scholarly journals An upcycled IoT

2021 ◽  
Vol 27 (4) ◽  
pp. 19-25
Author(s):  
Kristin Williams ◽  
Jessica Hammer ◽  
Scott E. Hudson
Keyword(s):  
Context Aware ◽  
End User ◽  
Everyday Objects ◽  
Context Aware Computing ◽  
End User Programming

An upcycled approach uses everyday objects as design material for IoT systems by enabling users to make their "dumb" objects "smart." Adopting this approach, IoT Codex realizes a new socially informed, context-aware computing and end-user programming.

Towards Dynamic Checklists

2021 ◽  
Vol 28 (2) ◽  
pp. 1-33
Author(s):  
Leah Kulp ◽  
Aleksandra Sarcevic ◽  
Megan Cheng ◽  
Randall S. Burd
Keyword(s):  
Medical Setting ◽  
Context Aware ◽  
Team Leaders ◽  
Penetrating Injuries ◽  
Context Aware Computing ◽  
In The Wild

The goal of this in-the-wild study was to understand how different patient, provider, and environment contexts affected the use of a tablet-based checklist in a dynamic medical setting. Fifteen team leaders used the digital checklist in 187 actual trauma resuscitations. The measures of checklist interactions included the number of unchecked items and the number of notes written on the checklist. Of the 10 contexts we studied, team leaders’ arrival after the patient and patients with penetrating injuries were both associated with more unchecked items. We also found that the care of patients with external injuries contributed to more notes written on the checklist. Finally, our results showed that more experienced leaders took significantly more notes overall and more numerical notes than less experienced leaders. We conclude by discussing design implications and steps that can be achieved with context-aware computing towards adaptive checklists that meet the needs of dynamic use contexts.

Efficient Ontology Integration Model for Better Inference in Context Aware Computing

2011 ◽  
Vol 268-270 ◽  
pp. 841-846
Author(s):  
Soo Mi Yang
Keyword(s):  
Video Data ◽  
Smart Devices ◽  
Collaborative Network ◽  
Context Aware ◽  
Integration Model ◽  
Smart Cameras ◽  
Ontology Integration ◽  
Context Aware Computing ◽  
Heterogeneous Devices ◽  
Distributed Ontology

In this paper, we describe efficient ontology integration model for better context inference based on distributed ontology framework. Context aware computing with inference based on ontology is widely used in distributed surveillance environment. In such a distributed surveillance environment, surveillance devices such as smart cameras may carry heterogeneous video data with different transmission ranges, latency, and formats. However even smart devices, they generally have small memory and power which can manage only part of ontology data. In our efficient ontology integration model, each of agents built in such devices get services not only from a region server, but also peer servers. For such a collaborative network, an effective cache framework that can handle heterogeneous devices is required for the efficient ontology integration. In this paper, we propose a efficient ontology integration model which is adaptive to the actual device demands and that of its neighbors. Our scheme shows the efficiency of model resulted in better context inference.

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