scholarly journals Multi-modal data collection for measuring health, behavior, and living environment of large-scale participant cohorts

GigaScience ◽  
2021 ◽  
Vol 10 (6) ◽  
Author(s):  
Congyu Wu ◽  
Hagen Fritz ◽  
Sepehr Bastami ◽  
Juan P Maestre ◽  
Edison Thomaz ◽  
...  
Keyword(s):  
Data Collection ◽  
Large Scale ◽  
Conceptual Development ◽  
Ecological Validity ◽  
Mobile Sensing ◽  
Living Environment ◽  
Mobile Technologies ◽  
Smart Devices ◽  
Sleep Behavior ◽  
Data Continuity

Abstract Background As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users’ daily lives with unprecedented comprehensiveness and ecological validity. A number of human-subject studies have been conducted to examine the use of mobile sensing to uncover individual behavioral patterns and health outcomes, yet minimal attention has been placed on measuring living environments together with other human-centered sensing data. Moreover, the participant sample size in most existing studies falls well below a few hundred, leaving questions open about the reliability of findings on the relations between mobile sensing signals and human outcomes. Results To address these limitations, we developed a home environment sensor kit for continuous indoor air quality tracking and deployed it in conjunction with smartphones, Fitbits, and ecological momentary assessments in a cohort study of up to 1,584 college student participants per data type for 3 weeks. We propose a conceptual framework that systematically organizes human-centric data modalities by their temporal coverage and spatial freedom. Then we report our study procedure, technologies and methods deployed, and descriptive statistics of the collected data that reflect the participants’ mood, sleep, behavior, and living environment. Conclusions We were able to collect from a large participant cohort satisfactorily complete multi-modal sensing and survey data in terms of both data continuity and participant adherence. Our novel data and conceptual development provide important guidance for data collection and hypothesis generation in future human-centered sensing studies.

Inspection Technologies and Crisis Management: Field Automation lessons from the field

2014 ◽  
Vol 2014 (1) ◽  
pp. 300246
Author(s):  
Donald P. Smith
Keyword(s):  
Data Collection ◽  
Disaster Response ◽  
Large Scale ◽  
Data Dissemination ◽  
Low Cost ◽  
Mobile Technologies ◽  
Bring Your Own Device ◽  
Accurate Information ◽  
Non Profit ◽  
Additional Support

The task of capturing accurate information from the field and sharing it with response teams, incident commanders, command posts, regional offices, and internal/external agencies in a timely manner is a goal that has been difficult to achieve, especially on large-scale events. Growing fiscal constraints necessitate that solutions be part of a stable reusable system that is easily used by responders/inspectors, and also easily expanded when additional support and complexity become necessary. However, the various types of events/activities can be very challenging for both responders and inspectors. Government agencies are not always homogenous; their regional branches may collect different details on the same object, leading to incompatibilities between regional information. If the various agencies' engaged in data collection and dissemination does not standardize their efforts, then, information meltdown occurs. Ultimately, the data that were collected and disseminated become untrustworthy and unreliable. In some cases, this can compromise enforcement actions. Once information is collected, it also requires processing and distribution to different internal, external, non-profit, and private agencies. Recent mobile technologies that are available through smart phones and tablets offer solutions that allow quick customizations, scalability, and low-cost alternatives to data collection/dissemination. The concept of ‘Bring Your Own Device’ (BYOD) helps agencies to utilize existing equipment/infrastructure and to standardize policies and minimize training/software needs. These technologies can be utilized during all phases of Disaster Management – mitigation, preparedness, response, recovery, and day-to-day inspection activities. This shifting paradigm offers opportunities for all field-deployed personnel to share data in a near real-time environment. Over the past few decades, we have been actively involved in developing field inspection applications and establishing an infrastructure for Disaster Response/inspection programs that has allowed EPA to successfully manage field data collection. This poster intends to share these efforts and to demonstrate their effectiveness. The following is a list of issues that will be covered by the application of field automation: cost sharing, rapid application deployment, ease of training, Internet sharing, data quality, and data dissemination.

scholarly journals Smart Devices in Airbnbs: Considering Privacy and Security for both Guests and Hosts

2020 ◽  
Vol 2020 (2) ◽  
pp. 436-458 ◽  
Author(s):  
Shrirang Mare ◽  
Franziska Roesner ◽  
Tadayoshi Kohno
Keyword(s):  
Data Collection ◽  
Large Scale ◽  
Security And Privacy ◽  
Smart Devices ◽  
Monitoring And Control ◽  
Data Types ◽  
Privacy And Security ◽  
Large Scale Survey ◽  
Internet History ◽  
And Control

