SLICE 2019 - International Workshop on Smart Living with IoT, Cloud, and Edge Computing (SLICE 2019)

Smart health, smart cities, smart industries, smart agriculture, smart environment, smart transportation, smart homes, smart education, smart business, smart energy, smart grids, and so on are the components that aid the mankind for smart living. However they require, typically, design and development of innovative technologies, standards, and protocols apart from their architectures and frameworks. IoT has emerged as an extension to Wireless Sensor Networks (WSNs) with low-cost and Internet-enabled solution for connecting and accessible anything from anywhere. In addition, such smartness derived due to the artificial intelligence yields in production of tremendous amounts of data. The data increases as a baby-boomer requiring efficient tools to analyze and extract suitable inferences for services in order to extend smart living. Cloud, Edge and Big Data acquired enormous attention in the light of massive data storage and analytics. With the large cohorts of gazette shrewdness and hi-tech population, the infrastructure, service delivery becomes expensive and difficult to manage for cities and governments. Automating systems through utilization of IoT, Cloud, Edge, Big Data, and M2M tools and technologies demonstrate great opportunity to reduce operating costs significantly, utilize those savings more effectively, and provide better services to communities for smarter living. This workshop provides a platform to the researchers to publish their innovative ideas, extensive analysis of their comparative studies, critical review of existing research and position papers in the above areas to meet the smart living requirements. The topics of interest include but are not limited to:
Platform architectures
Data analytics
Privacy preserving data mining
Big data integrity and confidentiality
Data and knowledge as a service
Security and privacy applications
Real-time and stream processing techniques and algorithms
Real-life case studies
Proactive/predictive and advanced machine learning models
Simplified and distributed data processing techniques
Ubiquitous machine learning
Fog computing
Smart living data warehouse
Soft computing techniques
Optimization
Resource utilization and Resource Management
Security and Trust
Mobile Computing
Application Development
Wireless Sensor Networks
Mobile Data Services
High Performance Computing