What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- The Internet
The scientist’s investigation covers issues in Artificial intelligence, Home automation, Activity recognition, Human–computer interaction and Context.
The study incorporates disciplines such as Smart environment, Machine learning, Systems architecture and Pattern recognition in addition to Artificial intelligence.
He has researched Home automation in several fields, including Computer security, XML, Health professionals and Quality of life.
Many of his studies on Activity recognition involve topics that are commonly interrelated, such as Data science.
His biological study spans a wide range of topics, including Self-management, Decision support system, Physical medicine and rehabilitation and Activities of daily living.
The various areas that Chris D. Nugent examines in his Context study include Ubiquitous computing, Artificial neural network and World Wide Web.
His most cited work include:
- Sensor-Based Activity Recognition (625 citations)
- A Knowledge-Driven Approach to Activity Recognition in Smart Homes (421 citations)
- Optimal Placement of Accelerometers for the Detection of Everyday Activities (229 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Activity recognition, Human–computer interaction, Machine learning and Home automation.
He interconnects Computer vision and Pattern recognition in the investigation of issues within Artificial intelligence.
His Activity recognition research incorporates themes from Smart environment, Data mining, Data science, Sensor fusion and Process.
His Human–computer interaction research incorporates elements of Context, Multimedia, Cognition and Activities of daily living.
His Context study often links to related topics such as Knowledge management.
He most often published in these fields:
- Artificial intelligence (21.84%)
- Activity recognition (17.82%)
- Human–computer interaction (14.22%)
What were the highlights of his more recent work (between 2017-2021)?
- Activity recognition (17.82%)
- Artificial intelligence (21.84%)
- Machine learning (10.78%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Activity recognition, Artificial intelligence, Machine learning, Classifier and Pattern recognition.
His research in Activity recognition intersects with topics in Context, Wearable technology, Wearable computer, Activities of daily living and Sensor fusion.
His research links Smart environment with Artificial intelligence.
His Smart environment course of study focuses on Home automation and Decision tree and Cognition.
His Machine learning research includes themes of Ontology and Identification.
His Classifier research includes elements of Data modeling, Dementia and Personalization.
Between 2017 and 2021, his most popular works were:
- 5G Communication: An Overview of Vehicle-to-Everything, Drones, and Healthcare Use-Cases (59 citations)
- Ethical adoption: A new imperative in the development of technology for dementia. (27 citations)
- Technology and Dementia: The Future is Now. (25 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- The Internet
Chris D. Nugent spends much of his time researching Artificial intelligence, Activity recognition, Pattern recognition, Classifier and Machine learning.
His study looks at the relationship between Artificial intelligence and topics such as Wearable technology, which overlap with Feature selection and Data-driven.
His Activity recognition research is multidisciplinary, incorporating perspectives in Ubiquitous computing, Home automation, Wearable computer, Data quality and Data science.
His work in Home automation tackles topics such as Usability which are related to areas like Process and Data collection.
Chris D. Nugent has included themes like Random forest and Imbalance problems in his Pattern recognition study.
His Machine learning study integrates concerns from other disciplines, such as Smart environment, Context, Activities of daily living, Popularity and Brain activity and meditation.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
