.IML 2017 : .International Conference on Internet of Things and Machine Learning
Call For Papers
Call for: Abstract, Full Paper, Poster Paper or Short paper.
International Conference on Internet of Things and Machine Learning (IML 2017)
Venue: Liverpool John Moores University, United Kingdom
Proceedings: ACM Digital Library/ ISBN: 978-1-4503-5243-7
The International Conference on Internet of Things and Machine Learning (IML 2017) will be held from October 17 - 18, 2017 in Liverpool John Moores University, Liverpool city, United Kingdom.
We invite you to submit your paper (Abstract, Full Paper, Poster Paper or Short paper) to IML conference.
Aim and Scope of the conference: http://iml-conference.org/
Important Dates: June, 15 2017.
Submission web-page: http://iml-conference.org/paper-submission/
All accepted and registered papers ((Abstract, Full Paper, Poster Paper or Short paper)) for IML 2017 conference will be published by ACM Digital Library. Under the ISBN: 978-1-4503-5243-7. ACM send all published materials to DBLP, Scopus and Thomson Reuters for indexing in their products.
Extended version of best papers:
Journal: European Journal of Operational Research Editorial Board (Indexed by Thomson Reuters)
Journal: Decision Sciences (Indexed by Thomson Reuters)
Keynote Speaker: Yacine Atif, University of Skövde, Sweden
Internet of Things:
Understanding Networks and Networking protocols
Sensors and hardware programming
Smart Cities (Smart parking, Smartphone detection, Traffic congestion, Smart lighting, etc.).
Smart Water (Potable water monitoring, Chemical leakage detection in rivers, River floods, etc.).
Security & Emergencies
Retail (Supply chain control, Intelligent shopping applications, Smart product management, etc.).
Logistics (Quality of shipment conditions, Item location, etc.).
Industrial Control (M2M Applications, Indoor air quality, Temperature monitoring, etc.).
Smart Agriculture (Green houses)
Digital Health-care / Telehealth / Telemedicine
IP multimedia subsystems
Data Engineering (capture, storage, search, sharing, modeling)
Advanced Data Computing
Data Interpretation and Analysis
Big Data Challenges
Support Vector Machines
Signal and Image Processing
Applications of Machine Learning