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SmartAD

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Anomaly Detection combining time series and unstructured data using AI ML algori...

Anomaly Detection combining time series and unstructured data using AI ML algorithms in a distributed cloud edge device scenario IoT has taken the world by storm and in 2025 there will be ~75Bn connected devices, creating an amount of data never generated before. This comes with a new set of challenges, which need to be addressed with regards to IoT device... ver más

30/09/2021

QBEE AS

129K€

Presupuesto del proyecto: 129K€

Líder del proyecto

QBEE AS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-09-30

INNOSUP-02-2019-2020: European SME innovation Associate -...

I+D

Cerrada hace 6 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

1 Participantes

QBEE AS

129.11K€ | Lider

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Duración del proyecto: 12 meses Fecha Inicio: 2020-09-15
Fecha Fin: 2021-09-30

Líder del proyecto

QBEE AS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 129K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto IoT has taken the world by storm and in 2025 there will be ~75Bn connected devices, creating an amount of data never generated before. This comes with a new set of challenges, which need to be addressed with regards to IoT device management, especially in industrial settings. Currently, there are limited tools for embedded Linux IoT device management (e.g. cameras, sensors, thermostats, routers, etc), which are not able to effectively manage the devices and keep the IoT infrastructure secure. QBee offers the qbee.io platform, a unique embedded Linux automation, provisioning and security tool enabling a highly efficient IoT device management with high security focus for the overall IoT infrastructure. With the SmartAD project, QBee targets the development of an innovative module to the platform, namely an automated smart, accurate and secure anomaly detection module, which was identified as top priority to disrupt the IoT devices management tools. Intelligent algorithms can be used for detection of malfunctioning/suspicious behavior using advanced anomaly detection, fingerprinting and the awareness of configuration changes that the device should adhere to. To achieve this, time series data as well as file and configuration changes needs to be analyzed. Although, QBee has a strong team in the area of full-stack development, system administration, embedded devices (Linux), automation and cloud software scaling, which allowed to bring the product to a beta-version, it is also very small, and currently QBee does not have in-house skills for the next innovation stage, where forefront Artificial Intelligence/Machine Learning and data analytics skills are demanded. The SME Innovation Associate Programme fits the QBee plan on boosting R&D activities and the recruitment of an Innovation Associate will be critical to develop this module which will make qbee.io platform unique in terms of detection & prevention of cyberattacks on industrial IoT infrastructures.

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