Selected papers from the Workshop on Collaborative Technologies and Data Science in Smart City Applications (CODASSCA 2020)
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (15 January 2021) | Viewed by 8148
Special Issue Editors
Interests: Data Science; Learning Analytics; Collaborative Computing
Interests: Mathematical methods for computer sciences, computer graphics
Special Issues, Collections and Topics in MDPI journals
Interests: Information theory and coding, data science, machine learning
Interests: deep learning; natural language processing; graph theory
Special Issue Information
Dear Colleagues,
The 2nd Workshop on Collaborative Technologies and Data Science in Smart City Applications (CODASSCA 2020) will be held at the American University of Armenia AUA, 25–28 August 2020 in Yerevan, Armenia. The workshop aims at exchanging knowledge about Ambient Intelligence (AmI) research based on advances in sensors and sensor networks, pervasive computing, embedding computational capability into everyday objects, artificial intelligence bringing cognitive capabilities to a new generation of devices, and sensors and controllers with their interfaces in smart environments (SmE) growing in their capabilities and easing collaboration among people. The main source and asset for making smart systems is data, which our information age has made easily accessible. The next main challenge we face is to effectively and efficiently extract knowledge from huge amounts of data from heterogeneous sources to make the systems self-contained and autonomous.
Authors of selected high-qualified papers from the conference will be invited to submit extended versions of their original papers (50% extensions of the contents of the conference paper) and contributions.
Potential topics include but are not limited to the following:
- Track on collaborative technologies with applications in smart cities;
- Track on data science and information theoretic approaches for smart systems;
- Track on technical challenges for smart environments;
- Track on artificial intelligence, neural networks, and deep learning;
- Track on smart human-centered computing.
Dr. Nelson Baloian
Dr. Wolfram Luther
Dr. Ashot Harutyunyan
Dr. Tomoo Inue
Dr. Hrant Khachatrian
Guest Editors
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