Internet of Things Data Analytics (IoTDA)
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: closed (15 June 2021) | Viewed by 24092
Special Issue Editors
Interests: services computing; web of things; edge computing; distributed sensing
Special Issues, Collections and Topics in MDPI journals
Interests: healthcare systems; augmented reality; big data; deep learning; internet of things; data mining
Special Issues, Collections and Topics in MDPI journals
Interests: Internet of things; data mining; cloud computing, formal verification
Special Issue Information
Dear Colleagues,
The Internet of Things (IoT) is not only about connecting billions of devices to the Internet, but also about connecting people, services, applications, businesses, and infrastructures, among many others. What makes the IoT even more interesting is how data and technology can be blended to build sustainable IoT Data Analytics (IoTDA) applications. With billions of devices embedded in environments, buildings, vehicles, or products and continuously generating huge amounts of real-time data in many different formats, building sustainable IoTDA applications is becoming more challenging. One of the main hurdles is determining a suitable environment for processing IoT data. While it is envisioned that IoT applications would typically perform data processing on the cloud, a growing number of limitations in meeting applications’ demands is prompting researchers to investigate more efficient ways for processing data near IoT devices, particularly for applications that require a low-latency response. With the growing number of IoT devices that have very limited computational abilities, the emergence of micro-clouds (or fog nodes) near data sources to create sustainable IoTDA applications makes this very timely. The IoTDA 2020 workshop provides researchers and practitioners a venue to discuss possible new methods for building sustainable IoTDA applications and develop methods and techniques to investigate existing IoTDA limitations. In this context, the workshop’s ambition is to help in shaping a community of interest on the existing research opportunities and challenges resulting from performing data analytics for IoT applications. In addition, the workshop helps in bringing researchers and practitioners together to investigate innovative ideas or approaches to this new research challenge with the main focus on developing sustainable IoTDA applications, fostering collaborations, and exchanging points of view. This Special Issue in Sensors is planned in conjunction with IoTDA 2020 (https://sites.google.com/view/iotda) and will include peer-reviewed feature papers presented at IoTDA 2020. Topics include, but are not limited to, the following:
- Distributed intelligence for IoT data analytics;
- Heterogeneous IoT data analytics for fog computing;
- Data quality metrics for IoT applications;
- Distributed data analytics in fog computing;
- Big data IoT applications (e.g., smart city, manufacturing, e-health);
- Visual analytics algorithms for IoT applications;
- Middleware for IoT applications;
- Mobility and context-awareness for IoT applications;
- Process modeling for IoT applications;
- Storage, querying, and diffusion of IoT data;
- Data compression for constrained IoT Devices;
- QoS guarantee for IoT applications;
- Privacy, security, and trust issues in IoT applications;
- Recovery schemes for IoT applications;
- Internet of Things as a service (IoTaaS);
- IoT data centers' data analytics;
- IoT management capabilities for data centers
Dr. Eyhab Al-Masri
Prof. Dr. Chi-Hua Chen
Dr. Alireza Souri
Dr. Olivera Kotevska
Guest Editors
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