IP Library Granted Patent US 12713204
Granted Patent B2
US 12713204 · App. 18/232,049 · Granted Aug 18, 2026

Digital asset location system

Inventor: David C. Loda (Oshkosh, WI)
Assignee: Oshkosh Corporation
H04W4/029H04B17/318H04W4/38
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12713204
App. No.
18/232,049
Granted
Aug 18, 2026
Kind
B2
Abstract

A system and method for ubiquitous global asset management is disclosed. This is comprised of a centralized, remotely accessible computer application displaying current, past, and predicting future geolocation of wirelessly tagged assets such as tools, components, finished goods, etc., throughout an organization's digital ecosystem. It integrates geolocation technologies to determine 3D positioning information of assets such as indoor BLE, outdoor LoRa WAN, private cellular networks and other wireless technologies. Geopositioned data is published to a centralized data pool for consumption by other applications. Usage includes indoor such as a factory or warehouse as well as outdoor supply depots, staging areas, supplier locations and enroute. The system also identifies geolocations in 3D using a smart device without tagging, such as a fixed asset location. Assets can be found using any system connected device. This provides an organization with ubiquitous tracking and asset migration patterns to optimize manufacturing and supply chain operations.

Claims (20)

1 . A system for locating an asset on a worksite, the system comprising:

a sensor network comprising a plurality of sensors, each configured to detect radio frequency signals from assets and smart devices;

a first smart device; and

at least one processor communicatively coupled to the first smart device and the sensor network and configured to:

receive, from the first smart device, a selection of a first asset;

identify a location of the first asset based on first signals emitted by the first asset;

determine the location of the first smart device based on second signals emitted by the first smart device and detected by a first subset of the plurality of sensors; and

provide, to the first smart device, directions from the first smart device to the first asset.

2 . The system of claim 1 , wherein identifying the location of the first asset based on first signals emitted by the first asset comprises determining the location by detecting the first signals by a second subset of the plurality of sensors.

3 . The system of claim 2 , further comprising a radio frequency tracking tag coupled to the first asset, wherein the first signals emitted by the first asset are emitted by the radio frequency tracking tag.

4 . The system of claim 2 , wherein the first signals detected by the second subset of the plurality of sensors each comprise a received signal strength indicator (RSSI) and wherein determining the location of the first asset comprises performing a geometrical calculation based on a location of each of the second subset of the plurality of sensors and the RSSI detected by each of the second subset of the plurality of sensors.

5 . The system of claim 1 , wherein the second signals detected by the first subset of the plurality of sensors each comprise a received signal strength indicator (RSSI) and wherein determining the location of the first smart device comprises performing a geometrical calculation based on a location of each of the first subset of the plurality of sensors and the RSSI detected by each of the first subset of the plurality of sensors.

6 . The system of claim 2 , wherein the at least one processor is further configured to:

monitor the location of the first asset over a first time period;

train a machine-learning model based in part on the monitored location;

predict a most efficient route from the first smart device to the first asset based on the machine-learning model; and

determine the directions from the first smart device to the first asset based on the predicted most efficient route.

7 . The system of claim 6 , further comprising a camera configured to photograph the worksite, wherein the at least one processor is configured to determine the directions from the first smart device to the first asset based in part on analyzing a photograph from the camera.

8 . The system of claim 1 , wherein providing the directions from the first smart device to the first asset comprises generating a graphical user interface (GUI) and providing the GUI to the first smart device.

9 . The system of claim 8 , wherein the GUI comprises a map of the worksite including an indicator of the location of the first asset and an indicator of the location of the first smart device.