Contextual sensitivity of the ambient temperature sensor in Smartphones
04 May 2015-pp 1-8
TL;DR: This work evaluates the sensitivity and accuracy of the on-board ambient temperature sensor under various circumstances and measures its performance against standardized weather monitoring equipment, and identifies the roles of several internal and external factors that affect the temperature data.
Abstract: Environmental monitoring using external and Smartphone-interfaced wireless sensors has been widely used in the past. The roadblocks start emerging when we use on-board sensors in off-the-shelf Smartphones to estimate context aware environmental parameters like ambient temperature, humidity and atmospheric pressure. In this work, we evaluate the sensitivity and accuracy of the on-board ambient temperature sensor under various circumstances and measure its performance against standardized weather monitoring equipment. Additionally, we identify the roles of several internal and external factors that affect the temperature data. Such an investigation is motivated by the need of pervasive temperature sensing to power Smart HVAC environments and for weather crowdsourcing. Our experiments reveal that while the on-board temperature sensors have great potential, using them for large scale data collection still requires significant work.
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Zhejiang University1, Cooperative Research Centre2, University of Adelaide3, International Institute for Applied Systems Analysis4, University of Exeter5, University of Illinois at Urbana–Champaign6, Hong Kong University of Science and Technology7, Swiss Federal Institute of Aquatic Science and Technology8, Southern Methodist University9, Zhejiang University of Technology10, Delft University of Technology11
TL;DR: A review of the state of the art in this field can be found in this article, where the authors present a framework for categorizing the methods used in the seven domains of geophysics considered in this review.
Abstract: Data are essential in all areas of geophysics. They are used to better understand and manage systems, either directly or via models. Given the complexity and spatiotemporal variability of geophysical systems (e.g., precipitation), a lack of sufficient data is a perennial problem, which is exacerbated by various drivers, such as climate change and urbanization. In recent years, crowdsourcing has become increasingly prominent as a means of supplementing data obtained from more traditional sources, particularly due to its relatively low implementation cost and ability to increase the spatial and/or temporal resolution of data significantly. Given the proliferation of different crowdsourcing methods in geophysics and the promise they have shown, it is timely to assess the state of the art in this field, to identify potential issues and map out a way forward. In this paper, crowdsourcing-based data acquisition methods that have been used in seven domains of geophysics, including weather, precipitation, air pollution, geography, ecology, surface water, and natural hazard management, are discussed based on a review of 162 papers. In addition, a novel framework for categorizing these methods is introduced and applied to the methods used in the seven domains of geophysics considered in this review. This paper also features a review of 93 papers dealing with issues that are common to data acquisition methods in different domains of geophysics, including the management of crowdsourcing projects, data quality, data processing, and data privacy. In each of these areas, the current status is discussed and challenges and future directions are outlined.
86 citations
Cites background from "Contextual sensitivity of the ambie..."
...…that is, whether they are indoors or outdoors or if a smartphone is carried in a pocket or handbag, and a lack of calibration or modifications for sensor drift (Anderson et al., 2012; Honicky et al., 2008; Majethia et al., 2015; Overeem, Leijnse, et al., 2013; Wolters & Brandsma, 2012)....
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...Clear protocols are also needed for collecting data from vehicles, low-cost sensors, and smartphones in order to deal with inconsistencies in the conditions of the equipment, such as the running speed of the vehicles, the operating system version of the smartphones, the conditions of batteries, the sensor environments, that is, whether they are indoors or outdoors or if a smartphone is carried in a pocket or handbag, and a lack of calibration or modifications for sensor drift (Anderson et al., 2012; Honicky et al., 2008; Majethia et al., 2015; Overeem, Leijnse, et al., 2013; Wolters & Brandsma, 2012)....
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TL;DR: The proposed approach, aiming at overcoming the limitation of existing disease surveillance approaches, combines the hybrid crowdsensing paradigm with sensing individuals’ bio-signals using optical sensors for monitoring any risks of spreading emerging infectious diseases in any (ad-hoc) crowds.
