bCheck focuses on improving boiler performance, mainly for property managers. Their mission focuses on predicting breakdowns and minimising maintenance and replacement costs. By developing sophisticated sensor devices that are connected to boilers, bCheck collects comprehensive data on parameters such as temperature, throughput and vibration. That data forms the basis for their machine learning models, which help predict upcoming boiler failures.
Together with competence centre InfoFarm, a partner with expertise in artificial intelligence and machine learning, bCheck has taken a crucial step in realising their goals. However, predicting boiler failures required historical data that was initially unavailable. To overcome this obstacle, they turned to real-time data analysis, detecting anomalies and changes in sensor behaviour. That approach enables bCheck to identify potential problems early and automatically send alerts to maintenance staff.
In addition to their predictive technologies, bCheck offers an interactive monitoring tool that uses advanced Changepoint Detection algorithms. This tool identifies anomalies in sensor behaviour, allowing proactive maintenance measures to be taken before problems escalate. The result does not only extend the lifetime of the boiler, but also improves planning and efficiency in maintenance activities.
Xploration
bCheck focuses on improving boiler performance. Their mission focuses on predicting breakdowns and minimising maintenance and replacement costs. Together with competence centre Infofarm, bCheck has taken a crucial step towards achieving their goals.
Our solution
Real-time data analysis, where they can detect anomalies and changes in sensor behaviour.
Result
bCheck enables property managers to optimise energy consumption, protect households from unexpected boiler failure during winter, all while minimising costs through smart predictive technologies and advanced monitoring solutions.
