Applin, Sally A. and Fischer, Michael D. (2017) Thing Theory: Connecting Humans to Smart Healthcare. In: Reis, Catarina I. and Maximiano, Marisa da Silva, eds. Internet of Things and Advanced Application in Healthcare. First edition. IGI-Global, Portugal, pp. 249-266. ISBN 978-1-5225-1820-4. E-ISBN 978-1-5225-1821-1. (doi:10.4018/978-1-5225-1820-4.ch009) (KAR id:63906)
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Official URL: http://dx.doi.org/10.4018/978-1-5225-1820-4.ch009 |
Abstract
Healthcare providers will enter location-aware smart environments with the expectation that their devices will integrate, their location will be incorporated, and the environment that they are within will specifically respond to their needs, as well as to the needs of their patients. Cooperation and coordination in complex environments requires people to have access to appropriate contextually sensitive information, some of which must be shared between them. To plan and design effective location-aware smart environments for healthcare, tools are required for integrating and responding to human needs and anticipating human intents and desires. A location-aware healthcare smart environment is another layer within this already highly heterogeneous system of communication. Each component in a location-aware smart environment network can generate data and send messages that must be processed, understood and responded to in some manner. In a healthcare environment, well placed software agents can help manage critical messages shared between sensors, low level software agents and the people who act on this information, improving care for patients and outcomes for providers. The authors’ propose a framework based on the agency of both humans and environmental components: Thing Theory, a logic-based agent framework that evolves discussion on how to connect humans to a healthcare environment designed to function for their benefit.
Item Type: | Book section |
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DOI/Identification number: | 10.4018/978-1-5225-1820-4.ch009 |
Uncontrolled keywords: | Healthcare, Information Technology, Internet of Things |
Divisions: | Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation |
Depositing User: | Michael Fischer |
Date Deposited: | 09 Oct 2017 11:19 UTC |
Last Modified: | 05 Nov 2024 10:59 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/63906 (The current URI for this page, for reference purposes) |
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