Background: Technological advancements, together with the decrease in both price and size of a large variety of sensors, has expanded the role and capabilities of regular mobile phones, turning them into powerful yet ubiquitous monitoring systems. At present, smartphones have the potential to continuously collect information about the users, monitor their activities and behaviors in real time, and provide them with feedback and recommendations. Objective: This systematic review aimed to identify recent scientific studies that explored the passive use of smartphones for generating health- and well-being–related outcomes. In addition, it explores users’ engagement and possible challenges in using such self-monitoring systems. Methods: A systematic review was conducted, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, to identify recent publications that explore the use of smartphones as ubiquitous health monitoring systems. We ran reproducible search queries on PubMed, IEEE Xplore, ACM Digital Library, and Scopus online databases and aimed to find answers to the following questions: (1) What is the study focus of the selected papers? (2) What smartphone sensing technologies and data are used to gather health-related input? (3) How are the developed systems validated? and (4) What are the limitations and challenges when using such sensing systems? Results: Our bibliographic research returned 7404 unique publications. Of these, 118 met the predefined inclusion criteria, which considered publication dates from 2014 onward, English language, and relevance for the topic of this review. The selected papers highlight that smartphones are already being used in multiple health-related scenarios. Of those, physical activity (29.6%; 35/118) and mental health (27.9; 33/118) are 2 of the most studied applications. Accelerometers (57.7%; 67/118) and global positioning systems (GPS; 40.6%; 48/118) are 2 of the most used sensors in smartphones for collecting data from which the health status or well-being of its users can be inferred. Conclusions: One relevant outcome of this systematic review is that although smartphones present many advantages for the passive monitoring of users’ health and well-being, there is a lack of correlation between smartphone-generated outcomes and clinical knowledge. Moreover, user engagement and motivation are not always modeled as prerequisites, which directly affects user adherence and full validation of such systems.

/pdf/passive-sensing-of-health-outcomes-through-smartphones-2sylm61fgo.pdf

Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations

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.

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2018RG000616

Crowdsourcing Methods for Data Collection in Geophysics : State of the Art, Issues, and Future Directions

Knjiga Prekinuta veza: zastita djetinjstva i obiteljskih odnosa u digitalnome dobu usmjerena je razvoju kvalitetnih i cvrstih odnosa unutar obitelji na osnovi kojih ce se i pojedini clanovi obitelji i obitelj kao zajednica moci lakse snalaziti u vrijeme nekontrolirane upotrebe tehnologija i medija. Knjiga nije namijenjena samo roditeljima i djeci nego i prakticarima i istraživacima u sustavu odgoja i obrazovanja kojima ce služiti kao prirucnik za strucno djelovanje. U toj se svrsi ogleda najvažniji doprinos ove knjige. Autorica na zanimljiv nacin sintetizira teorijsko znanje i podatke koje je dugi niz godina prikupljala svojim terapeutskim radom s djecom i obiteljima. Intenzivno naglasava da je suvremena obitelj u krizi zbog napretka tehnologije sto na nju i njezine clanove, bez izgradnje zastitnih mehanizama, može ostaviti dugotrajne i ozbiljne posljedice. Tehnologija ne može biti zamjena za jedinstvene i bliske interakcije među osobama. U svim poglavljima autorica, osim sto prezentira niz primjera iz stvarnoga života, nudi i konkretne savjete u obliku smjernica roditeljima s ciljem izgradnje autoriteta, potpunijega razumijevanja djece i autonomije u kulturi življenja i nacinu uporabe tehnologije i medija. Partnerski pristup skole, roditelja i sirega okruženja može služiti kao preduvjet za kulturu socijalne interakcije koja ce prednjaciti nad nekontroliranom uporabom tehnologije i medija i zaokupljenoscu njima. Pristup Catherine Steiner-Adair svakako proizlazi iz osobnih kompetencija koje stavlja u funkciju dobrobiti obitelji s ciljem njezine zastite u digitalnome dobu.

The Big Disconnect : Protecting Childhood and Family Relationships in the Digital Age

The effects of mobile promotions on customer purchase dynamics

Over the years, mobile phones have become versatile devices with a multitude of capabilities due to the plethora of embedded sensors that enable them to capture rich data unobtrusively. In a world where people are more conscious regarding their health and well-being, the pervasiveness of smartphones has enabled researchers to build apps that assist people to live healthier lifestyles, and to diagnose and monitor various health conditions. Motivated by the high smartphone coverage among young adults and the unique issues they face, in this review paper, we focus on studies that have used smartphone sensing for the well-being of young adults. We analyze existing work in the domain from two perspectives, namely Data Perspective and System Perspective. For both these perspectives, we propose taxonomies motivated from human science literature, which enable to identify important study areas. Furthermore, we emphasize the importance of diversity-awareness in smartphone sensing, and provide insights and future directions for researchers in ubiquitous and mobile computing, and especially to new researchers who want to understand the basics of smartphone sensing research targeting the well-being of young adults.

