you what to do first and what it is worth.

The platform's savings-opportunity view illustrates this. Opportunities are listed with the site, the annual euro value, the payback period and a confidence rating:

This format answers the capex question directly: where to deploy capital next, backed by your own data rather than a generic audit. Note that payback and confidence vary widely — a 2-month vampire-load fix and a 37-month battery project are not competing for the same budget, and the confidence rating tells you how much to trust the estimate before committing.

Key use cases

Out-of-hours waste

Consumption outside operating hours is often the largest single avoidable cost. In the platform's example, out-of-hours waste over the last 7 days totalled €186k, or 31% of total consumption, with the pattern broken down by day and hour. That granularity lets you separate a genuine 24-hour process from a schedule that was never corrected.

Ghost load

A ghost load is consumption that continues when nothing should be running. The example flags one at 02:00 on a Sunday at +248% against the expected band — the kind of event that is invisible on a monthly bill but obvious in one-minute data.

Solar yield and peak shaving

On-site generation needs to be measured against forecast, not just totalled. The example shows solar yield of 2.34 MWh, up 12% against forecast, with a peak of 412 kW at 11:30. Pairing generation data with consumption data is what makes peak-shaving and battery ROI modelling possible.

Capex prioritisation

Because opportunities are ranked by value, payback and confidence, the same dataset that runs daily operations also feeds capital planning.

Reporting: CSRD, EPBD and SECR

Building energy intelligence produces reporting-grade data for CSRD, EPBD and SECR, with pre-built certification reports and a direct push to the ESG platform your team already uses. The practical difference from assembling reports manually is that the underlying data is already unified and traceable to source meters and invoices, rather than reconstructed at reporting time. If your reporting obligations are the main driver, this is the capability to evaluate first.

How it differs from basic energy management software

Basic energy management software typically monitors consumption and raises alerts. Building energy intelligence adds three things on top:

1. Multi-source unification at portfolio scale — meters, BMS, spreadsheets, cloud and invoices across countries, not a single building or a single utility
2. Quantified, ranked outputs — savings opportunities with payback and confidence, not just charts
3. An operational workflow — alerts, audits, surveys, tasks, status and support built in, so findings turn into work rather than sitting in a report

It also extends into control: heating, cooling and lighting schedules can be set in the dashboard and run on site through the controllers you already have, which closes the loop between identifying waste and stopping it.

When this approach fits

It fits large, multi-site portfolios where data is fragmented across utilities, countries and vintages of building systems, and where the team needs both day-to-day operational visibility and defensible reporting. It is less relevant for a single building with one meter and no reporting obligation, where basic monitoring is sufficient.

Wia reports being live in 30+ countries. Pricing is not stated in the available material, so treat commercial terms as something to confirm directly rather than assume.

Energy management software for large building portfolios is a data layer that unifies every meter, BMS, invoice and IoT source across your sites into one view of how your buildings consume and produce energy. It fits portfolios that are too large or too fragmented to manage in spreadsheets — typically multi-site operators running electricity, gas and water across several countries, where the same team has to monitor consumption, find savings, schedule equipment and produce compliance reports. Wia, for example, describes itself as energy intelligence for the world's largest building portfolios, live in 30+ countries.

The core workflow: fragmented data in, intelligence out

The platform takes sources you already have — IoT meters, BMS systems, spreadsheets, cloud feeds and invoices — runs them through one intelligence layer, and outputs the alerts, forecasts and reports your team uses daily. That breaks into five jobs:

• Ingest — retrofit IoT, BMS, manual upload, cloud and invoices. Every meter, every source, every country. Fitted by site staff or a local electrician on live meters, with zero downtime.
• Monitor — electricity, gas and water across every building, down to one-minute data, with real-time visibility, anomaly detection and KPIs on one pane.
• Optimise — savings opportunities, solar yield, charging schedules, anomaly detection, forecasting, battery ROI and capex modelling.
• Manage — alerts, audits, surveys, tasks, status and support: the day-to-day workflow of running energy across a portfolio.
• Report — reporting-grade data for CSRD, EPBD and SECR, pre-built certification reports, and a direct push to the ESG platform your team already uses.

Control sits alongside these: heating, cooling and lighting schedules set in the dashboard and run on site through the controllers you already have.

What the output actually looks like

The value shows up as ranked, costed actions rather than raw charts. In Wia's own product view, a portfolio dashboard shows consumption and solar yield side by side, with a ghost load flagged at 02:00 at +248% versus the expected band. Savings opportunities are ranked by annual euro value, payback and confidence — for example:

Out-of-hours waste is quantified separately — in the example, €186k over the last 7 days, 31% of total consumption. This is the pattern to look for: not just monitoring, but a ranked answer to where to deploy capex next, backed by your own data.

How retrofit metering works without downtime

Installation is designed to avoid operational disruption. Meters are fitted on live circuits by site staff or a local electrician, with zero downtime, and data flows into the same platform as BMS points, invoices and manual uploads. That matters for portfolios where shutting down a distribution centre or cold store to install monitoring is not an option. The practical test is whether the vendor supports mixed sources from day one — retrofit IoT alongside existing BMS and utility invoices — rather than requiring a single metering standard across every site.

Evaluation criteria

Use the same dimensions to compare platforms:

• Multi-utility coverage — electricity, gas and water, not electricity alone.
• Data granularity — one-minute data is the benchmark for anomaly detection and scheduling.
• Source flexibility — IoT, BMS, spreadsheets, cloud and invoices in one layer.
• Anomaly detection — ghost loads and out-of-hours waste identified against an expected band, not just threshold alarms.
• Optimisation depth — savings opportunities, solar yield, battery ROI and capex modelling with payback and confidence attached.
• Reporting outputs — CSRD, EPBD and SECR reporting-grade data, plus a push into your existing ESG platform.
• Control integration — can schedules be set centrally and run on the controllers already on site?
• Deployment model — live-meter retrofit without downtime, and coverage across the countries you operate in.

Who it is for

Wia states the platform is built for operators and the partners that serve them. In practice that means energy managers running multi-site portfolios, facilities and operations teams who own day-to-day consumption, and the consultancies or service partners managing energy on a client's behalf. If your portfolio spans multiple countries, utilities and meter types, and you need both compliance reporting and a ranked savings pipeline from the same data, this category of software is aimed at you. If you have a single site with one utility meter, the ingestion and unification layer adds little over a basic monitoring tool.