The Internet of Things (IoT) is not only about connecting billions of devices to the Internet, but also about connecting people, services, applications, businesses, infrastructures, among many others. What makes the IoT even more interesting is how data and technology can be blended together to build sustainable IoT Data Analytics (IoTDA) applications. With billions of devices embedded in environments, buildings, vehicles, or products 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 low-latency response.
With the growing number of IoT devices that have very limited computational abilities, the emergence micro-clouds (or fog nodes) near data sources to create sustainable IoTDA applications makes this very timely. This workshop will provide 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 will help in bringing researchers and practitioners together to investigate innovative ideas or approaches to this new research challenge with main focus on developing sustainable IoTDA applications, foster collaborations and exchange points of view.
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, etc.)
Visual Analytics Algorithms for IoT Applications
Middleware for IoT Applications
Mobility and Context-Awareness for IoT Applications
Process Modelling 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
Oct 30, 2020: Due date for full workshop paper submissions (7:00PM AoE, 3:00AM EST, 12:00PM PST)
Nov 15, 2020: Notification of paper acceptance to authors
Nov 20, 2020: Camera-ready of accepted papers (firm date)
Dec 12, 2020: Workshop Day (virtual)
Saturday – December 12, 2020 - virtual (All times are Eastern Time) - Please use this time zone converter to know exact time in your location.
10:00 am – 10:10 am Opening Remarks and Welcome
10:15 am – 10:30 am (S28201) Pedestrian Trajectory Prediction Using Pre-trained Machine Learning Model for Human-Following Mobile Robot
Rina Akabane and Yuka Kato
10:35 am – 10:50 am (S28204) Elucidating the Extent by Which Population Staying Patterns Help Improve Electricity Load Demand Predictions
Guillaume Habault, Shinya Wada, Rui Kimura, and Chihiro Ono
10:55 am – 11:10 am (S28212) Failure Prediction in Datacenters Using Unsupervised Multimodal Anomaly Detection
Minglu Zhao, Reo Furuhata, Mulya Agung, Hiroyuki Takizawa, and Tomoya Soma
11:15 am – 11:30 am (S28217) Understanding Bit-Error Trade-off of Transform-based Lossy Compression on Electrocardiogram Signals
Aekyeung Moon, Seung Woo Son, Jiuk Jung, and Yun Jeong Song
11:35 am – 11:50 am (BigD748) Automatic Device Identification and Anomaly Detection with Machine Learning Techniques in Smart Factories
Chin-Wei Tien, Tse-Yung Huang, Ping Chun Chen, and Jenq-Haur Wang
12:00 pm – 1:00 pm Break
1:00 pm – 1:15 pm (S28205) Towards AIOps in Edge Computing Environments
Soeren Becker, Florian Schmidt, Anton Gulenko, Alexander Acker, and Odej Kao
1:20 pm – 1:35 pm (S28208) Synchronized Preprocessing of Sensor Data
Amal Tawakuli, Daniel Kaiser, and Thomas Engel
1:40 pm – 1:55 pm (S28214) A Scalable and Dependable Data Analytics Platform for Water Infrastructure Monitoring
Felix Lorenz, Morgan Geldenhuys, Harald Sommer, Frauke Jakobs, Carsten Lüring, Volker Skwarek, Ilja Behnke, and Lauritz Thamsen
2:00 pm – 2:15 pm (S28206) Anomaly and Degradation Detection Using Subspace Tracking in Streaming Data
Kyungduck Cha, Carol Sadek, and Zohreh Asgharzadeh
2:20 pm – 2:35 pm (S28215) Real-Time Machine Learning for Air Quality and Environmental Noise Detection
Sayed Khushal Shah, Zeenat Tariq, Jeehwan Lee, and Yugyung Lee
2:40 pm – 2:55 pm (S28209) A Reference Model for IoT Embodied Agents Controlled by Neural Networks
Nathalia Nascimento, Paulo Alencar, Donald Cowan, and Carlos Lucena
2:55 pm – 3:15 pm Break
3:20 pm – 3:35 pm (S28218) Automatic Multimodal Heart Disease Classification using Phonocardiogram Signal
Zeenat Tariq, Sayed Khushal Shah, and Yugyung Lee
3:40 pm – 3:55 pm (S28220) Large-scale Data Integration for Facilities Analytics: Challenges and Opportunities
Balaje T. Thumati, Halasya Siva Subramania, Rajeev Shastri, Karthik Kalyana Kumar, Nicole Hessner,
Vincent Villa, Aaron Page, and David Followell
4:00 pm – 4:15 pm (S28202) Towards Policy-aware Edge Computing Architectures
Pratik Baniya, Gaurav Bajaj, Jerry Lee, Clifton Francis, Ardeshir Bastani, and Mahima Agumbe Suresh
4:20 pm – 4:35 pm (S28216) Enhancing Resource Provisioning Across Edge-based Environments
Eyhab Al-Masri and James Olmsted
4:40 pm – 4:45 pm Closing Remarks
Chair:
Eyhab Al-Masri (University of Washington Tacoma, USA)
Chi-Hua Chen (Fuzhou University, China)
Program Committee Members:
Vikas Agarwal (IBM Research)
Reem Alotaibi (King Abdulaziz University)
Christian Beecks (University of Muenster)
Subarna Chatterjee (Harvard University)
Mingzhe Chen (Princeton University)
Francesco Colace (University of Salerno)
Sergey Kanzhelev (Google)
Amit A. Nanavati (IBM Research)
Paolo Nesi (University of Florence)
Karan Raj (Amazon)
Rabie Ramadan (University of Hail)
Lauritz Thamsen (Technische Universitat Berlin)
We welcome contributions describing original ideas, experiments and applications relevant to the workshop theme which have not been published earlier or are not currently pending submission at any other venue. All submitted papers must include the names and affiliations of all authors. Submitted papers will be peer-reviewed by members of the Workshop Program Committee. All accepted papers will be included in the main conference proceedings (see Proceedings section below).
Submission Categories:
Long Papers: 6 pages (research at a mature stage)
Short/Work-in-Progress Papers: 4 pages (early or intermediate stage)
Paper Submission Link:
Templates:
https://www.ieee.org/conferences/publishing/templates.html
Camera Ready Instructions:
https://wi-lab.com/cyberchair/2020/bigdata20/scripts/BigData_2020_Camera_ready_instruction.php?subarea=S
Proceedings:
All papers accepted will be included in the IEEE Big Data Conference Proceedings published by the IEEE Computer Society Press. At least one author of each accepted paper must register for the conference and present the paper at the workshop for the paper to be included in the conference proceedings. Details on the registration will be posted on the main conference's page.
Excellent papers selected from IoTDA 2020 Workshop will be recommended to be published in an upcoming MDPI Sensors Journal (impact factor 3.275) Special Issue "Internet of Things Data Analytics (IoTDA)" (deadline: February 28, 2021).