Some tasks are not particularly difficult.
They simply have to be repeated every single month.
OMS24 Zrt. had previously installed submeters for several clients located across different parts of Hungary. As part of the service, these clients received monthly reports based on their 15-minute interval consumption data.
Initially, this process was handled manually.
For each meter, the process involved:
downloading the data;
converting it;
checking and formatting it;
preparing the monthly spreadsheet;
and sending the report to the client.
The entire process took approximately 2.5–3 hours every month.
Not because the task itself was technically difficult, but because it consisted of many repetitive manual steps.
That led to a simple question:
if the same process has to be repeated every month, why should it still be done manually?
Automating the work that does not need to be done by hand
OMS24 Zrt. developed a dedicated metering data collection application.
Every 15 minutes, the system automatically retrieves the current meter readings from the connected devices.
It then calculates interval consumption from the meter readings and stores the resulting data in a database.
By the end of the month, the required data is already available.
The system generates the monthly report, ready for delivery to the client.
A large part of the previous manual workflow therefore disappeared completely.
The challenge was not collecting data – it was dealing with different meters
The sites were not equipped with one standard meter type.
Different manufacturers and meter models had been installed over the years, and the method of retrieving data varied between them.
One of the first challenges was therefore to determine the correct communication and data-reading method for each meter type and ensure that the required information entered the database consistently.
To solve this, we created individual reading templates for the different meter types.
Through a simple configuration interface, each template can be assigned to:
a client;
a metering point;
a meter type;
and the relevant network connection details.
This makes it possible to add further metering points without having to develop a completely new data collection process every time.
Once data collection is automated, you also need to know whether it is working.
Automatic collection is only useful if the system can tell us when something goes wrong.
If a meter stops communicating, we do not want to discover it at the end of the month.
For this reason, we developed a status interface that shows:
which meters are online;
which metering points are providing data correctly;
and where intervention may be required.
The data can be used for more than monthly reporting.
Because the measurement data is stored in a database, it is not limited to the monthly reporting process.
The reporting interface allows users to retrieve historical measurement data for any required period.
This is useful when analysing a particular operating period or when historical data is needed to investigate a question that arises later.
Reporting can also be automated.
The information required for email reporting can also be configured within the system.
This means that monthly report preparation and delivery no longer need to be handled as separate manual processes.
From 2.5–3 hours to around 5 minutes
The most immediate result of the development was the reduction in administrative workload.
A process that previously required 2.5–3 hours of manual data handling and report preparation each month was reduced to approximately 5 minutes.
Automation also significantly reduced the risk of errors caused by manual copying, conversion and data processing.
The system was not developed because the original task was impossible.
It was developed because a repetitive task should not have to be performed manually every month.
Who can benefit from this type of system?
Businesses operating large numbers of submeters
The solution can be particularly useful where many metering points need to be read and processed regularly.
Typical examples include:
industrial parks;
shopping centres;
multi-site businesses;
leased commercial properties;
large industrial or commercial facilities.
At many sites, tenant submeters are still read manually, recorded on site and later transferred into spreadsheets.
Automated data collection can eliminate much of this work.
Businesses that want to understand, not just record, their energy consumption
Data collection can also serve a much broader purpose than administrative reporting.
If energy efficiency is a genuine objective, the first step is to understand:
when energy is being consumed;
which areas or equipment are using it;
how demand changes over time;
and whether there are operating patterns that require further investigation.
That requires measurement data.
Data collection no longer has to be expensive.
The price-to-performance ratio of metering equipment has improved significantly in recent years, and there are now several practical options for data communication.
As a result, the data collection layer itself can often be implemented at relatively modest cost.
The architecture can also be adapted to the client’s technical and IT environment.
Data collection may operate:
entirely within the client’s own network;
on a physically or logically separated infrastructure;
or through a combination of the two.
The appropriate solution depends on the objective, the existing infrastructure, IT and security requirements, and the available budget.
This is only the starting point.
The system described here was deliberately designed for a relatively simple purpose:
collect data, store it, make it retrievable and generate reports.
The same data collection foundation can support much more advanced functionality, including:
graphical consumption dashboards;
energy KPIs;
automatic alerts;
detection of unusual consumption patterns;
cost allocation;
comparison of multiple sites;
and continuous energy monitoring.
So the first question should not be:
What software do we need?
It should be:
What do we want the measurement data to tell us?