Smartphone Sensing for the Well-Being of Young Adults: A Review

Large-scale mobile data studies can reveal valuable insights into user behavior, which in turn can assist system designers to create better user experiences. After a careful review of existing mobile data literature, we found that there have been no large-scale studies to understand smartphone usage behavior in India -- the second-largest and fastest growing smartphone market in the world. With the goal of understanding various facets of smartphone usage in India, we conducted a mixed-method longitudinal data collection study through an Android app released on Google Play. Our app was installed by 215 users, and logged 11.9 million data points from them over a period of 8 months. We analyzed this rich dataset along the lines of four broad facets of smartphone behavior -- how users use different apps, interact with notihcations, react to different contexts, and charge their smartphones -- to paint a holistic picture of smartphone usage behavior of Indian users. This quantitative analysis was complemented by a survey with 55 users and semi-structured interviews with 26 users to deeply understand their smartphone usage behavior. While our first-of-its-kind study uncovered many interesting facts about Indian smartphone users, we also found striking differences in usage behavior compared to past studies in other geographical contexts. We observed that Indian users spend significant time with their smartphones after midnight, continuously check notifications without attending to them and are extremely conscious about their smartphones’ battery. Perhaps the most dramatic finding is the nature of mobile consumerism of Indian users as shown by our results. Taken together, these and the rest of our findings demonstrate the unique characteristics that are shaping the smartphone usage behavior of Indian users.

Moving Beyond Market Research: Demystifying Smartphone User Behavior in India

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.

Contextual sensitivity of the ambient temperature sensor in Smartphones

With the evolution of nuclear families and diverse career options, families as social groups are spending lesser time together than in the past decades. In this work, we study both quantitative as well as qualitative aspects of time spent with family members through a smartphone-based pervasive study on a sample of 12 families over 14 days. Further, we also examine the perception of 78 millennials on what they feel about, and expect from, the time they spend with their families, however long it may be. We aim to identify the key parameters that shape family life in this day and age, along with examining the participation of individuals of various roles within the family in activities such as conversations, workout sessions, eating together and other social interactions. Among all activities detected to be performed by families reporting high satisfaction with familial life, Eating Together and Using Smartphones Together emerged as the most prominent ones. We discover a greater disparity among the habits of family members, especially millennials, staying away from each other as compared to those staying together.

https://dl.acm.org/doi/pdf/10.1145/3144730.3144735

Smartphone-based Qualitative Analyses of Social Activities During Family Time

In this paper, we describe PeopleSave - a drug recommendation and feedback system for doctors on the basis of contextual patient reviews crowd-sourced from the Internet. Unlike other systems proposed in the past, we filter information sources to check for crowdsourcing feasibility and then assess the drug's effectiveness based on its reported detrimental effect on a patient. This helps in eliminating certain drugs that would almost certainly have an adverse effect on the patient's health and thereby obtain a set of recommendable drugs. These recommendations are further refined by analyzing the sentiment behind the opinions of patients who have been administered these drugs in the past. The resultant set of prescribable drugs agrees with those suggested by the consulted physicians for the considered sample set of diabetes patients. The critical assessment of the prototype system for Diabetes Type II drugs by both doctors and patients also reiterates the need for a feedback system that can possibly go a long way in improving patient experience of a drug. This leads us to conclude that PeopleSave, as a combination of the recommendation system prototype and the proposed feedback system, can be successful in improving the process of prescription of medicines for a varied range of medical conditions.

PeopleSave: Recommending effective drugs through web crowdsourcing

In the world of smart objects, device-ranging and localization using Bluetooth Low Energy (BLE) is becoming popular due to its attractive energy performance, wide platform support and low costs. There has been sufficient motivation on statistical analysis of Channel State Information of Received Signal Strength Indicator (RSSI) data for more effective ranging-based models. However, there has been no ubiquitous solution which is both receiver-agnostic and does not require alteration in the advertisement protocol or packet structure of BLE. In this paper, we propose a truly unsupervised approach for channel-annotation of RSSI data received by a stationary receiver object. Given a sequence of RSSI observations and a discoverable receiver channel-switching policy, we determine the period and hence the time spent by the receiver in an individual channel. Then, we propose a sliding-window based algorithm which utilizes two well-established Likelihood-Ratio algorithms - KLIEP and uLSIF - for extracting Channel State Information of retrospective RSSI observation data. We believe this work lays the foundation of motivating future work in completely unsupervised methods for object-to-object ranging and localization.

Rahul Majethia

Papers

Moving Beyond Market Research: Demystifying Smartphone User Behavior in India

Contextual sensitivity of the ambient temperature sensor in Smartphones

Smartphone-based Qualitative Analyses of Social Activities During Family Time

PeopleSave: Recommending effective drugs through web crowdsourcing

Mining channel state information from bluetooth low energy RSSI for robust object-to-object ranging