Energy & Utilities / Smart Infrastructure
Supporting Sibelga’s Smart Lighting Rollout
Client: Sibelga
Sibelga is replacing the public lighting network in Brussels with connected LED luminaires. The objective is to convert almost 100,000 luminaires by 2030. The project is not only about saving energy, even if LED lighting is expected to reduce public lighting energy consumption by around 35%. It is also about making the network easier to monitor, control and operate through an IoT-based smart lighting system.
The challenge
At the start of the mission, the Smart Lighting system was already generating a lot of information, but it was not always easy to turn this data into clear operational actions. The network included thousands of connected luminaires, several controller technologies, different installation situations and many types of alarms or defects.
One of the main challenges was to improve the visibility on the real performance of the network: which assets were working correctly, which ones needed attention, which issues were isolated, and which ones were linked to a wider problem such as a circuit, cabinet, communication or installation issue.
A connected luminaire can be physically installed and switched on, but still not be fully reliable from an operational point of view if the controller is not correctly associated, if the dimming is not working, if the communication is unstable, or if the CMS data does not reflect the field reality. The challenge was therefore to make the CMS useful not only as a configuration tool, but also as a monitoring and dispatching tool for maintenance teams.
The outcome
The work helped turn the Smart Lighting IoT system into a more reliable and operational tool for network management. The CMS is now used not only to configure connected luminaires, but also to monitor network performance, detect defects, support root cause analysis and prepare maintenance interventions.
Monitoring views, dashboards, queries, automation workflows, quality-control checks and troubleshooting documentation were created or improved. These elements helped detect and qualify issues such as communication losses, dimming anomalies, faulty luminaires, installation defects and controller or cabinet-level failures.
The installation process also became more efficient. Newly installed assets can now be checked more systematically before handover, to make sure they are fully operational in the CMS and on site. This reduces the risk of adding new defects to the network and supports a faster installation rhythm.
For maintenance teams, the follow-up became clearer and more structured, with better issue classification, better preparation before field interventions and more reliable information for dispatching.
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