Friday, June 09, 2023
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ENORASI project

Workshop #1

The 1st Workshop of the ENORASI project was combined with the International Workshop on Pervasive Intelligence (PEINT) , as part of the 2019 EANN (international Conference on Engineering Applications of Neural Networks). It was hosted at the Knossos Royal Beach Resort in Crete (Greece) on the 24-26th of May 2019, which was co-organized with the University of Thessaly. Results from ENORASI project have been presented as representative part of the pervasive (ubiquitous) computing research area, that embeds computational power (i.e., using microprocessors) into daily life objects, in an effort to make them capable to communicate and perform tasks without the need of intense interaction with users. The concept of pervasive computing has recently emerged; a large number of applications such as wearable devices, smart/assistive homes and environments, smart cities, self driving cars etc. are already part of everyday life. Pervasive computing devices are constantly available and networked, often interconnected with cloud services.

Among the plethora of domains of application, several user groups such are people with disabilities or elderly persons may benefit the most. Disabled people may use smart devices so that difficulties within their daily life due their disabilities are surpassed. Moreover elderly people may live into smart environments so that their activities of daily living may be monitored and they may be assisted to continue their lives independently, with minimal human intervention.

This workshop focused on methods and applications for data analysis in smart environments, enabled by artificial intelligence, including (but not limited to) neural networks. It encourages the submission of papers addressing concepts and methods related to the processing and analysis of data from multiple sensor modalities, especially high throughput audio and video. Novel methods and algorithms in this context should cope with specific challenges and open research issues. Experiments on publicly available datasets are also encouraged to demonstrate the effectiveness of these methods. Application papers should stress the societal impact of the proposed approach.

The program of the event can be found at