Nearby Smartphones Research Articles

Addressing out-of-hospital cardiac arrest with current technology advances: Breaking the deadlock with a mobile network.

Out-of-hospital cardiac arrest (OHCA) is a global public health problem, with survival rates remaining low at around 10% or less despite widespread cardiopulmonary resuscitation (CPR) training and availability of automated external defibrillators (AEDs). This is partly due to the challenges of knowing when and where a sudden OHCA occurs and where the nearest AED is located. In response, countries around the world have begun to use network technology-based smartphone applications. These applications are activated by emergency medical service dispatchers and alert preregistered volunteer first responders (VFRs) to nearby OHCAs using Global Positioning System localization. Accumulating evidence, although mostly from observational studies, shows their effectiveness in increasing the rate of bystander CPR, defibrillation, and patient survival. Current guidelines recommend the use of these VFR alerting systems, and the results of ongoing randomized trials are awaited for further dissemination. This article also proposed the concept of a life-saving mobile network (LMN), which uses opportunistic network and wireless sensor network technologies to create a dynamic mesh network of potential victims, rescuers, and defibrillators. The LMN works by detecting a fatal arrhythmia with a wearable sensor device, localizing the victim and the nearest AED with nearby smartphones, and notifying VFRs through peer-to-peer communication. While there are challenges and limitations to implementing the LMN in society, this innovative network technology would reduce the tragedy of sudden cardiac death from OHCA.

Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts.

How likely is it to become infected by SARS-CoV-2 after being exposed? Almost everyone wondered about this question during the COVID-19 pandemic. Contact-tracing apps1,2 recorded measurements of proximity3 and duration between nearby smartphones. Contacts-individuals exposed to confirmed cases-were notified according to public health policies such as the 2 m, 15 min guideline4,5, despite limited evidence supporting this threshold. Here we analysed 7 million contacts notified by the National Health Service COVID-19 app6,7 in England and Wales to infer how app measurements translated to actual transmissions. Empirical metrics and statistical modelling showed a strong relation between app-computed risk scores and actual transmission probability. Longer exposures at greater distances had risk similar to that of shorter exposures at closer distances. The probability of transmission confirmed by a reported positive test increased initially linearly with duration of exposure (1.1% per hour) and continued increasing over several days. Whereas most exposures were short (median 0.7 h, interquartile range 0.4-1.6), transmissions typically resulted from exposures lasting between 1 h and several days (median 6 h, interquartile range 1.4-28). Households accounted for about 6% of contacts but 40% of transmissions. With sufficient preparation, privacy-preserving yet precise analyses of risk that would inform public health measures, based on digital contact tracing, could be performed within weeks of the emergence of a new pathogen.

What Happens to COVID-19 Data After the Pandemic? Socio-Technical Lessons

The COVID-19 global pandemic outbreak meant a complete reevaluation of societal interactions, business processes, and government policies. For decades, the scientific and technical communities had contemplated the possibility of an all-out air-borne virus and had postulated how technology might be used in response, for example, in the reduction of transmission rates. In this paper, we examine the Australian COVID-19 technological response, focused initially on using a contact tracing app that would continually be broadcasting for known recorded cases, one nearby smartphone to another, and to the successive deployment of a QR-code-based solution requiring checking in and checking out of a place of congregation, like a closed or open campus setting. Despite the lackluster outcomes of the high-fidelity solutions, government continued, and in some instances, persisted in relying on QR codes for a considerable period. These solutions necessitated the collection of data pertaining to an individual for functioning, prompting a series of questions regarding the collection, storage, dissemination, and use of this data, both at the height of the pandemic and presently. On reflection, was the data effectively used or integrated into the proposed processes? Could the data be utilized in an unauthorized manner? And how might we circumvent its unauthorized use moving forward? Are there any potentially positive use cases that we could envisage? And, significantly, in the context of this piece, what are the broader socio-technical lessons or learnings that could be derived from such implementations that can be reinstituted into the design of future health-oriented systems? This paper provides an overview of Australia’s contact tracing app, from here on referred to as COVIDSafe, and the subsequent use of QR Codes that were state based and governed by the Services arm of the Australian Government, to present design insights relevant to both the Australian context and beyond.

