Traditionally, lifts in buildings operate until something goes wrong — only then is a fault reported, often requiring emergency service.

Property managers today work reactively, leading to inefficiencies, costly call-outs, and a lower level of service. 

 

“Today, you basically know the elevator is working until it suddenly isn’t. Then a fault is reported, often urgently. It’s a very reactive way of working.”

 

— Fredrik Melander, Property Manager, Heba Fastighets AB

Heba tested an IoT solution in which five elevators were equipped with wireless sensors. Using machine learning, the system creates a baseline profile for each elevator, enabling it to detect deviations and trends with high precision:

 

• measures vibrations and movements
• logs downtime
• sends data to a cloud solution
• learns the elevator’s normal behavior and identifies deviations over time

When something deviates from the norm, early warnings are generated — allowing action to be taken before faults result in operational downtime or require a service report.

The pilot project demonstrated clear and measurable benefits. Heba received early signals of deviations before operational disruptions occurred, enabling proactive measures. Troubleshooting improved through objective and historical data, resulting in a more fact-based dialogue with the elevator contractor and reduced reliance on subjective fault reports.

Building on the positive results, Heba plans to roll out the solution to approximately 110 elevators across its portfolio in 2026 and integrate elevator data with other property and operational systems to create a unified, real-time view of operations.

Through this initiative, Heba can:

 

• reduce unnecessary call-outs
• plan maintenance proactively
• increase operational stability
• improve the tenant experience

 

The entire initiative aligns with Heba’s overarching strategy to gain visibility and control over its properties through data — supporting operations, maintenance, and long-term planning.