H2020Индивидуална стипендия2017–2019

ProbSenS · Probabilistic neuromorphic architecture for real-time Sensor fusion applied to Smart, water quality monitoring systems

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

Период: 2017-09-01 → 2019-08-31
Финансиране от ЕС: 175 420 €
Участници: 1
Схема: MSCA-IF-EF-ST

Линиите свързват координатора с партньорите.

Накратко на български

Нова компютърна архитектура, вдъхновена от биологичните системи, обединява данни от множество микросензори за проследяване на замърсителите във водата в реално време. Това позволява по-бърз и енергоефективен анализ на място, вместо скъпи и бавни лабораторни изследвания.

Този кратък обзор е генериран от изкуствен интелект

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

Резултати накратко

Probabilistic neuromorphic architecture for real-time Sensor fusion applied to Smart, water quality monitoring systems

The ProbSenS project aimed to develop a novel low-power event-driven probabilistic Very Large-Scale Integration (VLSI) architecture for real-time, adaptive and robust multisensor integration. Current commercial instrumentation is only able to analyze a small fraction of the markers targeted in everyday applications, and is generally bulky, monoparametric, and requires periodical calibration in front of environmental changes and sensor non-idealities. Most analyses are still performed in laboratories, resulting in increased costs, hindered logistics, and delayed detection. By using principles of how biological systems rapidly combine multisensory information and generate meaningful features in dynamic and uncontrolled real-world conditions, the neuromorphic networks designed in the project are connected to a set of Si-based microsensors to fuse multivariate data in situ for a true EU societal challenge: the real-time monitoring of water pollutants. The resulting system is targeted to be faster, smaller, energy efficient, and highly resilient to noise, nonlinearities, matrix effects, and drifts associated with the sensors.

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

Цел на проекта

“ProbSenS” will develop a novel low-power event-driven probabilistic Very Large-Scale Integration (VLSI) architecture for real-time, adaptive and robust multisensor integration. Multisensor integration exploits the extended coverage of multiple detectors to increase perceptual confidence in Smart Systems, but embedded implementations are yet in their infancy due to the lack of hardware able to infer from the multivariate, nonlinear, time-dependent and noisy signals supplied by modern sensors. By using principles of how biological systems promptly combine multisensory information and generate meaningful features in dynamic and uncontrolled real-world conditions, bioinspired Generative Deep Neural Network (GDNN) models are emerging as a powerful, CMOS-amenable computing paradigm to accelerate sensor fusion and enable quick, reliable self-learning and context-awareness under these constraints.This project aims to develop such technology into a smaller, smarter, calibration-free multisensor solution, tolerant to sensor drifts and suited to process low-latency data from a varied set of solid-state transducers in critical real-world monitoring/diagnosis scenarios where information is acquired on-line and mostly unlabelled, e.g. security, health and environmental care. ”ProbSenS” will broaden state-of-the-art insight in the following multidisciplinary areas: (i) The modelling of GDNNs as probabilistic processors for adaptive event-based sensor fusion in Smart Systems; (ii) the investigation of novel ultra-low-power VLSI circuits to realise their computational units in low-cost CMOS technologies; (iii) the yet unexplored event-driven fusion of electrochemical and optical microsensors using a GDNN; and (iv) the benchmark of this technology in a true EU societal challenge: the real-time monitoring of water pollutants. The final outcome will be a functional working prototype of the GDNN validated in the field together with Agbar, the largest water management company in Spain.

Оригинален текст от CORDIS (на английски).

Участници

UNIVERSITAT ZURICH · ZurichКоординаторШвейцария