Re-invigorating the photo album: augmenting printed photobooks with digital media

The photo album emerged in the late 1800s as place to collect portrait photos of visitors to a home, and was later appropriated by Kodak as a visual chronology of family history. With digital photography, the album has largely been replaced by online repositories of images shared on social media, and the selective printing of photobooks. In this paper, we present a ‘next-generation paper’ authoring system for annotating photobooks with multimedia content viewed on a nearby smartphone. We also report the results of a trial of this system, by nine travellers who used it to make augmented photobooks following a trip. These findings show that the augmented physical-and-digital photobook can heighten awareness of the multisensory aspects of travel, enrich memories, and enhance social interaction around photos. The social and technical implications for the future of the photo album are discussed.

Practical implementation of remote continuous glucose monitoring in hospitalized patients with diabetes.

PurposeInpatient diabetes management involves frequent assessment of glucose levels for treatment decisions. Here we describe a program for inpatient real-time continuous glucose monitoring (rtCGM) at a community hospital and the accuracy of rtCGM-based glucose estimates.MethodsAdult inpatients with preexisting diabetes managed with intensive insulin therapy and a diagnosis of coronavirus disease 2019 (COVID-19) were monitored via rtCGM for safety. An rtCGM system transmitted glucose concentration and trending information at 5-minute intervals to nearby smartphones, which relayed the data to a centralized monitoring station. Hypoglycemia alerts were triggered by rtCGM values of ≤85 mg/dL, but rtCGM data were otherwise not used in management decisions; insulin dosing adjustments were based on blood glucose values measured via fingerstick blood sampling. Accuracy was evaluated retrospectively by comparing rtCGM values to contemporaneous point-of-care (POC) blood glucose values.ResultsA total of 238 pairs of rtCGM and POC data points from 10 patients showed an overall mean absolute relative difference (MARD) of 10.3%. Clarke error grid analysis showed 99.2% of points in the clinically acceptable range, and surveillance error grid analysis showed 89.1% of points in the lowest risk category. It was determined that for 25% of the rtCGM values, discordances in rtCGM and POC values would likely have resulted in different insulin doses. Insulin dose recommendations based on rtCGM values differed by 1 to 3 units from POC-based recommendations.ConclusionrtCGM for inpatient diabetes monitoring is feasible. Evaluation of individual rtCGM-POC paired values suggested that using rtCGM data for management decisions poses minimal risks to patients. Further studies to establish the safety and cost implications of using rtCGM data for inpatient diabetes management decisions are warranted.

Bluetooth Low Energy Beacon Sensors to Document Handheld Magnifier Use at Home by People with Low Vision.

We explored the feasibility of using Bluetooth low energy (BLE) beacon sensors to determine when individuals with low vision (LV) use handheld magnifiers at home. Knowing the frequency and duration of magnifier use would be helpful to document increased magnifier use after successful rehabilitation training, or conversely, to know when someone has abandoned a magnifier and requires assistance. Estimote Sticker BLE beacon sensors were attached to the handles of optical handheld magnifiers and dispensed to eight LV subjects to use at home. Temperature and motion data from the BLE beacon sensors were collected every second by a custom mobile application on a nearby smartphone and transmitted to a secure database server. Subjects noted the date and start/end times of their magnifier use in a diary log. Each of the 99 diary-logged self-reports of magnifier use across subjects was associated with BLE beacon sensor recordings of motion (mean 407 instances; SD 365) and increased temperature (mean 0.20 °C per minute; SD 0.16 °C) (mean total magnitude 5.4 °C; SD 2.6 °C). Diary-logged duration of magnifier use (mean 42 min; SD 24) was significantly correlated with instances of motion (p < 0.001) and rate of temperature increase (p < 0.001) recorded by the BLE beacon sensors. The BLE beacon sensors reliably detected meaningfully increased temperature, coupled with numerous instances of motion, when magnifiers were used for typical reading tasks at home by people with LV.

