Insights and news from the ATOM Mobility team

‍How to automate maintenance alerts for rental fleets

Rental fleet maintenance automation is becoming essential for operators who want to scale without increasing operational complexity. Whether you manage cars, scooters, bikes, or mixed fleets, manual inspections and spreadsheets quickly fail once your fleet grows beyond a few dozen vehicles.

Breakdowns, missed services, and delayed repairs directly affect uptime, revenue, and customer satisfaction. Modern fleet technology makes it possible to automate maintenance using IoT telematics, onboard sensors, automatic error codes, mileage-based triggers, and structured dashboards.

Why manual maintenance tracking does not scale

In small fleets, maintenance is reactive. A customer reports an issue. A staff member checks the vehicle. Someone creates a task manually. This works for 20 vehicles, but for 200 it’s just too much work.

As fleets expand, issues are discovered too late, standards vary between locations, and staff spend more time coordinating than fixing. Rental fleet maintenance automation shifts operations from reactive repairs to preventive, system-driven workflows.

Using IoT telematics to monitor vehicles in real time

IoT telematics devices collect live data such as location, battery level, ignition status, engine health, and mileage. In car rental and car sharing fleets, telematics also track fuel levels, driving behaviour, and diagnostic information.

Instead of waiting for user reports, the system can trigger alerts automatically. For example:

when a battery drops below 20 percent
when a vehicle reaches a service mileage threshold
when a vehicle leaves a defined service area
when the vehicle receives a few negative reviews

This data feeds directly into the fleet platform, where workflows assign tasks automatically, reducing response times and eliminating internal coordination delays.

Onboard sensors and automatic error codes

Modern vehicles generate diagnostic trouble codes when systems fail. In connected fleets, these codes appear instantly in the operator dashboard.

If a vehicle reports a brake or engine warning, the system can block it from new bookings, notify technicians, and create a repair task automatically. In micromobility fleets, IoT modules detect tilt events, battery degradation, failed unlock attempts, or controller errors.

Digital reporting further improves vehicle availability. ATOM Mobility’s vehicle damage management feature shows how structured workflows reduce downtime and improve transparency.

Mileage-based and time-based service automation

Rule-based servicing is one of the most effective elements of rental fleet maintenance automation.

Operators can set simple service rules, such as:

changing oil every 15,000 km
checking brakes every 20,000 km
running a safety check every six months

When a vehicle reaches one of these limits, the system creates a task automatically. The vehicle can also be temporarily removed from booking until the service is done. This becomes especially important when operating in multiple cities, because it keeps safety standards consistent across the entire fleet.

Maintenance dashboards and task automation

A maintenance dashboard centralises alerts, open issues, and upcoming service requirements.

With structured task management, teams can assign jobs, set priorities, track resolution times, and analyse recurring issues. ATOM Mobility’s Task Manager feature enables operators to convert alerts directly into trackable actions within one system. Alerts that turn into tasks automatically make it clear what needs fixing and when it should be handled.

From reactive to predictive maintenance

With enough historical data, fleets can move beyond fixed intervals. Operators can identify patterns such as faster brake wear in specific models or higher damage rates in certain areas. Predictive maintenance allows servicing based on actual usage intensity, reducing unnecessary costs while preventing major failures.

For operators growing from 50 to 500 vehicles, automation delivers clear advantages:

higher uptime, because issues are detected earlier
lower operational costs, since preventive repairs are cheaper than breakdowns
improved safety and compliance, with no missed service intervals
better customer experience, with fewer malfunctioning vehicles
clearer performance metrics for management decisions

Automation supports maintenance teams with clearer priorities and better data.

Building the right automation stack

Effective rental fleet maintenance automation typically requires:

IoT hardware
a fleet management platform with automated alerts
configurable service rules
a task dashboard
task automation logic
analytics tools

When these components are connected, maintenance becomes scalable and controlled instead of reactive. This is especially important for operators running scooter, bike, car sharing, or rental businesses, where uptime directly impacts revenue and retention.

