Egain is a Swedish technology company that links intelligent software, big data, and human expertise to provide self-optimized and energy-efficient buildings. Thanks to applying AI-based self-learning cloud services that visualize and optimize energy usage, they reduce CO2 emission and heating costs in 7 European markets.
When we were approached by the client, they were looking for front-end developers to join their internal team and help them develop the platform visualizing the buildings’ energy consumption at a detailed level. In the first phase of the project, the main focus was to build a Proof of Concept. After that, we were working on several modules, implementing the designs provided by the client, testing the application, and helping to maintain it.
At different stages of the project, we’ve been working on different modules of the platform, including dashboards, admin panel, and resource databases.
After every major release, we have been following different testing scenarios in various environments to make sure that everything works smoothly for the end-users.
In the meantime, we were supporting the client’s team, working on some features in other modules, or fixing bugs.
Even though the end-customers of the product are the buildings’ administrators, they are not the only users of the product. The ones who are responsible for energy consumption monitoring, optimize it, and take care of the maintenance are the experts who are often located far away from the building. The challenge was to gather information from different sensors and collectors on one dashboard and let the experts monitor and manage them remotely.
How to convince the users that the product they are paying for is actually worth it? In order to show them the value they get, we needed to create a module that would display historical data and the forecasts, and that would be customizable for the users to compare the metrics of their choice.
When we joined the project, it was already present in different markets including Sweden, Denmark, Finland, Germany, Poland, France, and Switzerland. The platform was supposed to be supported by experts from different countries and needed to support 7 languages.
When we joined the Egain team, they already had a team of developers and needed to scale that team up with additional support on the frontend. We’ve been cooperating working on the UI, while the Egain internal team took care of the backend.
The dashboard that we created working with the Egain’s internal team combined data from different collectors and then specific sensors. Using that data, the experts are able to monitor the temperature, air humidity, and other parameters, along with additional information such as connection strength or time of the last meter-reading. The dashboard allows them also to manage sensors manually – update their software, turn them off and on – and optimize the work of different sensors within the specific collector.
In order to show the end-users a real value of implementing the product, we added an admin panel which helps the administrators of the buildings monitor the energy consumption and calculate the ROI. They can also set their goals and monitor the progress towards these goals.
The product contains the Resource manager which is a database of all the resources and documentation available in different languages. It makes it easy for the users to see all the files, check whether nothing is missing, make sure that the nomenclature is consistent across the whole platform, and add translation if necessary.
To facilitate the cooperation between the energy experts and the administrators of different buildings, we created an admin’s view that allows experts to see all properties that they are responsible for and monitor them on a high level.
In order to make sure that every release goes smoothly, we were testing different environments following the prepared testing scenarios and cases. Additionally, we were performing general smoke tests once a week.
With the dashboard, users who have different roles (experts, building administrators) are able to monitor energy consumption across different buildings, using multiple sensors that can be managed and optimized remotely to ensure the highest efficiency.
With the reports generated in the panel, the administrators of the buildings can easily calculate the profitability of the investment measured with the metric of their choice. They can calculate how long it will take to see the return of investment, how much savings it will generate over time, calculate the lifetime value of the investment (considering the lifespan of different elements that may require to be replaced after some time, inflation, maintenance costs, etc.).
Additionally, they can see the summary of all the investments with diagrams showing their impact on energy consumption along with the forecasts for future energy consumption.
As all the information coming from different sensors and collectors is presented on one dashboard, the energy experts are able to optimize energy consumption by adjusting their settings (remotely!), detect problems at a very early stage, and get them fixed.
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