From reactive lift operations to proactive early warning – how Heba digitized its lifts
Read moreProactive maintenance in practice
From gut feeling to fact-based decisions
A major benefit is the ability to prevent unnecessary call-outs through early indications of when a lift begins to deviate from its normal behaviour.
“Right now I’ve opened and closed the doors 10 times more often on floor 2 than I usually do — maybe there’s gravel in the tracks. Come and remove it before I have a breakdown.”
Combined with planned maintenance, it also gives us a better basis for decision-making. In one of my properties, the statistics show it clearly: door B on floor 1 is used almost exclusively — having that confirmed by data gives a completely different confidence in the decisions made.
“We make sure we are always on the ‘right side’ of the problem — which in the long run both reduces wear and extends the facility’s service life.”
— Fredrik Melander, Property Manager & PropTech Coordinator, Heba Fastighets AB
Case Study · Real Estate · Sweden · Heba Fastighets AB
Connected lifts 2025
Planned installations 2026
Continuous monitoring
24/7
The Challenge
Reactive operations — waiting for things to break
Traditionally, lifts in buildings operate until something goes wrong — only then is a fault reported, often requiring emergency service. Property managers work reactively, leading to inefficiencies, costly call-outs, and a lower quality of service for tenants.
“Today, you basically know the lift 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
The Solution
IoT sensors, machine learning, and early warnings
Heba tested an IoT solution where five lifts were equipped with wireless sensors. Using machine learning, the system creates a baseline profile for each lift — enabling it to detect deviations and trends with high precision.
Vibration & movement sensing
IoT sensors measure lift movement and vibrations continuously, capturing data that reflects the mechanical health of each lift in real time.
Automated downtime logging
Every stoppage is automatically recorded and timestamped, eliminating manual reporting and creating a reliable audit trail.
Cloud data pipeline
All sensor data is securely transmitted to the cloud, enabling centralised monitoring and long-term trend analysis across the entire portfolio.
ML baseline & early warnings
The system learns each lift’s normal behaviour. When deviations emerge, early warnings are triggered — before faults cause disruptions.
Results & Business Impact
From pilot to portfolio-wide rollout
The pilot demonstrated clear, measurable benefits. Heba received early deviation signals before operational disruptions occurred — enabling proactive intervention and fact-based dialogue with the lift contractor.
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Resources
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