- Prof. Allel Hadjali
- LIAS/ENSMA, Poitiers, France.
Website | E-mail
- Assoc. Prof. Miroslav Hudec
VSB - Technical University of Ostrava, Czech Republic.
University of Economics in Bratislava, Slovakia.
- Prof. Edy Portmann
University of Fribourg, Fribourg, Switzerland.
Website | E-mail
- Prof. Luis Martínez
University of Jaén, Jaén, Spain.
Website | E-mail
Special Issue Introduction
Internet of Things (IoT) is a paradigm that connects multiple and diverse smart objects via the Internet. Nowadays, this paradigm is receiving a momentous interest in a number of real-life fields including industry, transport, healthcare and smart cities. Interconnected smart objects will then become the major data producers and consumers instead of humans and generate huge amounts of data using their sensors every single second. Such IoT data are inherently uncertain, erroneous and noisy on the one hand, and voluminous, distributed and continuous on the other hand.
A smart environment is a connected small world in which sensor-enabled connected devices work collaboratively to make the lives comfortable, the business of enterprises much bigger and more flourishing, and so on. Additionally, it is capable of obtaining knowledge and applying it to satisfy complex users’ needs.
The recent research efforts oriented to integrate IoT with smart environments allow extending the capabilities of smart objects by enabling the user to monitor and control the environment from remote sites. It is remarkable that IoT-based smart environments have two main unique characteristics, namely, the prediction and the decision-making capabilities. Such environments can collect a variety of heterogeneous data from different sources (i.e., objects/devices) and apply data fusion and mining/learning techniques to leverage and analyse data gathered; this is the basis for developing data-driven intelligent decision support and providing new services. The problems like data disclosure, privacy, trust and explainability of mined knowledge from IoT Data should be covered for the long-term benefits of ordinary people.
Nowadays, in the context of IoT-based smart environments, data management constitutes an emergent and hot topic that faces many challenging research tasks. New solutions and revisited existing ones are proposed to address such challenging tasks. The goal of this special issue is to collect a set of high-quality papers showing the current state of the art, original and recent research for managing IoT data, especially, solutions that leverage techniques borrowed from computational intelligence field (Soft computing, Fuzzy logic, Uncertainty models, Neural networks, Evolutionary computing, …) for a more effective computing and therefore less energy demanding.
· IoT Data analytics
· IoT Data fusion / mining / integration
· Data quality, data collection and warehousing
· IoT Data cleaning / visualization
· IoT Data uncertainty management
· Knowledge discovery from IoT Data
· Linguistic summarization and interpretation
· Explainable AI for IoT Data
· Optimization based on IoT Data
· Energy and time efficient mining knowledge from IoT Data
· Trust, security and privacy managing
· IoT Data integrity and confidentiality
· Predictive and advanced machine learning models
· IoT-enabled services
· Real-time and stream processing techniques
· Real-life case studies
· Negative aspects and possible solutions
Submission Deadline31 Jan 2022