3,504 research outputs found
Implementation and Evaluation of a Cooperative Vehicle-to-Pedestrian Safety Application
While the development of Vehicle-to-Vehicle (V2V) safety applications based
on Dedicated Short-Range Communications (DSRC) has been extensively undergoing
standardization for more than a decade, such applications are extremely missing
for Vulnerable Road Users (VRUs). Nonexistence of collaborative systems between
VRUs and vehicles was the main reason for this lack of attention. Recent
developments in Wi-Fi Direct and DSRC-enabled smartphones are changing this
perspective. Leveraging the existing V2V platforms, we propose a new framework
using a DSRC-enabled smartphone to extend safety benefits to VRUs. The
interoperability of applications between vehicles and portable DSRC enabled
devices is achieved through the SAE J2735 Personal Safety Message (PSM).
However, considering the fact that VRU movement dynamics, response times, and
crash scenarios are fundamentally different from vehicles, a specific framework
should be designed for VRU safety applications to study their performance. In
this article, we first propose an end-to-end Vehicle-to-Pedestrian (V2P)
framework to provide situational awareness and hazard detection based on the
most common and injury-prone crash scenarios. The details of our VRU safety
module, including target classification and collision detection algorithms, are
explained next. Furthermore, we propose and evaluate a mitigating solution for
congestion and power consumption issues in such systems. Finally, the whole
system is implemented and analyzed for realistic crash scenarios
Communication System For Firefighters
Currently firefighters use two-way radios to communicate on the job, and they are forced to write reports based on their memory because there is not an easy way to record the communications between two-way radios. Firefighters need a system to automatically document what happened while they were responding to a call. To save them a significant amount of time when creating reports, our solution is to implement an application that allows firefighters to take pictures, record video and communicate in real time with their team of on-site responders. The proposed system will use a Wireless Local Area Network (WLAN) hosted on the fire truck itself to act as an access point (AP) to which the firefighters can connect. This AP will also save communication between firefighters to a local storage location. Upon return to the fire station, the AP will route all of the information stored locally to a larger database. For now, Wi-Fi will be our communication medium, with a prediction that our technology can eventually be extended to include radio signal
Accurate acoustic ranging system using android smartphones
ACCURATE ACOUSTIC RANGING SYSTEM USING ANDROID SMARTPHONES
By Mohammadbagher Fotouhi, Master of Science
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University
Virginia Commonwealth University 2017
Major Director: Dr. Ruixin Niu, Associate Professor of Department of Electrical and Computer Engineering
In this thesis, we present the design, implementation, and evaluation of an android ranging system, a high-accuracy acoustic-based ranging system which allows two android mobile phones to learn their physical distance from each other.
In this system we propose a practical solution for accurate ranging based on acoustic communication between speakers and microphones on two smartphones. Using the audible-band acoustic signal with the Wi-Fi assistance without the sound disturbance is promising for large deployment. Our method is a pure software-based solution and uses only the most basic set of commodity hardware: a speaker, a microphone, and Wi-Fi communication. So it is readily applicable to many commercial-off-the-shelf mobile devices like cell phones.
Our system is the result of several design goals, including user privacy, decentralized administration, and low cost. Rather than relying on any centralized management which tracks the user’s location to help them find their distance, our system helps devices learn their distance from each other without advertising their location information with any centralized management.
Compared to alternatives that require special-purpose hardware or pre-existence of precision location infrastructure , our system is applicable on most of off-the-shelf components so it is a commodity-based solution will obviously have wider applications and is cost effective.
