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    CARAMEL: Results on a Secure Architecture for Connected and Autonomous Vehicles Detecting GPS Spoofing Attacks 

    Vitale, Christian; Piperigkos, Nikos; Christos, Laoudias; Ellinas, Georgios; Casademont, Jordi; Escrig, Josep; Kloukiniotis, Andreas; Lalos, Aris S.; Moustakas, Konstantinos; Diaz Rodriguez, Rodrigo; Baños, Daniel; Roqueta, Gemma; Kapsalas, Petros; Hofmann, Klaus-Peter; Khodashenas, Pouria Sayyad (2021-05-04)

    The main goal of the H2020-CARAMEL project is to address the cybersecurity gaps introduced by the new technological domains adopted by modern vehicles applying, among others, advanced Artificial Intelligence and Machine ...

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    Considerations, challenges and opportunities when developing data-driven models for process manufacturing systems 

    Escrig, Josep; Fischer, Oliver J.; Gomes, Rachel L.; Porcu, Laura; Watson, Nicholas (2020-09-02)

    The increasing availability of data, due to the adoption of low-cost industrial internet of things technologies, coupled with increasing processing power from cloud computing, is fuelling increase use of data-driven models ...

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    Intelligent industrial cleaning: A multi-sensor approach utilising machine learning-based regression 

    Escrig, Josep; Simeone, Alessandro; Watson, Nicholas; Wooley, E. (2020-06-29)

    Effectively cleaning equipment is essential for the safe production of food but requires a significant amount of time and resources such as water, energy, and chemicals. To optimize the cleaning of food production equipment, ...

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    Intelligent Sensors for Sustainable Food and Drink Manufacturing 

    Watson, Nicholas; Fischer, Oliver; Simeone, Alessandro; Bowler, Alexander; Escrig, Josep; Rady, Ahmed; Woolley, Elliot; Adedeji, Akinbode (2021-11-05)

    Food and drink is the largest manufacturing sector worldwide and has significant environmental impact in terms of resource use, emissions, and waste. However, food and drink manufacturers are restricted in addressing these ...

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    Monitoring the cleaning of food fouling in pipes using ultrasonic measurements and machine learning 

    Escrig, Josep; Watson, Nicholas; Wooley, E. (2020-04-25)

    Food and drink production equipment is routinely cleaned to ensure it remains hygienic and operating under optimal conditions. A limitation of existing cleaning systems is that they do not know when the fouling material ...

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    Ultrasonic Measurements and Machine Learning for Monitoring the Removal of Surface Fouling during Clean-in-Place Processes 

    Escrig, Josep; Rady, A.; Rangappa, S.; Simeone, A.; Watson, N.J.; Wolley, E. (2020-05-23)

    Cleaning is an essential operation in the food and drink manufacturing sector, although it comes with significant economic and environmental costs. Cleaning is generally performed using autonomous Clean-in-Place (CIP) ...