Rental fleet maintenance automation makes maintenance more organised and easier to manage as you grow. IoT telematics, automatic diagnostics, mileage alerts, and task dashboards help create clear processes that support expansion.

For rental and shared mobility operators who want to grow steadily, automating maintenance is essential. It helps keep operations stable and supports long-term profitability.

Lime improved GPS. But parking compliance may need more than that

Lime improved GPS from 12m to ~1.5m accuracy - a big step forward for micromobility. 🚀 But parking compliance isn’t just about knowing where a vehicle is - it’s about proving it’s parked correctly. Real-world pilots (like Prague) show that physical verification (e.g. Bluetooth beacons) can significantly outperform GPS when it comes to actual compliance.

March 25, 2026

Lime just raised the bar for GPS-based parking compliance. But the bigger question is this: when cities want verified parking, is better GPS enough, or do operators need physical proof? That question matters more than ever.

Lime’s new LimeBike rollout in the UK comes with a major location upgrade. Lime says its new bikes can locate themselves to within 1.5 metres, a significant improvement from the roughly 12.3 metres typical in dense urban environments (this means that based on GPS data, a vehicle can be up to 12 meters farther or closer than the reported GPS location. Now this error is just 1.5 meters). That is real progress.

Lime’s upgrade is a meaningful step forward for GPS-based positioning. At the same time, cities are increasingly looking beyond positioning accuracy toward verifiable parking compliance.

Why this matters

Cities are becoming much less tolerant of parking disorder. In Kensington & Chelsea, the council seized 1,000 rental e-bikes by November 2025 and collected more than £81,000 in charges from operators.

That is the real backdrop for every operator today:

stricter enforcement
more political pressure
less room for ambiguity

So yes, better GPS is good news. But it does not automatically mean cities will see parking as “solved.” A vehicle may be near a bay, beside a bay, or slightly outside it. In dense urban areas, that difference matters. Traditional GPS struggles there because of building interference, blocked satellite visibility, and signal reflections.

So the strategic question is no longer:
“Can we improve GPS?”

It is:
“What kind of system gives cities enough confidence to enforce parking rules fairly and consistently?”

What the Prague pilot showed

A European Commission-backed pilot in Prague tested a different approach: Bluetooth-based parking verification.

Across 25 parking locations and 989 parking events, the results were clear:

90.6% success rate for SparkPark (Bluetooth infrastructure)
38.4% success rate for GPS/GNSS positioning
Technology readiness advanced from TRL 6 to 8/9

When the goal is verified parking inside a defined zone, infrastructure-based validation can significantly outperform vehicle-only (GPS) positioning.

GPS improvement vs physical verification

Lime’s move shows how far vehicle-side intelligence is improving. SparkPark points to a different model: verify the parking zone itself.

That distinction matters.

GPS estimates where the vehicle is
Infrastructure confirms whether it is correctly parked

Those are fundamentally different approach.

Why cities may prefer the second path

One of the key findings from the Prague pilot is not just technical - it is institutional. Cities often rely on operator-provided data to assess compliance. That creates a trust gap. What cities increasingly want:

independent verification
reliable compliance data
less reliance on operator-reported positioning

This is why the conversation is shifting from “better accuracy” → “verifiable proof.”

What this means for ATOM Mobility partners

Parking compliance is becoming more important than ever:

permit approvals
permit renewals
daily operational performance

Operators who can demonstrate verifiable compliance may have a clear advantage.

With ATOM Mobility, partners can explore:

integration-ready compliance workflows as ATOM Mobility already implemented bluetooth-based parking verification together with SparkPark
futher support for infrastructure-based validation like SparkPark
10x faster deployment without full fleet replacement

Instead of waiting for hardware cycles, operators can move faster and adapt to changing city expectations.

Lime deserves credit for pushing GPS accuracy forward. It is a meaningful step for the industry. But the Prague pilot highlights something equally important:

Micromobility parking may not be solved by better positioning alone. It may also require verification.