Forecasting Crowd Counts With Wi-Fi Systems: Univariate, Non-Seasonal Models

Recently, event organizers and researchers have advocated the development of novel technologies supporting crowd control, notably for public events. This paper presents a crowd monitoring system based on probe requests (PRs), which are Wi-Fi packets smartphones send periodically. By estimating the global rate at which nearby smartphones send PRs, Wi-Fi sensors can estimate crowd counts. The core contribution of this paper is a computationally tractable method that forecasts crowd counts up to thirty minutes in the future, with forecasts becoming available as soon as two hours of data are available. The forecasting method relies on autoregressive integrated moving average (ARIMA) models. Contributions also include two methods that compute prediction intervals associated with the forecasts, one of which is based upon generalized autoregressive conditional heteroskedasticity (GARCH) models. Recent real-world data from Winter Wonders 2018/2019 (an event that took place in Brussels, Belgium) notably demonstrate that the proposed forecasting method outperforms its immediate variations as well as baseline models (i.e., random walk models).

Exfiltrating data from air-gapped computers via ViBrAtIoNs

Air-gap covert channels are special types of covert communication channels that enable attackers to exfiltrate data from isolated, network-less computers. Various types of air-gap covert channels have been demonstrated over the years, including electromagnetic, magnetic, acoustic, optical, and thermal.In this paper, we introduce a new type of vibrational (seismic) covert channel. We observe that computers vibrate at a frequency correlated to the rotation speed of their internal fans. These inaudible vibrations affect the entire structure on which the computer is placed. Our method is based on malware’s capability of controlling the vibrations generated by a computer, by regulating its internal fan speeds. We show that the malware-generated covert vibrations can be sensed by nearby smartphones via the integrated, sensitive accelerometers. Notably, the accelerometer sensors in smartphones can be accessed by any app without requiring the user permissions, which make this attack highly evasive. We implemented AiR-ViBeR, malware that encodes binary information, and modulate it over a low frequency vibrational carrier. The data is then decoded by malicious application on a smartphone placed on the same surface of the air-gapped computer (e.g., on a desk). We discuss the attack model, provide technical background, and present the implementation details and evaluation results. Our results show that using AiR-ViBeR, data can be exfiltrated from air-gapped computer to a nearby smartphone on the same table, or even an adjacent table, via vibrations. Finally, we propose a set of countermeasures for this new type of attack.

Textile-based wearable solid-contact flexible fluoride sensor: Toward biodetection of G-type nerve agents

Rising global concerns posed by chemical and biological threat agents highlight the critical need to develop reliable strategies for the real-time detection of such threats. While wearable sensing technology is well suited to fulfill this task, the use of on-body devices for rapid and selective field identification of chemical agents is relatively a new area. This work describes a flexible printed textile-based solid-contact potentiometric sensor for the selective detection of fluoride anions liberated by the biocatalytic hydrolysis of fluorine-containing G-type nerve agents (such as sarin or soman). The newly developed solid-contact textile fluoride sensor relies on a fluoride-selective bis(fluorodioctylstannyl)methane ionophore to provide attractive analytical performance with near-Nernstian sensitivity and effective discrimination against common anions, along with excellent reversibility and repeatability for dynamically changing fluoride concentrations. By using stress-enduring printed inks and serpentine structures along with stretchable textile substrates, the resulting textile-based fluoride sensor exhibits robust mechanical resiliency under severe mechanical strains. Such realization of an effective textile-based fluoride-selective electrode allowed biosensing of the nerve-agent simulant diisopropyl fluorophosphate (DFP), in connection to immobilized organophosphorus acid anhydrolylase (OPAA) or organophosphorus hydrolase (OPH) enzymes. A user-friendly portable electronic module transmits data from the new textile-based potentiometric biosensor wirelessly to a nearby smartphone for alerting the wearer instantaneously about potential chemical threats. While expanding the scope of wearable solid-contact anion sensors, such a textile-based potentiometric fluoride electrode transducer offers particular promise for effective discrimination of G-type neurotoxins from organophosphate (OP) pesticides, toward specific field detection of these agents in diverse defense settings.

