scholarly journals Unsupervised Hierarchical Clustering Approach for Tourism Market Segmentation Based on Crowdsourced Mobile Phone Data

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2972 ◽  
Author(s):  
Jorge Rodríguez ◽  
Ivana Semanjski ◽  
Sidharta Gautama ◽  
Nico Van de Weghe ◽  
Daniel Ochoa
Keyword(s):  
Hierarchical Clustering ◽  
Market Segmentation ◽  
Wearable Sensors ◽  
Essential Element ◽  
Cost Effective ◽  
Mobile Phone Data ◽  
Mobility Data ◽  
Tourism Management ◽  
Clustering Approach ◽  
Spatio Temporal

Understanding tourism related behavior and traveling patterns is an essential element of transportation system planning and tourism management at tourism destinations. Traditionally, tourism market segmentation is conducted to recognize tourist’s profiles for which personalized services can be provided. Today, the availability of wearable sensors, such as smartphones, holds the potential to tackle data collection problems of paper-based surveys and deliver relevant mobility data in a timely and cost-effective way. In this paper, we develop and implement a hierarchical clustering approach for smartphone geo-localized data to detect meaningful tourism related market segments. For these segments, we provide detailed insights into their characteristics and related mobility behavior. The applicability of the proposed approach is demonstrated on a use case in the Province of Zeeland in the Netherlands. We collected data from 1505 users during five months using the Zeeland app. The proposed approach resulted in two major clusters and four sub-clusters which we were able to interpret based on their spatio-temporal patterns and the recurrence of their visiting patterns to the region.

scholarly journals Wearable Sensors for Human Environmental Exposure in Urban Settings

2021 ◽  
Author(s):  
Carolin Helbig ◽  
Maximilian Ueberham ◽  
Anna Maria Becker ◽  
Heike Marquart ◽  
Uwe Schlink
Keyword(s):  
Acoustic Noise ◽  
Wearable Sensors ◽  
Environmental Parameters ◽  
Urban Structure ◽  
Protective Behavior ◽  
Urban Settings ◽  
Current Trends ◽  
Spatio Temporal ◽  
Smart Technologies ◽  
Study Designs

AbstractGlobal population growth, urbanization, and climate change worsen the immediate environment of many individuals. Elevated concentrations of air pollutants, higher levels of acoustic noise, and more heat days, as well as increasingly complex mixtures of pollutants pose health risks for urban inhabitants. There is a growing awareness of the need to record personal environmental conditions (“the human exposome”) and to study options and implications of adaptive and protective behavior of individuals. The vast progress in smart technologies created wearable sensors that record environmental as well as spatio-temporal data while accompanying a person. Wearable sensing has two aspects: firstly, the exposure of an individual is recorded, and secondly, individuals act as explorers of the urban area. A literature review was undertaken using scientific literature databases with the objective to illustrate the state-of-the-art of person-based environmental sensing in urban settings. We give an overview of the study designs, highlight and compare limitations as well as results, and present the results of a keyword analysis. We identify current trends in the field, suggest possible future advancements, and lay out take-home messages for the readers. There is a trend towards studies that involve various environmental parameters and it is becoming increasingly important to identify and quantify the influence of various conditions (e.g., weather, urban structure, travel mode) on people’s exposure.

scholarly journals EZ-SEP: Extended Z-SEP Routing Protocol with Hierarchical Clustering Approach for Wireless Heterogeneous Sensor Network

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1021
Author(s):  
Zhanserik Nurlan ◽  
Tamara Zhukabayeva ◽  
Mohamed Othman
Keyword(s):  
Sensor Network ◽  
Hierarchical Clustering ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Cluster Head ◽  
Average Power ◽  
Base Station ◽  
Average Power Consumption ◽  
Clustering Approach ◽  
Heterogeneous Sensor Network

Wireless sensor networks (WSN) are networks of thousands of nodes installed in a defined physical environment to sense and monitor its state condition. The viability of such a network is directly dependent and limited by the power of batteries supplying the nodes of these networks, which represents a disadvantage of such a network. To improve and extend the life of WSNs, scientists around the world regularly develop various routing protocols that minimize and optimize the energy consumption of sensor network nodes. This article, introduces a new heterogeneous-aware routing protocol well known as Extended Z-SEP Routing Protocol with Hierarchical Clustering Approach for Wireless Heterogeneous Sensor Network or EZ-SEP, where the connection of nodes to a base station (BS) is done via a hybrid method, i.e., a certain amount of nodes communicate with the base station directly, while the remaining ones form a cluster to transfer data. Parameters of the field are unknown, and the field is partitioned into zones depending on the node energy. We reviewed the Z-SEP protocol concerning the election of the cluster head (CH) and its communication with BS and presented a novel extended mechanism for the selection of the CH based on remaining residual energy. In addition, EZ-SEP is weighted up using various estimation schemes such as base station repositioning, altering the field density, and variable nodes energy for comparison with the previous parent algorithm. EZ-SEP was executed and compared to routing protocols such as Z-SEP, SEP, and LEACH. The proposed algorithm performed using the MATLAB R2016b simulator. Simulation results show that our proposed extended version performs better than Z-SEP in the stability period due to an increase in the number of active nodes by 48%, in efficiency of network by the high packet delivery coefficient by 16% and optimizes the average power consumption compared to by 34.

