Accuracy floors set by BLE versus UWB

RTLS cost starts with the positioning technology itself. Accuracy depends on the technology and deployment. UWB can offer sub-meter accuracy (<30 cm), while BLE typically provides 1-3 meter accuracy. Battery life follows the same split: BLE tags can last from 1-3 years, while UWB tags may need charging every few months.

That difference decides what you can reliably see. A 1-3 m BLE reading is enough to cut random walking when a forklift or pallet is “somewhere in this bay.” Sub-meter UWB becomes useful when you need to confirm a vehicle is inside a tight safety zone or parked exactly at a pick face. Wi-Fi-based systems sit in the middle for many halls but still require the same density decisions; the platform treats them as one more modality alongside BLE, UWB, RFID and SLAM localization.

Higher precision does not automatically mean more value. It means more anchors, more frequent updates, and shorter battery cycles. Match the technology to the decision you need to make, not to a marketing accuracy number.

Tag and anchor density as the real spend lever

Once the technology is chosen, the next cost driver is how many tags and fixed anchors you place. Every additional data point on the floor adds hardware, mounting time and ongoing licence units. Sparse coverage works for zone-level asset search: you learn the forklift is in the north aisle and stop the five-minute hunt. Dense coverage is required for dwell and utilization visibility—knowing whether a vehicle spent twenty minutes idle at a blocked dock or simply waited for the next pull order.

In a 30,000 sqm automotive Tier-2 plant the RTLS investment was €81,000. The same size plant in another case spent €120,000. The difference is not magic; it tracks the number of tracked vehicles and the density needed to keep live 3D positions trustworthy across the whole floor. A lighter 15,000 sqm logistic-center deployment used only €3,500 and still delivered usable real-time visibility across an L-shaped layout.

Density therefore trades directly against the benefit you want. Low density shortens search time. High density unlocks utilization numbers and the ability to see repeated dwell patterns that waste shifts.

Utilization visibility that cut fleet size

Live positions turn into utilization data only when the coverage is dense enough to rebuild routes and idle time. In the first 30,000 sqm Tier-2 RTLS case, productivity across 15 forklifts moved from 63 % to 75 %, the fleet dropped from 15 to 13 units, and four FTEs were no longer needed. First-year OPEX saved reached €179,000 against the €81,000 outlay.

A second plant of the same size started with 36 forklifts and 108 drivers. After RTLS the fleet fell to 20 vehicles (−44 %) and drivers to 60 (−44 %). The investment was €120,000; first-year OPEX saved was €960,000. Both results came from the same underlying capability: continuous location data that made idle driving and unbalanced workloads visible instead of guessed.

These numbers stay case-specific. They show what denser, higher-accuracy tracking unlocked when the plant already had enough traffic to repay the denser installation.

Safety incidents avoided through speed and location control

Safety is the third measurable outcome. In a 55,000 sqm white-goods plant the RTLS layer cost €50,000. Average forklift speed fell from 15 km/h to 6 km/h (−60 %) while performance held. The audit trail stayed available for every movement. The plant treated the safety improvement as the primary return; no further euro figure was attached.

Position data alone does not stop a collision. It does let supervisors set zone rules, review near-miss patterns and keep vehicles below speeds that turn a corner into an incident. When the technology choice and density already support reliable location, that safety layer arrives with almost no extra hardware.

Choose BLE or UWB (or Wi-Fi) for the accuracy floor you need, then set density for the specific decision—search time, utilization numbers or speed control—that the plant will act on. The measured cases show the range of outlays and the concrete operational results that followed.