Passive sensing by Sentinel-1 SAR: Methods and applications

2022 ◽  
Vol 270 ◽  
pp. 112866
Author(s):  
Andrea Monti-Guarnieri ◽  
Clement Albinet ◽  
Alessandro Cotrufo ◽  
Niccolò Franceschi ◽  
Marco Manzoni ◽  
...  
Keyword(s):  
Passive Sensing

Author response for "Use of passive sensing to quantify adolescent mobile device usage: Feasibility, acceptability, and preliminary validation of the eMoodie application"

2020 ◽  
Author(s):  
Sarah E. Domoff ◽  
Claire Ann Banga ◽  
Aubrey L. Borgen ◽  
Ryan P. Foley ◽  
Chelsea Robinson ◽  
...  
Keyword(s):  
Mobile Device ◽  
Author Response ◽  
Passive Sensing ◽  
Preliminary Validation

PROFILING OF CLOUD WATER CONTENT BY ACTIVE-PASSIVE SENSING

2014 ◽  
Vol 73 (13) ◽  
pp. 1141-1152
Author(s):  
Ye. N. Belov ◽  
B. A. Kabanov ◽  
Stanislav I. Khomenko ◽  
G. I. Khlopov ◽  
A. M. Linkova ◽  
...  
Keyword(s):  
Water Content ◽  
Cloud Water ◽  
Passive Sensing ◽  
Cloud Water Content

scholarly journals Passive sensing on mobile devices to improve mental health services with adolescent and young mothers in low-resource settings: the role of families in feasibility and acceptability

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sujen Man Maharjan ◽  
Anubhuti Poudyal ◽  
Alastair van Heerden ◽  
Prabin Byanjankar ◽  
Ada Thapa ◽  
...  
Keyword(s):  
Data Collection ◽  
Health Services ◽  
Mobile Devices ◽  
Family Involvement ◽  
Mobile Phones ◽  
Young Mothers ◽  
Audio Recording ◽  
Low Resource Settings ◽  
Passive Sensing ◽  
Passive Data

Abstract Background Passive sensor data from mobile devices can shed light on daily activities, social behavior, and maternal-child interactions to improve maternal and child health services including mental healthcare. We assessed feasibility and acceptability of the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) platform. The StandStrong passive data collection platform was piloted with adolescent and young mothers, including mothers experiencing postpartum depression, in Nepal. Methods Mothers (15–25 years old) with infants (< 12 months old) were recruited in person from vaccination clinics in rural Nepal. They were provided with an Android smartphone and a Bluetooth beacon to collect data in four domains: the mother’s location using the Global Positioning System (GPS), physical activity using the phone’s accelerometer, auditory environment using episodic audio recording on the phone, and mother-infant proximity measured with the Bluetooth beacon attached to the infant’s clothing. Feasibility and acceptability were evaluated based on the amount of passive sensing data collected compared to the total amount that could be collected in a 2-week period. Endline qualitative interviews were conducted to understand mothers’ experiences and perceptions of passive data collection. Results Of the 782 women approached, 320 met eligibility criteria and 38 mothers (11 depressed, 27 non-depressed) were enrolled. 38 mothers (11 depressed, 27 non-depressed) were enrolled. Across all participants, 5,579 of the hour-long data collection windows had at least one audio recording [mean (M) = 57.4% of the total possible hour-long recording windows per participant; median (Mdn) = 62.6%], 5,001 activity readings (M = 50.6%; Mdn = 63.2%), 4,168 proximity readings (M = 41.1%; Mdn = 47.6%), and 3,482 GPS readings (M = 35.4%; Mdn = 39.2%). Feasibility challenges were phone battery charging, data usage exceeding prepaid limits, and burden of carrying mobile phones. Acceptability challenges were privacy concerns and lack of family involvement. Overall, families’ understanding of passive sensing and families’ awareness of potential benefits to mothers and infants were the major modifiable factors increasing acceptability and reducing gaps in data collection. Conclusion Per sensor type, approximately half of the hour-long collection windows had at least one reading. Feasibility challenges for passive sensing on mobile devices can be addressed by providing alternative phone charging options, reverse billing for the app, and replacing mobile phones with smartwatches. Enhancing acceptability will require greater family involvement and improved communication regarding benefits of passive sensing for psychological interventions and other health services. Registration International Registered Report Identifier (IRRID): DERR1-10.2196/14734

Statistical Analysis of SHM Passive Sensing Systems

2015 ◽  
Vol 665 ◽  
pp. 241-244
Author(s):  
Marco Thiene ◽  
Zahra Sharif Khodaei ◽  
M.H. Aliabadi
Keyword(s):  
Statistical Analysis ◽  
Health Monitoring ◽  
Sensor Failure ◽  
Impact Detection ◽  
Sensing Systems ◽  
Detection And Identification ◽  
Passive Sensing ◽  
Service Load ◽  
Reliability And Robustness ◽  
Load Conditions

Structural Health Monitoring (SHM) techniques have gained an increased interest to be utilised alongside NDI techniques for aircraft maintenance. However, to take the SHM methodologies from the laboratory conditions to actual structures under real load conditions requires them to be assessed in terms of reliability and robustness. In this work, a statistical analysis is carried out for a passive SHM system capable of impact detection and identification. The sensitivity of the platform to parameters such as noise, sensor failure and in-service load conditions has been investigated and reported.

A review of passive self-sensing tag

Sensor Review ◽  
2017 ◽  
Vol 37 (3) ◽  
pp. 338-345 ◽  
Author(s):  
Yawei Xu ◽  
Lihong Dong ◽  
Haidou Wang ◽  
Jiannong Jing ◽  
Yongxiang Lu
Keyword(s):  
Radio Frequency Identification ◽  
Large Scale ◽  
Low Cost ◽  
Integrated Sensor ◽  
Content Type ◽  
Passive Sensing ◽  
Static Information ◽  
Potential Applications ◽  
Frequency Identification ◽  
Identification Tags

Purpose Radio frequency identification tags for passive sensing have attracted wide attention in the area of Internet of Things (IoT). Among them, some tags can sense the property change of objects without an integrated sensor, which is a new trend of passive sensing based on tag. The purpose of this paper is to review recent research on passive self-sensing tags (PSSTs). Design/methodology/approach The PSSTs reported in the past decade are classified in terms of sensing mode, composition and the ways of power supply. This paper presents operation principles of PSSTs and analyzes the characteristics of them. Moreover, the paper focuses on summarizing the latest sensing parameters of PSSTs and their matching equipment. Finally, some potential applications and challenges faced by this emerging technique are discussed. Findings PSST is suitable for long-term and large-scale monitoring compared to conventional sensors because it gets rid of the limitation of battery and has relatively low cost. Also, the static information of objects stored in different PSSTs can be identified by a single reader without touch. Originality/value This paper provides a detailed and timely review of the rapidly growing research in PSST.

Three-dimensional passive sensing photon counting for object classification

2007 ◽  
Author(s):  
Seokwon Yeom ◽  
Bahram Javidi ◽  
Edward Watson
Keyword(s):  
Photon Counting ◽  
Three Dimensional ◽  
Object Classification ◽  
Passive Sensing
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