Currently, two smartphones are used to estimate the distance between them through Wi-Fi and audio communications. The basic idea is estimating the distance between two phones by estimating the traveling time of audio signal from one phone to the other as the speed of sound is known. The preliminary results of ranging demonstrate that our algorithm could achieve high accuracy, and stable and reliable results for real time smartphone-based indoor ranging
An Indoor Navigation System Using a Sensor Fusion Scheme on Android Platform
With the development of wireless communication networks, smart phones have become a necessity for people’s daily lives, and they meet not only the needs of basic functions for users such as sending a message or making a phone call, but also the users’ demands for entertainment, surfing the Internet and socializing. Navigation functions have been commonly utilized, however the navigation function is often based on GPS (Global Positioning System) in outdoor environments, whereas a number of applications need to navigate indoors. This paper presents a system to achieve high accurate indoor navigation based on Android platform. To do this, we design a sensor fusion scheme for our system. We divide the system into three main modules: distance measurement module, orientation detection module and position update module. We use an efficient way to estimate the stride length and use step sensor to count steps in distance measurement module. For orientation detection module, in order to get the optimal result of orientation, we then introduce Kalman filter to de-noise the data collected from different sensors. In the last module, we combine the data from the previous modules and calculate the current location. Results of experiments show that our system works well and has high accuracy in indoor situations
Distributed and adaptive location identification system for mobile devices
Indoor location identification and navigation need to be as simple, seamless,
and ubiquitous as its outdoor GPS-based counterpart is. It would be of great
convenience to the mobile user to be able to continue navigating seamlessly as
he or she moves from a GPS-clear outdoor environment into an indoor environment
or a GPS-obstructed outdoor environment such as a tunnel or forest. Existing
infrastructure-based indoor localization systems lack such capability, on top
of potentially facing several critical technical challenges such as increased
cost of installation, centralization, lack of reliability, poor localization
accuracy, poor adaptation to the dynamics of the surrounding environment,
latency, system-level and computational complexities, repetitive
labor-intensive parameter tuning, and user privacy. To this end, this paper
presents a novel mechanism with the potential to overcome most (if not all) of
the abovementioned challenges. The proposed mechanism is simple, distributed,
adaptive, collaborative, and cost-effective. Based on the proposed algorithm, a
mobile blind device can potentially utilize, as GPS-like reference nodes,
either in-range location-aware compatible mobile devices or preinstalled
low-cost infrastructure-less location-aware beacon nodes. The proposed approach
is model-based and calibration-free that uses the received signal strength to
periodically and collaboratively measure and update the radio frequency
characteristics of the operating environment to estimate the distances to the
reference nodes. Trilateration is then used by the blind device to identify its
own location, similar to that used in the GPS-based system. Simulation and
empirical testing ascertained that the proposed approach can potentially be the
core of future indoor and GPS-obstructed environments
Situational Awareness Enhancement for Connected and Automated Vehicle Systems
Recent developments in the area of Connected and Automated Vehicles (CAVs) have boosted the interest in Intelligent Transportation Systems (ITSs). While ITS is intended to resolve and mitigate serious traffic issues such as passenger and pedestrian fatalities, accidents, and traffic congestion; these goals are only achievable by vehicles that are fully aware of their situation and surroundings in real-time. Therefore, connected and automated vehicle systems heavily rely on communication technologies to create a real-time map of their surrounding environment and extend their range of situational awareness. In this dissertation, we propose novel approaches to enhance situational awareness, its applications, and effective sharing of information among vehicles.;The communication technology for CAVs is known as vehicle-to-everything (V2x) communication, in which vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) have been targeted for the first round of deployment based on dedicated short-range communication (DSRC) devices for vehicles and road-side transportation infrastructures. Wireless communication among these entities creates self-organizing networks, known as Vehicular Ad-hoc Networks (VANETs). Due to the mobile, rapidly changing, and intrinsically error-prone nature of VANETs, traditional network architectures are generally unsatisfactory to address VANETs fundamental performance requirements. Therefore, we first investigate imperfections of the vehicular communication channel and propose a new modeling scheme for large-scale and small-scale components of the communication channel in dense vehicular networks. Subsequently, we introduce an innovative method for a joint modeling of the situational awareness and networking components of CAVs in a single framework. Based on these two models, we propose a novel network-aware broadcast protocol for fast broadcasting of information over multiple hops to extend the range of situational awareness. Afterward, motivated by the most common and injury-prone pedestrian crash scenarios, we extend our work by proposing an end-to-end Vehicle-to-Pedestrian (V2P) framework to provide situational awareness and hazard detection for vulnerable road users. Finally, as humans are the most spontaneous and influential entity for transportation systems, we design a learning-based driver behavior model and integrate it into our situational awareness component. Consequently, higher accuracy of situational awareness and overall system performance are achieved by exchange of more useful information
Google Play apps ERM: (energy rating model) multi-criteria evaluation model to generate tentative energy ratings for Google Play store apps
A common issue that is shared among Android smartphones users was and still related to saving their batteries power and to avoid the need of using any recharging resources. The tremendous increase in smartphone usage is clearly accompanied by an increase in the need for more energy. This preoperational relationship between modern technology and energy generates energy-greedy apps, and therefore power-hungry end users. With many apps falling under the same category in an app store, these apps usually share similar functionality. Because developers follow different design and development schools, each app has its own energy-consumption habits. Since apps share similar features, an end-user with limited access to recharging resources would prefer an energy-friendly app rather than a popular energy-greedy app. However, app stores give no indication about the energy behaviour of the apps they offer, which causes users to randomly choose apps without understanding their energy-consumption behaviour. Furthermore, with regard to the research questions about the fact that power saving application consumes a lot of electricity, past studies clearly indicate that there is a lot of battery depletion due to several factors. This problem has become a major concern for smartphone users and manufacturers. The main contribution of our research is to design a tool that can act as an effective decision support factor for end users to have an initial indication of the energy-consumption behaviour of an application before installing it. The core idea of the “before-installation” philosophy is simplified by the contradicting concept of installing the app and then having it monitored and optimized. Since processing requires power, avoiding the consumption of some power in order to conserve a larger amount of power should be our priority. So instead, we propose a preventive strategy that requires no processing on any layer of the smartphone. To address this issue, we propose a star-rating evaluation model (SREM), an approach that generates a tentative energy rating label for each app. To that end, SREM adapts current energy-aware refactoring tools to demonstrate the level of energy consumption of an app and presents it in a star-rating schema similar to the Ecolabels used on electrical home appliances.
