OpenHPS - An Open Source Hybrid Positioning System

OpenHPS is an open source hybrid positioning system to help developers fuse various positioning technologies and algorithms. The system offers a modular data processing framework with each modules ranging from computer vision to common algorithms such as fingerprinting or data persistence of sampled data.

The framework is maintained and used by the Web and Information Systems Engineering Lab at the Vrije Universiteit Brussel. Read more...

Quick Start

If you have npm installed, start using @openhps/core with the following commands.

bash
$ npm install @openhps/core --save

Then you can start by importing the model builder to create your first positioning model.

ts
import { ModelBuilder } from '@openhps/core';
ModelBuilder.create()
    .from(/* ... */)
    .via(/* ... */)
    .to(/* ... */)
    .build();

Latest News

OpenHPS v0.4 - Sensors, Web source nodes, RDF and more ... Sunday, 26 Feb 2023 We have released OpenHPS v0.4 which adds new Web source nodes, better use of sensors and improved mapping to semantic linked data.
FOSDEM 2022: Rapid Prototyping of a Positioning System Using the OpenHPS Framework Sunday, 06 Feb 2022 OpenHPS was presented at FOSDEM 2022 where we focussed on the open source collaboration oppertunities and presented the framework from a more technical point of view.
IPIN 2021: Indoor Positioning Using the OpenHPS Framework Wednesday, 01 Dec 2021 Our framework was presented on the 11th International Conference on Indoor Positioning and Indoor Navigation (IPIN). In this paper we demonstrate the use of OpenHPS with an indoor positioning use case along with new modules aimed for indoor scenarios.

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