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Cited by 767

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Towards the Implementation of IoT for Environmental Condition Monitoring in Homes

Kelly, Sean Dieter Tebje, Suryadevara, Nagender Kumar, Mukhopadhyay, Subhas Chandra·2013·IEEE Sensors Journal

Abstract

In this paper, we have reported an effective implementation for Internet of Things used for monitoring regular domestic conditions by means of low cost ubiquitous sensing system. The description about the integrated network architecture and the interconnecting mechanisms for the reliable measurement of parameters by smart sensors and transmission of data via internet is being presented. The longitudinal learning system was able to provide a self-control mechanism for better operation of the devices in monitoring stage. The framework of the monitoring system is based on a combination of pervasive distributed sensing units, information system for data aggregation, and reasoning and context awareness. Results are encouraging as the reliability of sensing information transmission through the proposed integrated network architecture is 97%. The prototype was tested to generate real-time graphical information rather than a test bed scenario.

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Metadata

Authors
Kelly, S. D. T., Suryadevara, N. K., & Mukhopadhyay, S. C.
Venue
IEEE Sensors Journal
Published
2013-10
Volume
13
Issue
10
Pages
3846-3853
ISSN
  • 1530-437X (ISSN-L)
  • 1558-1748
  • 2379-9153
OpenAlex
W2141175342
Cited by
767
References
0
FWCI
32.55
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Towards the Implementation of IoT for Environmental Condition Monitoring in Homes. https://app.cochat.ai/papers/10.1109/jsen.2013.2263379
The paper
Kelly, S. D. T., Suryadevara, N. K., & Mukhopadhyay, S. C. (2013). Towards the Implementation of IoT for Environmental Condition Monitoring in Homes. IEEE Sensors Journal. https://doi.org/10.1109/jsen.2013.2263379

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.