The SREM will also inspire developers and app providers to come up with multiple energy-greedy versions of the same app in order to suit the needs of different categories of users and rate their own apps.
We proposed adding SREM to Google Play store in order to generate the energy-efficiency label for each app which will act as a guide for both end users and developers without running any processes on the end-users smartphone. Our research also reviews relevant existing literature specifically those covering various energy-saving techniques and tools proposed by various authors for Android smartphones. A secondary analysis has been done by evaluating the past research papers and surveys that has been done to assess the perception of the users regarding the phone power from their battery. In addition, the research highlights an issue that the notifications regarding the power saving shown on the screen seems to exploit a lot of battery. Therefore, this study has been done to reflect the ways that could help the users to save the phone battery without using any power from the same battery in an efficient manner. The research offers an insight into new ways that could be used to more effectively conserve smartphone energy, proposing a framework that involves end users on the process.Um problema comum entre utilizadores de smartphones Android tem sido a necessidade de economizar a energia das baterias, de modo a evitar a utilização de recursos de recarga. O aumento significativo no uso de smartphones tem sido acompanhado por um aumento, tambĂ©m significativo, na necessidade de mais energia. Esta relação operacional entre tecnologia moderna e energia gera aplicações muito exigentes no seu consumo de energia e, portanto, perfis de utilizadores que requerem nĂveis de energia crescentes. Com muitos das aplicações que se enquadram numa mesma categoria da loja de aplicações (Google Store), essas aplicações geralmente tambĂ©m partilham funcionalidades semelhantes. Como os criadores destas aplicações seguem abordagens diferentes de diversas escolas de design e desenvolvimento, cada aplicação possui as suas prĂłprias caraterĂsticas de consumo de energia. Como as aplicações partilham recursos semelhantes, um utilizador final com acesso limitado a recursos de recarga prefere uma aplicação que consome menos energia do que uma aplicação mais exigente em termos de consumo energĂ©tico, ainda que seja popular. No entanto, as lojas de aplicações nĂŁo fornecem uma indicação sobre o comportamento energĂ©tico das aplicações oferecidas, o que faz com que os utilizadores escolham aleatoriamente as suas aplicações sem entenderem o correspondente comportamento de consumo de energia. Adicionalmente, no que diz respeito Ă questĂŁo de investigação, a solução de uma aplicação de economia de energia consume muita eletricidade, o que a torna limitada; estudos anteriores indicam claramente que há muita perda de bateria devido a vários fatores, nĂŁo constituindo solução para muitos utilizadores e para os fabricantes de smartphones. A principal contribuição de nossa pesquisa Ă© projetar uma ferramenta que possa atuar como um fator de suporte Ă decisĂŁo eficaz para que os utilizadores finais tenham uma indicação inicial do comportamento de consumo de energia de uma aplicação, antes de a instalar. A ideia central da filosofia proposta Ă© a de atuar "antes da instalação", evitando assim a situação em se instala uma aplicação para perceber Ă posteriori o seu impacto no consumo energĂ©tico e depois ter que o monitorizar e otimizar (talvez ainda recorrendo a uma aplicação de monitorização do consumo da bateria, o que agrava ainda mais o consumo energĂ©tico). Assim, como o processamento requer energia, Ă© nossa prioridade evitar o consumo de alguma energia para conservar uma quantidade maior de energia. Portanto, Ă© proposta uma estratĂ©gia preventiva que nĂŁo requer processamento em nenhuma camada do smartphone.