scholarly journals A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data

2020 ◽  
Vol 236 ◽  
pp. 111493 ◽  
Author(s):  
Joshua Lizundia-Loiola ◽  
Gonzalo Otón ◽  
Rubén Ramo ◽  
Emilio Chuvieco
Keyword(s):  
Burned Area ◽  
Modis Data ◽  
Active Fire ◽  
Burned Area Mapping ◽  
Clustering Approach ◽  
Spatio Temporal

scholarly journals Modelling of Bi-Directional Spatio-Temporal Dependence and Users’ Dynamic Preferences for Missing POI Check-In Identification

2019 ◽  
Vol 33 ◽  
pp. 5458-5465 ◽  
Author(s):  
Dongbo Xi ◽  
Fuzhen Zhuang ◽  
Yanchi Liu ◽  
Jingjing Gu ◽  
Hui Xiong ◽  
...  
Keyword(s):  
Large Scale ◽  
Real Life ◽  
Location Prediction ◽  
Temporal Dependence ◽  
Great Opportunity ◽  
Mobility Data ◽  
Proposed Model ◽  
Poi Recommendation ◽  
Spatio Temporal ◽  
Dynamic Preferences

Human mobility data accumulated from Point-of-Interest (POI) check-ins provides great opportunity for user behavior understanding. However, data quality issues (e.g., geolocation information missing, unreal check-ins, data sparsity) in real-life mobility data limit the effectiveness of existing POIoriented studies, e.g., POI recommendation and location prediction, when applied to real applications. To this end, in this paper, we develop a model, named Bi-STDDP, which can integrate bi-directional spatio-temporal dependence and users’ dynamic preferences, to identify the missing POI check-in where a user has visited at a specific time. Specifically, we first utilize bi-directional global spatial and local temporal information of POIs to capture the complex dependence relationships. Then, target temporal pattern in combination with user and POI information are fed into a multi-layer network to capture users’ dynamic preferences. Moreover, the dynamic preferences are transformed into the same space as the dependence relationships to form the final model. Finally, the proposed model is evaluated on three large-scale real-world datasets and the results demonstrate significant improvements of our model compared with state-of-the-art methods. Also, it is worth noting that the proposed model can be naturally extended to address POI recommendation and location prediction tasks with competitive performances.

scholarly journals Experimental Characterization of Inkjet-Printed Stretchable Circuits for Wearable Sensor Applications

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3476 ◽  
Author(s):  
Jumana Abu-Khalaf ◽  
Razan Saraireh ◽  
Saleh Eisa ◽  
Ala’aldeen Al-Halhouli
Keyword(s):  
Wearable Sensors ◽  
Cost Effective ◽  
Experimental Characterization ◽  
Wearable Sensor ◽  
Successful Development ◽  
Sensor Applications ◽  
Cost Effective Method ◽  
Stretchable Circuits ◽  
Nanoparticle Ink

This paper introduces a cost-effective method for the fabrication of stretchable circuits on polydimethylsiloxane (PDMS) using inkjet printing of silver nanoparticle ink. The fabrication method, presented here, allows for the development of fully stretchable and wearable sensors. Inkjet-printed sinusoidal and horseshoe patterns are experimentally characterized in terms of the effect of their geometry on stretchability, while maintaining adequate electrical conductivity. The optimal fabricated circuit, with a horseshoe pattern at an angle of 45°, is capable of undergoing an axial stretch up to a strain of 25% with a resistance under 800 Ω. The conductivity of the circuit is fully reversible once it is returned to its pre-stretching state. The circuit could also undergo up to 3000 stretching cycles without exhibiting a significant change in its conductivity. In addition, the successful development of a novel inkjet-printed fully stretchable and wearable version of the conventional pulse oximeter is demonstrated. Finally, the resulting sensor is evaluated in comparison to its commercially available counterpart.

scholarly journals Investigating the practical viability of walk-sharing in improving pedestrian safety

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Debjit Bhowmick ◽  
Stephan Winter ◽  
Mark Stevenson ◽  
Peter Vortisch
Keyword(s):  
Public Perception ◽  
Performance Metrics ◽  
Social Preferences ◽  
Cost Effective ◽  
Pedestrian Safety ◽  
Web Based ◽  
Proactive Approach ◽  
Community Acceptance ◽  
Urban Scenario ◽  
Spatio Temporal

AbstractWalk-sharing is a cost-effective and proactive approach that promises to improve pedestrian safety and has been shown to be technically (theoretically) viable. Yet, the practical viability of walk-sharing is largely dependent on community acceptance, which has not, until now, been explored. Gaining useful insights on the community’s spatio-temporal and social preferences in regard to walk-sharing will ensure the establishment of practical viability of walk-sharing in a real-world urban scenario. We aim to derive practical viability using defined performance metrics (waiting time, detour distance, walk-alone distance and matching rate) and by investigating the effectiveness of walk-sharing in terms of its major objective of improving pedestrian safety and safety perception. We make use of the results from a web-based survey on the public perception on our proposed walk-sharing scheme. Findings are fed into an existing agent-based walk-sharing model to investigate the performance of walk-sharing and deduce its practical viability in urban scenarios.

Sign in / Sign up

Export Citation Format

Share Document