Evidence map›Paper›PMID 32992965›Full record

ArticleSensors (Basel, Switzerland)2020

A Network Sensor Fusion Approach for a Behaviour-Based Smart Energy Environment for Co-Making Spaces.

Teng-Wen Chang, Hsin-Yi Huang, Chung-Wen Hung, Sambit Datta, Terrance McMinn

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Teng-Wen ChangCollege of Design, National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan.ORCID 0000-0001-9503-2766
Hsin-Yi HuangCollege of Design, National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan.ORCID 0000-0002-4765-1869
Chung-Wen HungDepartment of Electrical Engineering, National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan.ORCID 0000-0002-1051-545X
Sambit DattaSchool of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Bentley, WA 6102, Australia.ORCID 0000-0002-5683-3832
Terrance McMinnShunya Pty Ltd., 44 Marcus Avenue, Booragoon, WA 6154, Australia.ORCID 0000-0003-3424-0128

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

User behaviour and choice is a significant parameter in the consumption patterns of energy in the built environment. This paper introduces a behavior-based approach for developing smart energy applications. With the rapid development of wireless sensor networks and the Internet of Things (IoT), human-computer interfaces can be created through the mapping of user experiences. These applications can provide users with dynamic feedback on their energy consumption patterns in their built environment. The paper describes a "Sensible Energy System" (SENS) that is based on user experience design methods with sensor network technology. Through SENS, solar energy simulation is combined with device consumption data in order to achieve an IoT network to facilitate the interaction between user behaviors and electricity consumption. The interaction between users and devices through SENS can not only optimize power consumption, but also provide consumers with additional choice and dynamic decision making regarding their consumption. This article provides an (1) understanding and analysis of users' spatial interaction, explains the (2) planning of the new smart environment design and user experiences, discusses (3) designing a suitable Wireless sensor network (WSN) agent and energy connection, describes (4) the information that has been collected, and (5) incorporates a rooftop solar potential simulation for predicting energy outputs into the sensor network model.

Indexed as

ambient agentsinternet of thingssmart buildingssolar energyuser behaviourwireless sensor networks

Identifiers

PMID32992965
PMCPMC7582833

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.