Abstract: The risk of spreading diseases within (ad-hoc)crowds and the need to pervasively screen asymptomatic individuals to protect the population against emerging infectious diseases, request permanentcrowd surveillance., particularly in high-risk regions. Thecase of Ebola epidemic in West Africa in recent years has shown the need for pervasive screening. The trend today in diseases surveillance is consisting of epidemiological data collection about emerging infectious diseases using social media, wearable sensors systems, or mobile applications and data analysis. This approach presents various limitations. This paper proposes a novel approach for diseases monitoring and risk prevention of spreading infectious diseases. The proposed approach, aiming at overcoming the limitation of existing disease surveillance approaches, combines the hybrid crowdsensing paradigm with sensing individuals’ bio-signals using optical sensors for monitoring any risks of spreading emerging infectious diseases in any (ad-hoc) crowds. A proof-of-concept has been performed using a drone armed with a cat s60 smartphone featuring a Forward Looking Infra-Red (FLIR) camera. According to the results of the conducted experiment, the concept has the potential to improve the conventional epidemiological data collection. The measurement is reliable, and the recorded data are valid. The measurement error rates are about 8%.
15 citations
Cites background from "Contextual sensitivity of the ambie..."
...have evaluated in [20] the sensitivity and accuracy of the onboard ambient temperature sensor under various circumstances and measure its performance against standardized weather monitoring equipment....
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18 Mar 2020
TL;DR: Batteries-as-Thermometers is designed and implemented, a temperature sensing service based on the information of mobile device batteries, expanding the ability to sense the device's ambient temperature without requiring additional sensors or taking up the limited on-device space.
Abstract: The ability to sense ambient temperature pervasively, albeit crucial for many applications, is not yet available, causing problems such as degraded indoor thermal comfort and unexpected/premature shutoffs of mobile devices. To enable pervasive sensing of ambient temperature, we propose use of mobile device batteries as thermometers based on (i) the fact that people always carry their battery-powered smart phones, and (ii) our empirical finding that the temperature of mobile devices' batteries is highly correlated with that of their operating environment. Specifically, we design and implement Batteries-as-Thermometers (BaT), a temperature sensing service based on the information of mobile device batteries, expanding the ability to sense the device's ambient temperature without requiring additional sensors or taking up the limited on-device space. We have evaluated BaT on 6 Android smartphones using 19 laboratory experiments and 36 real-life field-tests, showing an average of 1.25°C error in sensing the ambient temperature.
12 citations
Cites background from "Contextual sensitivity of the ambie..."
...25oC in an indoor environment was also reported in [44]....
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..., up to 20% error [44]), thus making it inaccurate and also untimely....
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...(1) Ambient temperature is spatially non-uniform in both outdoor and indoor environments [44, 46]: (i) statistics show a temperature di erence of up to 12oC between urban and rural outdoor areas, caused by the urban heat island e ect [41] resulting from urbanization; (ii) the non-uniformity of indoor ambient temperature can be seen from Fig....
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01 Jan 2013
TL;DR: S4除了规格变得更强大．有1Ｕ9GHZ四核处理器与1 ．6GHZ
Abstract: S4除了规格变得更强大．有1．9GHZ四核处理器与1．6GHZ八核处理器．5英寸HDS—AMOLED屏幕以及1300万像素拍照等规格．相机画质、功能都有很大进步．能开启前后镜头同时拍照，还新加入非常多的新鲜功能．像是可以用眼睛或手势控制网页浏览．锁屏时也有Widget功能．影片自动暂停等．不管是实用性还是新奇程度都非常令人惊艳。
8 citations
30 Jun 2016
TL;DR: This work looks at the possibility of identifying indoor locations with likely incorrect/stale Wi-Fi fingerprints, by using concurrent readings fromWi-Fi and barometer sensors from a collection of mobile devices.
Abstract: We explore the use of multi-dimensional mobile sensing data as a means of identifying errors in one or more of those data streams. More specifically, we look at the possibility of identifying indoor locations with likely incorrect/stale Wi-Fi fingerprints, by using concurrent readings from Wi-Fi and barometer sensors from a collection of mobile devices. Our key contribution is a novel two-step process: (i) using longitudinal, crowd-sourced readings of (possibly incorrect) Wi-Fi location estimates to statistically estimate the barometer calibration offset of individual mobile devices, and (ii) then, using such offset-corrected barometer readings from devices (that are supposedly collocated) to identify likely errors in indoor localization. We evaluate this approach using data collected from 104 devices collected on the SMU campus over a period of 61 days: our results show that (i) 49% of the devices had barometer offsets that result in errors in floor-level estimation, and (iii) 46% of the Wi-Fi location estimates were potentially incorrect. By identifying specific locations with unusually high fraction of incorrect location estimates, we attempt to more accurately pinpoint the areas that need re-fingerprinting.
7 citations
Cites background from "Contextual sensitivity of the ambie..."
...Majethia et al [5] further showed that the barometer static offset is not constant, but affected by additional context factors, such as the phone’s temperature....
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