Para resolver este problema, Ă© proposto um modelo de avaliação por classificação baseado em nĂveis e identificado por estrelas (SREM). Esta abordagem gera uma etiqueta de classificação energĂ©tica provisĂłria para cada aplicação. Para isso, o SREM adapta as atuais ferramentas de refatoração com reconhecimento de energia para demonstrar o nĂvel de consumo de energia de uma aplicação, apresentando o resultado num esquema de classificação por estrelas semelhante ao dos rĂłtulos ecolĂłgicos usados em eletrodomĂ©sticos. O SREM tambĂ©m se propõe influenciar quem desenvolve e produz as aplicações, a criarem diferentes versões destas, com diferentes perfis de consumo energĂ©tico, de modo a atender Ă s necessidades de diferentes categorias de utilizadores e assim classificar as suas prĂłprias aplicações. Para avaliar a eficiĂŞncia do modelo como um complemento Ă s aplicações da loja Google Play, que atuam como uma rotulagem para orientação dos utilizadores finais. A investigação tambĂ©m analisa a literatura existente relevante, especificamente a que abrange as várias tĂ©cnicas e ferramentas de economia de energia, propostas para smartphones Android. Uma análise secundária foi ainda realizada, focando nos trabalhos de pesquisa que avaliam a perceção dos utilizadores em relação Ă energia do dispositivo, a partir da bateria. Em complemento, a pesquisa destaca um problema de que as notificações sobre a economia de energia mostradas na tela parecem explorar muita bateria. Este estudo permitiu refletir sobre as formas que podem auxiliar os utilizadores a economizar a bateria do telefone sem usar energia da mesma bateria e, mesmo assim, o poderem fazer de maneira eficiente. A pesquisa oferece uma visĂŁo global das alternativas que podem ser usadas para conservar com mais eficiĂŞncia a energia do smartphone, propondo um modelo que envolve os utilizadores finais no processo.Un problème frĂ©quent rencontrĂ© par les utilisateurs de smartphones Android a Ă©tĂ©, tout en l’étant toujours, d’économiser leur batterie et d’éviter la nĂ©cessitĂ© d’utiliser des ressources de recharge. La croissance considĂ©rable de l’utilisation des smartphones s’accompagne clairement d’une augmentation des besoins en Ă©nergie. Cette relation prĂ©opĂ©rationnelle entre la technologie moderne et l’énergie gĂ©nère des applications gourmandes en Ă©nergie, et donc des utilisateurs finaux qui le sont tout autant. De nombreuses applications relevant de la mĂŞme catĂ©gorie dans une boutique partagent gĂ©nĂ©ralement des fonctionnalitĂ©s similaires. Étant donnĂ© que les dĂ©veloppeurs adoptent diffĂ©rentes approches de conception et de dĂ©veloppement, chaque application a ses propres caractĂ©ristiques de consommation d’énergie. Comme les applications partagent des fonctionnalitĂ©s similaires, un utilisateur final disposant d’un accès limitĂ© aux ressources de recharge prĂ©fĂ©rerait une application Ă©coĂ©nergĂ©tique plutĂ´t qu’une autre gourmande en Ă©nergie. Cependant, les boutiques d’applications ne donnent aucune indication sur le comportement Ă©nergĂ©tique des applications qu’elles proposent, ce qui incite les utilisateurs Ă choisir des applications au hasard sans comprendre leurs caractĂ©ristiques en ce domaine. En outre, en ce qui concerne les questions de recherche sur le fait que les applications d’économie d’énergie consomment beaucoup d’électricitĂ©, des Ă©tudes antĂ©rieures indiquent clairement que la dĂ©charge d’une batterie est due Ă plusieurs facteurs. Ce problème est devenu une prĂ©occupation majeure pour les utilisateurs et les fabricants de smartphones. La principale contribution de notre Ă©tude est de concevoir un outil qui peut agir comme un facteur d’aide efficace Ă la dĂ©cision pour que les utilisateurs finaux aient une indication initiale du comportement de consommation d’énergie d’une application avant de l’installer. L’idĂ©e de base de la philosophie « avant l’installation » est simplifiĂ©e par le concept contradictoire d’installer l’application pour ensuite la contrĂ´ler et l’optimiser. Puisque les opĂ©rations de traitement