What is he best known for?
The fields of study he is best known for:
- Operating system
- The Internet
- Computer network
Mobile computing, Data stream mining, Context awareness, Wireless sensor network and World Wide Web are his primary areas of study.
He combines subjects such as Data stream and Information retrieval with his study of Data stream mining.
The various areas that he examines in his Context awareness study include Qualitative reasoning, Context model, Ubiquitous computing, Human–computer interaction and Sensor fusion.
The Wireless sensor network study combines topics in areas such as Cloud computing, Middleware and Data science.
His Middleware research incorporates elements of Market research and Relation.
His studies in World Wide Web integrate themes in fields like Ontology and Intelligent agent.
His most cited work include:
- Context Aware Computing for The Internet of Things: A Survey (1728 citations)
- Mining data streams: a review (804 citations)
- Sensing as a service model for smart cities supported by Internet of Things (625 citations)
What are the main themes of his work throughout his whole career to date?
Arkady Zaslavsky mostly deals with Distributed computing, Mobile computing, World Wide Web, Computer network and Context awareness.
His Distributed computing research incorporates themes from Scalability, Multi-agent system and Software agent.
His study focuses on the intersection of Mobile computing and fields such as Mobile device with connections in the field of Data stream mining, Data mining and Android.
His World Wide Web course of study focuses on Mobile agent and Computer security.
His study on Computer network also encompasses disciplines like
- Wireless ad hoc network that intertwine with fields like Mobile ad hoc network,
- The Internet that connect with fields like Cloud computing.
His study looks at the intersection of Context awareness and topics like Ubiquitous computing with Adaptation.
He most often published in these fields:
- Distributed computing (19.01%)
- Mobile computing (16.74%)
- World Wide Web (14.88%)
What were the highlights of his more recent work (between 2014-2020)?
- Smart city (6.61%)
- Context awareness (13.84%)
- World Wide Web (14.88%)
In recent papers he was focusing on the following fields of study:
Arkady Zaslavsky spends much of his time researching Smart city, Context awareness, World Wide Web, Waste collection and Waste management.
His Smart city study combines topics in areas such as Intelligent transportation system, Real-time computing, Context management, Cyber-physical system and Big data.
His Context awareness research includes elements of Ontology, Context model, Software deployment and Mobile device.
His Context model study which covers Query language that intersects with Data science.
His work deals with themes such as Decision support system and Focus, which intersect with Waste management.
His Interoperability study also includes fields such as
- Data discovery and Access control most often made with reference to Database,
- Wireless sensor network most often made with reference to Cloud computing.
Between 2014 and 2020, his most popular works were:
- OpenIoT: Open Source Internet-of-Things in the Cloud (157 citations)
- Internet of Things Platform for Smart Farming: Experiences and Lessons Learnt. (127 citations)
- Challenges and Opportunities of Waste Management in IoT-Enabled Smart Cities: A Survey (92 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- The Internet
- Computer network
His primary areas of investigation include Smart city, Decision support system, Waste management, Waste collection and Service.
In his study, Cost efficiency, Data stream mining and Incentive is strongly linked to Transport engineering, which falls under the umbrella field of Smart city.
He has included themes like Multimedia, The Internet and Big data in his Data stream mining study.
His Service study integrates concerns from other disciplines, such as Scalability, Middleware and Interoperability.
His study in World Wide Web is interdisciplinary in nature, drawing from both User interface and Database.
His research in Field intersects with topics in Quality, Wireless sensor network and Data science.
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