Smartphone-based data collection from wireless sensor networks in an urban environment

Can, Zuhal; Demirbaş, Murat

doi:10.1016/j.jnca.2015.08.013

Cited by 25 publications

(10 citation statements)

References 29 publications

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“…(2019) ACM Transactions on Knowledge Discovery from Data Computer Science ○ ● Cabalquinto et al. (2020) Telematics and Informatics Information Science & Library Science ○ ● Can and Demirbas (2015) Journal of Network and Computer Applications Public, Environmental & Occu. Health ○ ● Cao et al.…”

Section: Methodology Developmentmentioning

confidence: 99%

Towards a new era of mass data collection: Assessing pandemic surveillance technologies to preserve user privacy

Ribeiro‐Navarrete

Saura

Palacios‐Marqués

2021

Technological Forecasting and Social Change

159

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Controlling the coronavirus pandemic is triggering a cross-border strategy by which national governments attempt to control the spread of the COVID-19 pandemic. A response based on sharing facts about millions of private movements and a call to study information behavior during the global health crisis has been advised worldwide. The present study aims to identify the technologies to control the COVID-19 and future pandemics with massive data collection from users’ mobile devices. This research undertakes a Systematic Literature Review (SLR) of the studies about the currently available methods, strategies, and actions to collect and analyze data from users’ mobile devices. In a total of 76 relevant studies, 13 technologies that are classified based on the following aspect of data and data management have been identified: (1) security; (2) destruction; (3) voluntary access; (4) time span; and (5) storage. In addition, in order to understand how these technologies can affect user privacy, 25 data points that these technologies could have access to if installed through mobile applications have been detected. The paper concludes with a discussion of important theoretical and practical implications of preserving user privacy and curbing COVID-19 infections in the global public health emergency situation.

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Section: Methodology Developmentmentioning

confidence: 99%

Towards a new era of mass data collection: Assessing pandemic surveillance technologies to preserve user privacy

Ribeiro‐Navarrete

Saura

Palacios‐Marqués

2021

Technological Forecasting and Social Change

159

View full text Add to dashboard Cite

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“…This Wireless Sensor Network (WSN) is suitable for monitoring physical and chemical water characteristics in remote areas at lower cost and reduce manpower requirement [3]. It can be utilized for water quality monitoring [4] which presents many advantages like its portability [5] and near real-time data acquisition and data logging capability [6]. It has gained popularity among the research community ranging from environmentalist [7] to embedded systems community [8].…”

Section: Introductionmentioning

confidence: 99%

A system for monitoring water quality in a large aquatic area using wireless sensor network technology

Demetillo

Japitana

Taboada

2019

Sustain Environ Res

115

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In this paper, a low cost, real-time water quality monitoring system which can be applied in remote rivers, lakes, coastal areas and other water bodies is presented. The main hardware of the system consists of off-the-shelf electrochemical sensors, a microcontroller, a wireless communication system and the customized buoy. It detects water temperature, dissolved oxygen and pH in a pre-programmed time interval. The developed prototype disseminates the gathered information in graphical and tabular formats through a customized web-based portal and preregistered mobile phones to better serve relevant end-users. To check the system effectivity, the buoy's stability in harsh environmental conditions, system energy consumption, data transmission efficiency and webbased display of information were carefully evaluated. The experimental results prove that the system has great prospect and can be practically used for environmental monitoring by providing stakeholders with relevant and timely information for sound decision making.

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“…In summary, low-power wireless links deployed in forest environments are easily affected by the complex forest environment and then are both unreliable and extremely hard to precisely predict. Our experimental study discloses the importance of the following issues that need to be considered or addressed in practical wireless sensor networks deployed in forests: (1) how to model and evaluate the link validity with as effective and resource-efficient metrics as possible; (2) how to guarantee the reliable data delivery over the data-ack link of high asymmetry; (3) how to deploy wireless sensor nodes in forests such that the network topology can be kept efficiently connected with a high probability; (4) how to employ and schedule mobile sinks, such as mobile phones [ 9 , 32 ], to collect the sensory data, if the sensor network is unavoidably segmented due to poor links; and (5) how to achieve optimized cooperative designs across the link, the MAC and the routing layers [ 33 ] to further save the limited network energy.…”

Section: Summary Of Observationsmentioning

confidence: 99%

Link Investigation of IEEE 802.15.4 Wireless Sensor Networks in Forests

Ding

Sun

Yang

et al. 2016

Sensors

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Wireless sensor networks are expected to automatically monitor the ecological evolution and wildlife habits in forests. Low-power links (transceivers) are often adopted in wireless sensor network applications, in order to save the precious sensor energy and then achieve long-term, unattended monitoring. Recent research has presented some performance characteristics of such low-power wireless links under laboratory or outdoor scenarios with less obstacles, and they have found that low-power wireless links are unreliable and prone to be affected by the target environment. However, there is still less understanding about how well the low-power wireless link performs in real-world forests and to what extent the complex in-forest surrounding environments affect the link performances. In this paper, we empirically evaluate the low-power links of wireless sensors in three typical different forest environments. Our experiment investigates the performance of the link layer compatible with the IEEE 802.15.4 standard and analyzes the variation patterns of the packet reception ratio (PRR), the received signal strength indicator (RSSI) and the link quality indicator (LQI) under diverse experimental settings. Some observations of this study are inconsistent with or even contradict prior results that are achieved in open fields or relatively clean environments and thus, provide new insights both into effectively evaluating the low-power wireless links and into efficiently deploying wireless sensor network systems in forest environments.

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Smartphone-based data collection from wireless sensor networks in an urban environment

Cited by 25 publications

References 29 publications

Towards a new era of mass data collection: Assessing pandemic surveillance technologies to preserve user privacy

Towards a new era of mass data collection: Assessing pandemic surveillance technologies to preserve user privacy

A system for monitoring water quality in a large aquatic area using wireless sensor network technology

Link Investigation of IEEE 802.15.4 Wireless Sensor Networks in Forests

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