Not:
“Where is the vehicle likely parked?”

But:
“Can this parking event be verified with confidence?”

Final thought?

The future of parking compliance is likely evolving across two complementary paths:

Path 1: improve GPS accuracy
Path 2: implement physical verification

The first makes parking smarter. The second makes it more reliable and verifiable.

And in regulated urban mobility, confidence and trust often matter as much as precision.

Want to explore how ATOM Mobility can support stricter parking compliance workflows and how SparkPark technology works alongside the ATOM Mobility platform? Get in touch with our team to discuss integration options and city-facing parking control setups.

‍

Sources:

Lime GPS upgrade announcement:
https://www.smartcitiesworld.net/micromobility/new-lime-bike-upgrade-to-hit-uk-streets-this-month-12568

West Midlands LimeBike rollout:
https://www.wmca.org.uk/news/new-limebike-to-launch-in-west-midlands/

Kensington & Chelsea enforcement data:
https://www.rbkc.gov.uk/newsroom/1000-e-bikes-seized-borough

Prague SparkPark pilot (EIT Urban Mobility):
https://marketplace.eiturbanmobility.eu/best-practices/high-precision-parking-for-shared-micromobility-in-prague

SparkPark:
https://sparkpark.no

ATOM Connect 2026: Bringing the shared micromobility industry together

The micromobility industry doesn’t need another generic mobility conference. 🚫🎤 It needs real conversations between operators who are actually in the field. ⚙️ That’s exactly what ATOM Connect 2026 is built for. 🎯🤝

February 25, 2026

The shared mobility industry is evolving rapidly. Operators are navigating scaling challenges, regulatory complexity, hardware decisions, fleet optimization, and new integration models, all while aiming for sustainable growth.

That’s exactly why ATOM Mobility is organizing ATOM Connect 2026.

Our previous edition of ATOM Connect brought together professionals from the car sharing and rental industry for focused, high-quality discussions and networking. This year, we are narrowing the focus and dedicating the entire event to one fast-moving segment of the industry: shared micromobility.

ATOM Connect 2026 is designed specifically for operators, partners, and decision-makers working in shared micromobility. It is not a broad mobility conference or a public exhibition. It is a curated space for industry professionals to exchange practical experience, insights, and lessons learned.

On May 14th, 2026 in Riga, we will once again bring the community together, this time with a clear focus on micromobility.

What to expect

This year’s agenda will address the real operational and strategic questions shaping shared micromobility today:

Scaling fleets sustainably
Multi-vehicle operations beyond scooters
Regulatory cooperation and long-term city partnerships
Data-driven fleet optimization
MaaS integration and ecosystem collaboration
Marketing and automation for growth

As usual, we aim to host both local and international operators from smaller, fast-growing fleets to established large-scale players alongside hardware providers and ecosystem partners.

On stage, you’ll hear from leading shared mobility companies - including Segway on hardware partnerships, Umob on MaaS integration, Anadue on data-driven fleet intelligence, Elerent on multi-vehicle operational realities and more insightful discussions.

The goal is simple: meaningful discussions with people who understand the operational realities of the industry.

A curated, industry-focused event

ATOM Connect is free to attend, but participation is industry-focused (each submission is manually reviewed and verified). We are intentionally keeping the audience relevant and aligned to ensure high-quality conversations and valuable networking.

If you work in shared micromobility and would like to join the event, you can find the full agenda and register here:
👉 https://www.atommobility.com/atom-connect-2026

In the coming weeks, we will be revealing more speakers and additional agenda updates. We look forward to bringing the industry together again.

Unmet demand heatmap: Turn missed searches into measurable revenue growth

📉 Every unmet search is lost revenue. The unmet demand heatmap shows where users actively searched for vehicles but none were available - giving operators clear, search-based demand signals to rebalance fleets 🚚, improve conversions 📈, and grow smarter 🧠.