MAGNETO: Covert channel between air-gapped systems and nearby smartphones via CPU-generated magnetic fields

This papers shows that attackers can leak data from isolated, air-gapped computers to nearby smartphones via covert magnetic signals. The proposed covert channel works even if a smartphone is kept inside a Faraday shielding case, which aims to block any type of inbound and outbound wireless communication (Wi-Fi, cellular, Bluetooth, etc.). Malware is implemented to control the magnetic fields emanating from the computer by regulating workloads on the CPU cores. Sensitive data such as encryption keys, passwords, or keylogging data is encoded and transmitted over the magnetic signals. A smartphone located near the computer receives the covert signals with its magnetic sensor. I present technical background, discuss signal generation, data encoding, and signal reception. The proposed covert channel works from a user-level process, without requiring special privileges, and can successfully operate from within an isolated virtual machine (VM).

SmartDR:A device-to-device communication for post-disaster recovery

Natural disasters, such as earthquakes, can cause severe destruction and create havoc in the society. Buildings and other structures may collapse during disaster incidents causing injuries and deaths to victims trapped under debris and rubble. Immediately after a natural disaster incident, it becomes extremely difficult for first responders and rescuers to find and save trapped victims. Often searches are carried out blindly in random locations, which delay the rescue of the victims. This paper introduces a Smartphone Assisted Disaster Recovery (SmartDR) method for post-disaster communication using Smartphones. SmartDR utilizes the device-to-device (D2D) communication technology in Fifth Generation (5G) networks, which enables direct communication between proximate devices without the need of relaying through a network infrastructure, such as mobile access points or mobile base stations. We examine a scenario of multi-hop D2D communication where smartphones carried by trapped victims and other people in disaster affected areas can self-detect the occurrence of a disaster incident by monitoring the radio environment and then can self-switch to a disaster mode to transmit emergency help messages with their location coordinates to other nearby smartphones. To locate other nearby smartphones also operating in the disaster mode and in the same channel, each smartphone runs a rendezvous process. The emergency messages are thus relayed to the functional base station or rescue centre. To facilitate routing of the emergency messages, we propose a path selection algorithm, which considers both delay and the leftover energy of a device (a smartphone in this case). Thus, the SmartDR method includes: (i) a multi-channel channel hopping rendezvous protocol to improve the victim localization or neighbour discovery, and (ii) an energy-aware multi-path routing (Energy-aware ad-hoc on-demand distance vector or E-AODV) protocol to overcome the higher energy depletion rate at devices associated with single shortest path routing. The SmartDR method can guide search and rescue operations and increase the possibility of saving lives immediately aftermath a disaster incident. A simulation-based performance study is conducted to evaluate the protocol performance in post-disaster scenario. Simulation results show that a significant performance gain is achievable when a device utilizes the channel information for the rendezvous process and the leftover energy for routing path selection. Our results show that peer discovery in multi-channel D2D environment can be significantly improved when channel quality information is considered in CH sequence design. Moreover, selecting a routing path based on LoE of a device and the standard deviation of residual energy of a path, can not only enhance the network lifetime, but also reduce the chance of network being partitioned.

EDirect: Energy-Efficient D2D-Assisted Relaying Framework for Cellular Signaling Reduction

Mobile Instant Messaging (IM) apps, such as WhatsApp and WeChat, frequently send heartbeat messages to remote servers to maintain their always-online status. Periodic heartbeat messages are small in size, but their transmissions incur heavy signaling traffic due to frequently establishing and releasing communication channels between Base Stations (BSs) and smartphones, known as the signaling storm. Meanwhile, smartphones also need to activate the cellular data communication module frequently for transmitting short heartbeat messages, resulting in substantial energy consumption. To address these issues, we present eDirect, an energy-efficient D2D-assIsted Relaying framEwork for Cellular signaling reducTion. eDirect selects active smartphones as relays to opportunistically collect heartbeat messages from nearby smartphones using energy-efficient D2D communication. The collected heartbeat messages are transmitted to the BS in an aggregated manner to reduce cellular signaling traffic. Based on the beating frequencies and deadlines of the collected heartbeat messages, eDirect schedules transmissions of the collected heartbeat messages to minimize signaling overhead and energy consumption while meeting the deadline constraints. We implement and evaluate our solution on Android smartphones. The results from real-world experiments show that our solution reduces signaling traffic by at least 50% and energy consumption by up to 36%.