AbstractConsumer smart home devices are becoming increasingly pervasive. As Airbnb hosts deploy smart devices in spaces shared with guests, we seek to understand the security and privacy implications of these devices for both hosts and guests. We conducted a large-scale survey of 82 hosts and 554 guests to explore their current technology practices, their preferences for smart devices and data collection/sharing, and their privacy and security concerns in the context of Airbnbs. We found that guests preferred smart devices, even viewed them as a luxury, but some guests were concerned that smart devices enable excessive monitoring and control, which could lead to repercussions from hosts (e.g., locked thermostat). On average, the views of guests and hosts on data collection in Airbnb were aligned, but for the data types where differences occur, serious privacy violations might happen. For example, 90% of our guest participants did not want to share their Internet history with hosts, but one in five hosts wanted access to that information. Overall, our findings surface tensions between hosts and guests around the use of smart devices and in-home data collection. We synthesize recommendations to address the surfaced tensions and identify broader research challenges.

scholarly journals Acceleration of Inner-Pairing Product Operation for Secure Biometric Verification

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2859
Author(s):  
Seong-Yun Jeon ◽  
Mun-Kyu Lee
Keyword(s):  
Mobile Technologies ◽  
Smart Devices ◽  
Biometric Data ◽  
Product Operation ◽  
Biometric Verification ◽  
Naive Method ◽  
Biometric Template ◽  
Need To Evaluate ◽  
Time Required ◽  
Pairing Product

With the recent advances in mobile technologies, biometric verification is being adopted in many smart devices as a means for authenticating their owners. As biometric data leakage may cause stringent privacy issues, many proposals have been offered to guarantee the security of stored biometric data, i.e., biometric template. One of the most promising solutions is the use of a remote server that stores the template in an encrypted form and performs a biometric comparison on the ciphertext domain, using recently proposed functional encryption (FE) techniques. However, the drawback of this approach is that considerable computation is required for the inner-pairing product operation used for the decryption procedure of the underlying FE, which is performed in the authentication phase. In this paper, we propose an enhanced method to accelerate the inner-pairing product computation and apply it to expedite the decryption operation of FE and for faster remote biometric verification. The following two important observations are the basis for our improvement—one of the two arguments for the decryption operation does not frequently change over authentication sessions, and we only need to evaluate the product of multiple pairings, rather than individual pairings. From the results of our experiments, the proposed method reduces the time required to compute an inner-pairing product by 30.7%, compared to the previous best method. With this improvement, the time required for biometric verification is expected to decrease by up to 10.0%, compared to a naive method.

scholarly journals Privacy Leakage in Mobile Sensing: Your Unlock Passwords Can Be Leaked through Wireless Hotspot Functionality

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Jie Zhang ◽  
Xiaolong Zheng ◽  
Zhanyong Tang ◽  
Tianzhang Xing ◽  
Xiaojiang Chen ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Mobile Sensing ◽  
Experimental Results ◽  
Smart Devices ◽  
Detection Accuracy ◽  
Phase Information ◽  
Current Sensing ◽  
Privacy Leakage ◽  
Sensing Systems ◽  
Additional Hardware

Mobile sensing has become a new style of applications and most of the smart devices are equipped with varieties of sensors or functionalities to enhance sensing capabilities. Current sensing systems concentrate on how to enhance sensing capabilities; however, the sensors or functionalities may lead to the leakage of users’ privacy. In this paper, we present WiPass, a way to leverage the wireless hotspot functionality on the smart devices to snoop the unlock passwords/patterns without the support of additional hardware. The attacker can “see” your unlock passwords/patterns even one meter away. WiPass leverages the impacts of finger motions on the wireless signals during the unlocking period to analyze the passwords/patterns. To practically implement WiPass, we are facing the difficult feature extraction and complex unlock passwords matching, making the analysis of the finger motions challenging. To conquer the challenges, we use DCASW to extract feature and hierarchical DTW to do unlock passwords matching. Besides, the combination of amplitude and phase information is used to accurately recognize the passwords/patterns. We implement a prototype of WiPass and evaluate its performance under various environments. The experimental results show that WiPass achieves the detection accuracy of 85.6% and 74.7% for passwords/patterns detection in LOS and in NLOS scenarios, respectively.