exigent de l’énergie, Ă©viter la consommation d’une partie d’entre elles pour l’économiser devrait ĂŞtre notre prioritĂ©. Nous proposons donc une stratĂ©gie prĂ©ventive qui ne nĂ©cessite aucun traitement sur une couche quelconque du smartphone. Pour rĂ©soudre ce problème, nous proposons un modèle d’évaluation au moyen d’étoiles (star-rating evaluation model ou SREM), une approche qui gĂ©nère une note Ă©nergĂ©tique indicative pour chaque application. Ă€ cette fin, le SREM adapte les outils actuels de refactoring sensibles Ă l’énergie pour dĂ©montrer le niveau de consommation d’énergie d’une application et la prĂ©sente dans un schĂ©ma de classement par Ă©toiles similaire aux labels Ă©cologiques utilisĂ©s sur les appareils Ă©lectromĂ©nagers. Le SREM incitera Ă©galement les dĂ©veloppeurs et les fournisseurs d’applications Ă mettre au point plusieurs versions avides d’énergie d’une mĂŞme application afin de rĂ©pondre aux besoins des diffĂ©rentes catĂ©gories d’utilisateurs et d’évaluer leurs propres applications. Nous avons proposĂ© d’ajouter le SREM au Google Play Store afin de gĂ©nĂ©rer le label d’efficacitĂ© Ă©nergĂ©tique pour chaque application. Celui-ci servira de guide Ă la fois pour les utilisateurs finaux et les dĂ©veloppeurs sans exĂ©cuter de processus sur le smartphone des utilisateurs finaux. Notre recherche passe Ă©galement en revue la littĂ©rature existante pertinente, en particulier celle qui couvre divers outils et techniques d’économie d’énergie proposĂ©s par divers auteurs pour les smartphones Android. Une analyse secondaire a Ă©tĂ© effectuĂ©e en Ă©valuant les documents de recherche et les enquĂŞtes antĂ©rieurs qui ont Ă©tĂ© rĂ©alisĂ©s pour Ă©valuer la perception des utilisateurs concernant l’alimentation tĂ©lĂ©phonique depuis leur batterie. En outre, l’étude met en Ă©vidence un problème selon lequel les notifications concernant les Ă©conomies d’énergie affichĂ©es Ă l’écran semblent elles-mĂŞmes soumettre les batteries Ă une forte utilisation. Par consĂ©quent, cette Ă©tude a Ă©tĂ© entreprise pour reflĂ©ter les façons qui pourraient aider les utilisateurs Ă Ă©conomiser efficacement la batterie de leur tĂ©lĂ©phone sans pour autant la dĂ©charger. L’étude offre un bon aperçu des nouvelles façons d’économiser plus efficacement l’énergie des smartphones, en proposant un cadre qui implique les utilisateurs finaux dans le processus
This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE/ACM TRANSACTIONS ON NETWORKING 1 Design, Realization, and Evaluation of DozyAP for Power-Efficient Wi-Fi
Abstract—Wi-Fi tethering (i.e., sharing the Internet connection of a mobile phone via its Wi-Fi interface) is a useful functionality and is widely supported on commercial smartphones. Yet, existing Wi-Fi tethering schemes consume excessive power: They keep the Wi-Fi interface in a high power state regardless if there is ongoing traffic or not. In this paper, we propose DozyAP to improve the power efficiency of Wi-Fi tethering. Based on measurements in typical applications, we identify many opportunities that a tethering phone could sleep to save power. We design a simple yet reliable sleep protocol to coordinate the sleep schedule of the tethering phone with its clients without requiring tight time synchronization. Furthermore, we develop a two-stage, sleep interval adaptation algorithm to automatically adapt the sleep intervals to ongoing traffic patterns of various applications. DozyAP does not require any changes to the 802.11 protocol and is incrementally deployable through software updates. We have implemented DozyAP on commercial smartphones. Experimental results show that, while retaining comparable user experiences, our implementation can allow the Wi-Fi interface to sleep for up to 88 % of the total time in several different applications and reduce the system power consumption by up to 33 % under the restricted programmability of current Wi-Fi hardware. Index Terms—802.11, mobile hotspot, power-efficient, software access point, Wi-Fi tethering
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