UbiquiTouch

We present UbiquiTouch, an ultra low power wireless touch interface. With an average power consumption of 30.91μW, UbiquiTouch can run on energy harvested from ambient light. It achieves this performance through low power touch sensing and passive communication to a nearby smartphone using ambient FM backscatter. This approach allows UbiquiTouch to be deployed in mobile situations both in indoor and outdoor locations, without the need for any additional infrastructure for operation. To demonstrate the potential of this technology, we evaluate it in several different and realistic scenarios. Finally, we address the future application space for this technology.

Fansmitter: Acoustic data exfiltration from air-Gapped computers via fans noise

Computers that contain sensitive information are often maintained in air-gapped isolation. In this defensive measure, a computer is disconnected from the Internet - logically and physically - preventing accidental or intentional leakage of sensitive information outward. In recent years it has been shown that malware can leak data over an air-gap by transmitting sonic and ultrasonic signals from a computer speaker. In order to eliminate such acoustic covert channels, current best practice recommends the elimination of speakers in secured computers, thereby creating a so-called ‘audio-gapped’ system.In this paper, we present ‘Fansmitter,’ a malware that can acoustically exfiltrate data from air-gapped computers, even when audio hardware and speakers are not present. Our method utilizes the noise emitted from the CPU, GPU, and chassis fans. We show that a software can regulate the internal fans’ rotation speed in order to control their acoustic signal, known as blade pass frequency (BPF). Binary data can be modulated and transmitted over these audio signals to a remote microphone (e.g., a nearby smartphone). We present design considerations, including acoustic waveform analysis, data modulation and demodulation, and data transmission and reception. We evaluate the acoustic covert channel with various fans at different distances and present the results. We also discuss issues such as stealth, interference, and countermeasures. Using our method we successfully transmitted data from audio-less, air-gapped computers, to a mobile phone in the same room. We demonstrated an effective transmission at distances of 1–8 m, with a maximum bit rate of 60 bit/min per fan.

An Online Incentive Mechanism for Collaborative Task Offloading in Mobile Edge Computing

This paper discusses incentive mechanism design for collaborative task offloading in mobile edge computing (MEC). Different from most existing work in the literature that was based on offline settings, in this paper, an online truthful mechanism integrating computation and communication resource allocation is proposed. In our system model, upon the arrival of a smartphone user who requests task offloading, the base station (BS) needs to make a decision right away without knowing any future information on i) whether to accept or reject this task offloading request and ii) if accepted, who to execute the task (the BS itself or nearby smartphone users called collaborators). By considering each task’s specific requirements in terms of data size, delay, and preference, we formulate a social-welfare-maximization problem, which integrates collaborator selection, communication and computation resource allocation, transmission and computation time scheduling, as well as pricing policy design. To solve this complicated problem, a novel online mechanism is proposed based on the primal-dual optimization framework. Theoretical analyses show that our mechanism can guarantee feasibility, truthfulness, and computational efficiency (competitive ratio of 3). We further use comprehensive simulations to validate our analyses and the properties of our proposed mechanism.

VTracer: When Online Vehicle Trajectory Compression Meets Mobile Edge Computing

Vehicles can be easily tracked due to the proliferation of vehicle-mounted global positioning system (GPS) devices. ${\sf VTracer}$ is a cost-effective mobile system for online trajectory compression and tracing vehicles, taking the streaming GPS data as inputs. Online trajectory compression, which seeks a concise and (near) spatial-lossless data representation before revealing the next vehicle’s GPS position, is gradually becoming a promising way to alleviate burdens such as communication bandwidth, storing, and cloud computing. In general, an accurate online map-matcher is a prerequisite. This two-phase approach is nontrivial because we need to overcome the essential contradiction caused by the resource-constrained GPS devices and the heavy computation tasks. ${\sf VTracer}$ meets the challenge by leveraging the idea of mobile edge computing. More specifically, we offload the heavy computation tasks to the nearby smartphones of drivers (i.e., smartphones play the role of cloudlets), which are almost idle during driving. More importantly, they have relatively more powerful computing capacity. We have implemented ${\sf VTracer}$ on the Android platform and evaluate it based on a real driving trace dataset generated in the city of Chongqing, China. Experimental results demonstrate that ${\sf VTracer}$ achieves the excellent performance in terms of matching accuracy, compression ratio, and it also costs the acceptable memory, energy, and app size.

