Special Session on Machine Intelligence in IoT (MIIoT)

The Internet of Things (IoT) refers to uniquely addressable objects and their virtual representations in an internet-like structure. The concepts of pervasive computing and ubiquitous computing are related to the internet of things, in the sense that all of these paradigms are enabled by large-scale embedded sensor devices. On the other hand, Machine Intelligence aims to design and develop robust automated decision making systems. Its objective is to minimize the manual interruptions and maximize the accuracy of the machine made ‘thoughts’ in a system. Since IoT can sense and communicate, they have become tools for understanding complexity, and may often enable autonomic responses to challenging scenarios without human intervention. The large number of devices simultaneously producing data in an automated way will greatly dwarf the information which individuals can enter manually. Machine Intelligence provides us the framework and tools to go beyond trivial real-time decision and automation use cases for IoT. This is a quite challenging task as the real time accurate decisions are to be made in various circumstances over similar ‘things’ may be with some different features. This session aims to introduce the machine intelligence features to solve the challenges in IoT or to enhance its performance and to have interface among academicians and industry people over the problems and feasible solutions.    

Authors should submit their papers online using EDAS. Unregistered authors should first create an account on EDAS to log on. Further guidelines for submission are posted at:http://icacci-conference.org/web/call-for-papers


Topics of interest include, but are not limited to:

  • Real-time machine learning 
  • Iterative machine learning 
  • Multi-target learning
  • Automated video surveillance and tracking
  • Generating data analysis pipelines
  • Evaluation of machine learning models tailored to sensor data
  • Data extraction from sensor networks
  • Data conversion and calibration issues
  • Meta-learning, e.g., learning to adjust the analysis pipeline automatically
  • Interpretable models, e.g., Rule Learning or Decision Tree Learning
  • Generating high-quality data sets
  • Data quality issues
  • Dealing with missing and low quality data
  • Gesture recognition
  • Object recognition
  • Feature Engineering with a focus on sensor data features
  • Generating high-quality features from sensor data
  • Application in various areas like e-health, smart city, intelligent transportation system

All papers that conform to submission guidelines will be peer reviewed and evaluated based on originality, technical and/or research content/depth, correctness, relevance to conference, contributions, and readability. The manuscripts should be submitted in PDF format. Acceptance of papers will be communicated to authors by email. At least one full paying author of each accepted paper must register for the conference before the indicated deadline. Accepted and presented papers will be published in the conference proceedings and submitted to IEEE Xplore as well as other Abstracting and Indexing (A&I) databases.

Session Organisers

Debarati Bhunia Chakraborty
Indian Statistical Institute, Kolkata, West Bengal, India
E-mail: debarati.earth@gmail.com

Suman Sankar Bhunia
Jadavpur University, Kolkata, West Bengal, India
E-mail: bhunia.suman@gmail.com

Key Dates

Paper Submission Ends:May 10, 2015
Acceptance Notification: May 31, 2015
Final Paper Deadline: June 25, 2015

Organized by

Technical Co-sponsors

IEEE Logo IEEE ComSoc   INNS India ACM Trivandrum Chapter 

ACM Trivandrum Chapter