Developing a Visualisation Tool for Tour Planning

The development and applicability of a web-based time-geographic visualisation tool

Geography ◽

10.1080/00167487.2017.12094012 ◽

2017 ◽

Vol 102 (2) ◽

pp. 71-78 ◽

Cited By ~ 2

Author(s):

Minsung Kim ◽

Daeheon Cho ◽

Sang-II Lee ◽

Jungyeop Shin

Keyword(s):

Web Based ◽

Visualisation Tool

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Metro Transit-Centric Visualization for City Tour Planning

Computer Graphics Forum ◽

10.1111/cgf.12383 ◽

2014 ◽

Vol 33 (3) ◽

pp. 271-280 ◽

Cited By ~ 6

Author(s):

Pio Claudio ◽

Sung-Eui Yoon

Keyword(s):

Tour Planning

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Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks

Complexity ◽

10.1155/2021/3941074 ◽

2021 ◽

Vol 2021 ◽

pp. 1-17

Author(s):

Fan Chao ◽

Zhiqin He ◽

Renkuan Feng ◽

Xiao Wang ◽

Xiangping Chen ◽

...

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Data Gathering ◽

Base Station ◽

Sensor Nodes ◽

Wireless Sensor ◽

Cluster Center ◽

Mobile Data ◽

Tour Planning ◽

Mobile Data Gathering

Tradition wireless sensor networks (WSNs) transmit data by single or multiple hops. However, some sensor nodes (SNs) close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink (MS), which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a novel strategy is proposed to reduce the latency of mobile data gathering in a WSN while the routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle (UAV) is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed.

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Tour Planning Mechanism Using CLR Method to Achieve Reliability Control in WSN

International Journal of Science and Research (IJSR) ◽

10.21275/art20175378 ◽

2017 ◽

Vol 6 (7) ◽

pp. 666-668

Keyword(s):

Tour Planning ◽

Reliability Control

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DPUK Cohort Explorer: An Interactive Visualisation Tool

International Journal for Population Data Science ◽

10.23889/ijpds.v5i5.1432 ◽

2020 ◽

Vol 5 (5) ◽

Author(s):

Laura North

Keyword(s):

Real World ◽

Data Transfer ◽

Real World Data ◽

World Data ◽

Visualisation Tool ◽

Field Level ◽

Level Information ◽

Data Portal ◽

Portal Website ◽

Interactive Visualisation

IntroductionThe Dementias Platform UK (DPUK) Cohort Explorer is an interactive, online visualisation tool that allows users to explore data for a number of DPUK cohorts. Over 30 variables across cohorts have been harmonised, including information on demographics, lifestyle, cognition, health, and genetic biomarkers. Objectives and ApproachThe tool has been developed to complement existing DPUK cohort metadata to provide a visual representation of participant numbers and field-level information for a selection of cohorts. This enables users to determine a cohort’s eligibility before applying for access to a cohort’s data, and aid in shaping potential hypotheses. Developed using Microsoft PowerBI, the Explorer hosts a subset of the cohort’s baseline, harmonised data, allowing a user to interrogate the visualisations of the uploaded data in a secure manner on the DPUK Data Portal website. Visualisations are linked so that participant numbers and distributions can be explored interactively. ResultsThis approach allows the user to explore the harmonised data across a number of cohorts simultaneously whilst setting and adjusting filters that are of interest to the user’s search criteria. This provides a better understanding of the real-world data and enables the user to determine the feasibility of each cohort for potential studies, whilst facilitating meaningful comparisons across cohorts. The tool currently visualises five DPUK cohorts with a total of 82,391 participants, however it is being incrementally developed with more cohorts being added continually. Conclusion / ImplicationsBy combing an easy-to-use, interactive dashboard with harmonised sets of real-world data, the tool allows the user to explore, interrogate and better understand field-level information in a secure manner with zero data transfer. This provides more insight for the user when applying for access to a cohort dataset using the DPUK Data Portal and may help the user to make more informed decisions and/or hypotheses.

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