LARGE-SCALE PREDICTOR VALIDATION IN PROJECT A: DATA COLLECTION PROCEDURES AND DATA BASE PREPARATION

1990 ◽  
Vol 43 (2) ◽  
pp. 301-311 ◽  
Author(s):  
WINNIE Y. YOUNG ◽  
JANIS S. HOUSTON ◽  
JAMES H. HARRIS ◽  
R. GENE HOFFMAN ◽  
LAURESS L. WISE
Keyword(s):  
Data Collection ◽  
Data Base ◽  
Large Scale

scholarly journals The W Model, a Systematic Engineering for Water Source Clearance, Renewable Energy Production, and Ecological Agricuture Development – A Proposal for Sustainable Development

2017 ◽  
Vol 10 (5) ◽  
pp. 143
Author(s):  
Tongyuan Wang
Keyword(s):  
Renewable Energy ◽  
Large Scale ◽  
Organic Fertilizer ◽  
Water Source ◽  
Small Towns ◽  
Living Environment ◽  
Economic Feasibility ◽  
Organic Fertilizers ◽  
Ecological Agriculture ◽  
Agriculture Development

This article proposes a systematic engineering for sustainable economic and ecologic development. This system is deemed to be applicable in any country of the world. The system aims to realize five important objectives: water source clearance, energy saving and emission reduction, renewable energy and organic fertilizer production, and ecological agriculture development, all in large scale and at low cost. The main conception of the new system to reach these goals is the replacement of the conventional sewage treatment approach with more efficient and more ecological process – the natural fermentation of the mixture of the urban sewage and agrarian wastes, such that water body clearance, including water de-eutrophication, green algae prevention and siltation dredging will all be accomplished at virtually a zero cost. Along with this process, the system can produce a vast amount of renewable energy and organic fertilizers, consequently ecological agriculture development in large scale can be realized. As a result, this system will greatly reduce the use of chemical fertilizers thus largely reduce the consumption of fossil energy and the related polluting emissions. This system is thus fully a circular economy model through full west-reuse processes, which ultimately will enhance our life quality with healthier food and living environment. The system is flexible and adaptable to be implemented in either small towns or megacities. The implementation and operation of this system will also benefits employment growth. Lastly, in terms of economic feasibility and profitability, millions to billions of dollars of annual revenue can be generated from the running of this system in a country.

Energy Efficient Data Collection in Large-Scale Internet of Things via Computation Offloading

2019 ◽  
Vol 6 (3) ◽  
pp. 4176-4187 ◽  
Author(s):  
Guorui Li ◽  
Jingsha He ◽  
Sancheng Peng ◽  
Weijia Jia ◽  
Cong Wang ◽  
...  
Keyword(s):  
Data Collection ◽  
Internet Of Things ◽  
Energy Efficient ◽  
Large Scale ◽  
Computation Offloading ◽  
Efficient Data ◽  
Efficient Data Collection

scholarly journals Resistance to Canadian mining projects in Mexico: lessons from the lifecycle of the San Xavier Mine in San Luis Potosí

2019 ◽  
Vol 26 (1) ◽  
pp. 84 ◽  
Author(s):  
Darcy Victor Tetreault
Keyword(s):  
Large Scale ◽  
Local Level ◽  
Living Environment ◽  
Human Consumption ◽  
Ecological Distribution ◽  
Political Class ◽  
San Luis ◽  
San Luis Potosi ◽  
Mining Projects ◽  
San Luis Potosí

<p>This article analyses resistance movements to large-scale mining projects in Mexico, particularly the case of sustained organized resistance to the San Xavier Mine, in the central north state of San Luis Potosí. As one of the first struggles in Mexico against Canadian mining projects after the signing of the North American Free Trade Agreement, the leaders of this movement pioneered strategies of resistance on the legal front and were instrumental in building anti-mining alliances and networks on the national and international levels. Now that the excavation process has finished and the mine is closing down, this article seeks to draw on the case to illustrate the complementarity of three approaches for interpreting resistance to mining: class struggle, ecological distribution conflicts, and the clash of cultural valuations over territorial vocation. The argument is that these approaches are not mutually exclusive; they can be combined to explain the multiple dimensions of specific struggles, whose shifts in emphasis at different moments of the struggle are conditioned by – and condition – the phase of a mine's development. By contextualizing the case study in a broader analysis of social environmental conflicts around mining in Mexico and elsewhere in Latin America, the analysis seeks to illustrate the ways in which the struggle against the San Xavier Mine is representative of broader trends, as well as its peculiarities. On the local level, we find the struggle has more to do with defending conditions of social and cultural reproduction than protecting the means of production that sustain traditional livelihoods. This pertains, not just to a non-contaminated living environment and the availability of clean water for human consumption, but also to the conservation of natural and architectural patrimony with historic and cultural significance.</p><p><strong>Key words</strong>: Mining conflicts, Canadian imperialism, political class formation, ecological distribution, cultural valuations</p>

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