Event-Triggered Ephemeral Group Communication and Coordination over Sound for Smart Consumer Devices.

Voice-based interfaces have become one of the most popular device capabilities, recently being regarded as one flagship user experience of smart consumer devices. However, the lack of common coordination mechanisms might often degrade the user experience, especially when interacting with multiple voice-enabled devices located closely. For example, a hotword or wake-up utterance such as “hi Bixby” or “ok Google” frequently triggers redundant responses by several nearby smartphones. Motivated by the problem of uncoordinated react of voice-enabled devices especially in a multiple device environment, in this paper, we discuss the notion of an ephemeral group of consumer devices in which the member devices and the transient lifetime are implicitly determined by an external event (e.g., hotword detection) without any provisioned group structure, and specifically we concentrate on the time-constrained leader election process in such an ephemeral group. To do so: (i) We first present the sound-based multiple device communication framework, namely tailtag, that leverages the isomorphic capability of consumer devices for the tasks of processing hotword events and transmitting data over sound, and thus renders both the tasks confined to the same room area and enables the spontaneous leader election process in a unstructured group upon a hotword event. (ii) To improve the success rate of the leader election with a given time constraint, we then develop the adaptive messaging scheme especially tailored for sound-based data communication that inherently has low data rate. Our adaptive scheme utilizes an application-specific score that is individually calculated by a member device for each event detection, and employs score-based scheduling by which messages of a high score are scheduled first and so unnecessary message transmission can be suppressed during the election process. (iii) Through experiments, we also demonstrate that, when a hotword is detected by multiple smartphones in a room, the framework with the adaptive messaging scheme enables them to successfully achieve a coordinated response under the given latency bound, yielding an insignificant non-consensus probability, no more than 2%.

The Cornwall a-book: An Augmented Travel Guide Using Next Generation Paper

Electronic publishing usually presents readers with book or e-book options for reading on paper or screen. In this paper, we introduce a third method of reading on paper-and-screen through the use of an augmented book (‘a-book’) with printed hotlinks than can be viewed on a nearby smartphone or other device. Two experimental versions of an augmented guide to Cornwall are shown using either optically recognised pages or embedded electronics making the book sensitive to light and touch. We refer to these as second generation (2G) and third generation (3G) paper respectively. A common architectural framework, authoring workflow and interaction model is used for both technologies, enabling the creation of two future generations of augmented books with interactive features and content. In the travel domain we use these features creatively to illustrate the printed book with local multimedia and updatable web media, to point to the printed pages from the digital content, and to record personal and web media into the book.

Android smartphones network implementation in the absence of internet

AbstractIn this paper, Mobile Delay Tolerant Network service is implemented in Android application that allows the use of smartphones for broadcasting messages to nearby smartphones without Internet. A simple experiment is carried out with simple facilities and one type of routing protocols. This is implemented with only one router and eleven smartphones.

&lt;italic&gt;Outlet&lt;/italic&gt;: Outsourcing Wearable Computing to the Ambient Mobile Computing Edge

Wearable devices, e.g., smart glass and watch, could achieve fine-grained human-centric sensing nowadays, but still lack sufficient capacities to execute sophisticated data processing algorithms. This paper presents Outlet to explore the feasibility to leverage the available computing resources from user’s ambience, e.g., from nearby smart phones, tablets, computers, Wi-Fi APs, and so on, to form a mobile computing edge. We can then outsource wearable computing tasks to this ambient edge to locally digest the sensory data for prompt user feedback and reaction, as it is perfectly located in user’s vicinity. The Outlet design avoids the traditional offloading to the remote clouds, whose performance may highly depend on the high-speed Internet connectivity and availability. To enable the Outlet design, we identify three major challenges: context dependence, scattered resources, and resource dynamics, and propose a series of key techniques to address each of them. To examine Outlet ’s performance, we conduct extensive trace-driven evaluations and the results indicate promising performance achieved by Outlet , e.g., mostly within 97.6% to 99.5% closeness of the optimal performance and always outperforming the baseline approach under various system settings.