February 17, 2026

Fleet operators don’t lose revenue because of lack of demand - they lose it because demand appears in the wrong place at the wrong time. That’s exactly the problem the Unmet demand heatmap solves.

This new analytics layer from ATOM Mobility shows where users actively searched for vehicles but couldn’t find any within reach. Not guesses. Not assumptions. Real, proven demand currently left on the table.

What is the unmet demand heatmap?

The unmet demand heatmap highlights locations where:

A user opened the app
Actively searched for available vehicles
No vehicle was found within the defined search radius

In other words: high-intent users who wanted to ride, but couldn’t. Unlike generic “app open” data, unmet demand is recorded only when a real vehicle search happens, making this one of the most actionable datasets for operators.

Why unmet demand is more valuable than app opens

Many analytics tools track where users open the app (ATOM Mobility provides this data too). That’s useful - but incomplete. Unmet demand answers a much stronger question:
Where did users try to ride and failed? That difference matters.

Unmet demand data is:

✅ Intent-driven (search-based, not passive)

✅ Directly tied to lost revenue

✅ Immediately actionable for rebalancing and expansion

✅ Credible for discussions with cities and partners

How it works

Here’s how the logic is implemented under the hood:

1. Search-based trigger. Unmet demand is recorded only when a user performs a vehicle search. No search = no data point.

2. Distance threshold. If no vehicle is available within 1,000 meters, unmet demand is logged.

The radius can be customized per operator
Adaptable for dense cities vs. suburban or rural areas

3. Shared + private fleet support. The feature tracks unmet demand for:

Shared fleets
Private / restricted fleets (e.g. corporate, residential, campus)

This gives operators a full picture across all use cases.

4. GPS validation. Data is collected only when:

GPS is enabled
Location data is successfully received

This ensures accuracy and avoids noise.

Smart data optimization (no inflated demand)

To prevent multiple searches from the same user artificially inflating demand, the system applies intelligent filtering:

- After a location is stored, a 30-minute cooldown is activated
- If the same user searches again within 30 minutes And within 100 meters of the previous location → the record is skipped
- After 30 minutes, a new record is stored - even if the location is unchanged

Result: clean, realistic demand signals, not spammy heatmaps.

Why this matters for operators

📈 Increase revenue

Unmet demand shows exactly where vehicles are missing allowing you to:

Rebalance fleets faster
Expand into proven demand zones
Reduce failed searches and lost rides

🚚 Smarter rebalancing

Instead of guessing where to move vehicles, teams can prioritize:

High-intent demand hotspots
Time-based demand patterns
Areas with repeated unmet searches

🏙 Stronger city conversations

Unmet demand heatmaps are powerful evidence for:

Permit negotiations
Zone expansions
Infrastructure requests
Data-backed urban planning discussions

📊 Higher conversion rates

Placing vehicles where users actually search improves:

Search → ride conversion
User satisfaction
Retention over time

Built for real operational use

The new unmet demand heatmap is designed to work alongside other analytics layers, including:

- Popular routes heatmap
- Open app heatmap
- Start & end locations heatmap

Operators can also:

Toggle zone visibility across heatmaps
Adjust time periods (performance-optimized)
Combine insights for strategic fleet planning

From missed demand to competitive advantage

Every unmet search is a signal. Every signal is a potential ride. Every ride is revenue. With the unmet demand heatmap, operators stop guessing and start placing vehicles exactly where demand already exists.

👉 If you want to see how unmet demand can unlock growth for your fleet, book a demo with ATOM Mobility and explore how advanced heatmaps turn data into decisions.

🚀 New feature alert: Web-booker for ride-hailing and taxi operations

🚕 Web-booker is a lightweight ride-hail widget that lets users book rides directly from a website or mobile browser - no app install required. It reduces booking friction, supports hotel and partner demand, and keeps every ride fully synced with the taxi operator’s app and dashboard.

February 9, 2026