H2020Индивидуална стипендия2016–2017

SmartPosition · Smartphone-based Mobile Positioning System

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2016-05-02 → 2017-11-01
Финансиране от ЕС: 127 591 €
Участници: 1
Схема: MSCA-IF-EF-ST

Линиите свързват координатора с партньорите.

Накратко на български

Системите за позициониране чрез смартфони изследват как обединените данни от различни сензори подобряват точното проследяване на потребителя в сложна среда. Това помага за създаването на по-надеждни услуги за локализация в реално време, когато стандартните филтри за обработка на данни се провалят.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Smartphone-based Mobile Positioning System

The Project is carried out under the background of worldwide diffusion and rapid escalation of smart mobile devices. With a budget of EUR 70 billion for the period 2014-2020, the H2020 programme provides opportunities for the development of applications (apps) for use with EGNSS (European Global Navigation Satellite Systems) and Galileo. Most of these applications/services are strictly related to the user’s position information, namely Localization/Positioning/Tracking (LPT) based services/applications, which have radically changed the way of life for our citizens and even have growing market prospects. In this context, reliable, high precision and real-time LPT constitutes the key research theme of the Project. Given the challenges (i.e., harsh, unknown and dynamic environments) and opportunities (highly informative sensor data), this project has targeted to two tasks: T1. develop a new concept, “Big Sensor”, as the definition of the collective employment of multi-type sensors in a single, centralized or distributed, system e.g. a smartphone; and T2. establish new LPT solutions that complements the failure of Bayesian filters for the Big Sensor system, including two paradigms: Clustering for Filtering (C4F), and Fitting for Smoothing (F4S). Based on the innovative integration of data mining (clustering and fitting) technologies with statistical signal processing, the project was carried out precisely to the scheduled objectives in our proposal, leading to three directions of the achievements of the Project: Objective O1. Theoretically analyse when and why the filters/smoother are not workable or are less favorable than the sensor data-only inference, providing systematic guidelines to distinguish them; Objective O2. Establish Big Sensor-oriented C4F and F4S algorithms and technologies, addressing their advantages and challenges regarding sensor data correlation, inconsistency, ambiguity, etc. Objective O3. Develop a smartphone-based mobile positioning application, called “SmartPosition”, with the dual intention of verifying the theoretical findings and seeking realistic application for Home Care.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

This project aims to develop two new estimation paradigms for designing a reliable, high precision and real-time mobile positioning system (MPS): clustering for filtering (C4F) and fitting for smoothing (F4S). The present MPS faces two immediate challenges from the real life world. First, little is known about the background and therefore accurate system modelling is difficult or even impossible and the use of conventional filters/smoothers is challenging or even infeasible. Secondly, the data is very rich in the sense that it comes from multiple and many types of sensors with improved scanning frequency and accuracy. The rich sensor data can be used to circumvent poor background knowledge and to provide a greater breadth of observation regardless of individual sensor failure. However, it is expected that rich data will also pose a great challenge for real time filtering implementation.This project will develop a new concept, “Big Sensor”, to flexibly utilize the rich time-varying sensor data in the concerned MPS and to implement C4F and F4S. The Big Sensor-based C4F and F4S use all available information including WIFI, Bluetooth, GPS signals as well as altitude, acceleration, and direction information based on embedded software to locate mobile devices. The resulting MPS will not rely on sophisticated filters and will therefore be more reliable and computationally faster.The research emphasis of the project will be on flexible and optimal sensor data inference which is found by developing novel clustering and fitting algorithms. The researcher and the partitioning organizations have synergic expertise and solid research track records in the related fields. Smartphone-based realistic MPS applications (apps) will be developed, with the potential use of European GNSS. The resulting MPS and its apps will be integrated into a Home Care system that the Host group has investigated for the purpose of tracking the movement and well-being of elderly/disabled people.

Оригинален текст от CORDIS (на английски).

Участници

UNIVERSIDAD DE SALAMANCA · SalamancaКоординаторИспания