AIOT Intelligent Internet of Things and applications

Artificial Intelligence & Internet of Things (IoT) are the latest trending technology making society-changing in many fields especially in industries like Manufacturing, Automation, Healthcare, Energy, Transport, Defence, Space, Data Mining, Elder Care etc. AI & IoT, are opening a wide set of new opportunities, both for novel services/applications and increased efficiency/scalability. These opportunities include locally sharing information, collaborating, generating/consuming a huge amount of data and learning from a massive amount of data in real time to quickly identify newly emerging unknown patterns. Indeed, distributed big data analytics, modern Machine Learning (ML) technology, Artificial Intelligence (AI), real-time data collection and processing, scalable and distributed security solutions such as blockchain, and distributed secure data processing, may play a significant role.
However, successful decision-making needs to combine the best qualities of both human and digital knowledge. To do so, it is capital to structure any type of relevant and reliable knowledge and incorporate it as part of decision analytics Indeed, there is an increasing recognition of utilizing knowledge whenever available or can be created purposefully. This includes contextual and organizational information that analytics by itself does not provide.

This Special Issue aims to demonstrate the indispensable role of business data and methodological know-how in helping decision-making and how to use and exploit the prior knowledge to enhance data analytic for autonomous decision-making. We hence encourage original paper submissions, which have not been published or submitted for publication elsewhere, from both academia and industry presenting novel research addressing the aforementioned challenges. We are seeking both conceptual and empirical papers offering new insights and contribution to the development of data analytic algorithms and systems for autonomous decision-making, which focus on the following topics (but are not limited to) which demonstrate the role of exploiting the knowledge to enhance data analytics:

Enhancing the capability in handling uncertainty
Enhancing transparency, interpretability and explainability
Reducing the complexity of model architecture in time and space
Enhancing the capability to avoid social discrimination and unfair treatment
Enhancing automated decision making capability and performance
Enhancing reliability and integrity of data analytics

Submission Guidelines

Submissions should conform strictly to the Instructions for Authors available on the conference website
Submissions should be in English with the following page length (pages of around 400 words each):
- Full papers (12-16 pages including references)
- Short papers (6-8 pages including references)
Submissions should be either in PDF or in MS-Word, formatted in the style of the Springer Publications format for Communications in Computer and Information Science (CCIS). For details on the CCIS style, see https://www.springer.com/gp/authors-editors/conference-proceedings/conference-proceedings-guidelines
Submissions should be submitted through the Editorial Management system available at: Easychair

For any queries related to this special session, you can contact session chairs.