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A better understanding of how the COVID-19 pandemic responds to social distancing efforts is required for the control of future outbreaks and to calibrate partial lock-downs. We present quantitative relationships between key parameters characterizing the COVID-19 epidemiology and social distancing efforts of nine selected European countries. Epidemiological parameters were extracted from the number of daily deaths data, while mitigation efforts are estimated from mobile phone tracking data. The decrease of the basic reproductive number ($$R_0$$ R 0 ) as well as the duration of the initial exponential expansion phase of the epidemic strongly correlates with the magnitude of mobility reduction. Utilizing these relationships we decipher the relative impact of the timing and the extent of social distancing on the total death burden of the pandemic.

Mobile phone tracking poses challenges to individual privacy because a phone's sensor data and metadata logs can reveal behavioral, contextual, and psychological information about the individual who uses the phone. Here, I argue for a process-oriented approach to respecting individual privacy in the context of mobile phone tracking by treating informed consent as a process, not a mouse click. This process-oriented approach allows individuals to exercise their privacy preferences and requires the design of self-tracking systems that facilitate transparency, opt-in default settings, and individual control over personal data, especially with regard to: (1) what kinds of personal data are being collected and (2) how the data are being used and shared. In sum, I argue for the development of self-tracking systems that put individual user privacy and control at their core, while enabling people to harness their personal data for self-insight and behavior change. This approach to mobile phone privacy is a radical departure from current standard data practices and has implications for a wide range of stakeholders, including individual users, researchers, and corporations.

Smartphones are linked with individuals and are valuable and yet easily available sources for characterizing users' behavior and activities. User's location is among the characteristics of each individual that can be utilized in the provision of location-based services (LBs) in numerous scenarios such as remote health-care and interactive museums. Mobile phone tracking and positioning techniques approximate the position of a mobile phone and thereby its user, by disclosing the actual coordinate of a mobile phone. Considering the advances in positioning techniques, indoor positioning is still a challenging issue, because the coverage of satellite signals is limited in indoor environments. One of the promising solutions for indoor positioning is fingerprinting in which the signals of some known transmitters are measured in several reference points (RPs). This measured data, which is called dataset is stored and used to train a mathematical model that relates the received signal from the transmitters (model input) and the location of that user (the output of the model). Considering all the improvements in indoor positioning, there is still a gap between practical solutions and the optimal solution that provides near theoretical accuracy for positioning. This accuracy directly impacts the level of usability and reliability in corresponding LBSs. In this paper, we develop a smartphone app with the ability to be trained and detect users' location, accurately. We use Gaussian Process Regression (GPR) as a probabilistic method to find the parameters of a non-linear and non-convex indoor positioning model. We collect a dataset of received signals' strength (RSS) in several RPs by using a software which is prepared and installed on an Android smartphone. We also find the accurate 2σ confidence interval in the presented GPR method and evaluate the performance of the proposed method by measured data in a realistic scenario. The measurements confirm that our proposed method outperforms some conventional methods including KNN, SVR and PCA-SVR in terms of accuracy.

Texting-while-driving (T&D) is one of the top dangerous behaviors for drivers. Many interesting systems and mobile phone applications have been designed to help to detect or combat T&D. However, for a T&D detection system to be practical, a key property is its capability to distinguish driver's mobile phone from passengers’. Existing solutions to this problem generally rely on the user's manual input, or utilize specific localization devices to determine whether a mobile phone is at the driver's location. In this paper, we propose a method which is able to detect T&D automatically without using any extra devices. The idea is very simple: when a user is composing messages, the smartphone embedded sensors (i.e., gyroscopes, accelerometers, and GPS) collect the associated information such as touchstrokes, holding orientation and vehicle speed. This information will then be analyzed to see whether there exists some specific T&D patterns. Extensive experiments have been conducted by different persons and in different driving scenarios. The results show that our approach can achieve a good detection accuracy with low false positive rate. Besides being infrastructure-free and with high accuracy, the method does not access the content of messages and therefore is privacy-preserving.

Insecurity is one of the major challenges that the entire world is facing now, each country having their peculiar security issues. The crime rate in every part of the society these days has become a threatening issue such that vehicles are now used for co mmitting criminal activities mo re than before. The issue of vehicle theft has increased tremendously, mostly at gunpoint or car parks. In view of these, there is a need for adequate records of stolen, identified and recovered vehicles which are not readily available in our society and as such very important. The development of a vehicle theft alert and location identification system beco mes more necessary for vehicle o wners to ensure theft prevention and a speedy identification towards recovery efforts in situations where a vehicle is missing, stolen or driven by an unauthorized person. The theft alert function makes use of a GSM applicat ion developed and installed in a mobile phone device wh ich is embedded in the vehicle to communicate with the vehicle owner's mobile phone. The communicat ion is established via SMS (i.e. between the installed mobile phone device and that of the vehicle owner). The co mmunications established include; (i). Sending an SMS alert fro m installed mobile phone device to vehicle owner mobile phone when the car ignition is put on. (ii). Sending an SMS fro m the vehicle owner's mobile phone to start and stop the installed mobile phone device application. The location identificat ion function makes use of a web application developed to; (i). Determine the real time location of a vehicle by means of tracking using GPS. (ii). Broadcast missing or stolen vehicle informat ion to social media and security agency. The implementation of the installed mobile phone device application was done using JAVA because of its capabilit ies in programming mobile applications while PHP and MySQL was used for the web application functions. Integration testing of the system was carried out using simple percentage calculation for the performance evaluation. Fifty seven (57) vehicle owners were sampled and questionnaires were d istributed to them in order to ascertain the acceptability and wo rkab ility of the developed system. The result obtained shows the effectiveness of the system and hence it can be used to effectively monitor vehicle as it is been driven within or outside its jurisdiction. More so, the system can be used as database of missing, identified or recovered vehicles by various security agencies. Index Terms—Veh icle, Theft alert, Location identification, Tracking, GPS.

The development of ways to reduce malpractices in examination centers in all educational institutions is an important area of research. One of the major problems discovered aiding malpractices has been the creation of mobile phones, which however is a good communication device but needs to be curtailed during examinations. In order to have a 100% assurance that no student can cheat with his or her mobile phone a mobile detector system with a frequency jamming feature was developed using mobile cell phone detection techniques of measuring a cell phone's electromagnetic properties, determining an identifiable signature, measuring the RF spectrum and meeting the jamming requirements.

International audience; With the rapid expansion of cities around the world, large number of movements are made daily as people commute from their homes to their destinations, including workplaces. From these movements, trends and patterns can be derived which in turn, can provide valuable insights for urban planning. This is particularly relevant in the ‘smart cities' context. However, such movement data are often difficult to gather and analyse without infringing on privacy rights, especially with the increasing concerns on privacy issues. This paper reports on the use of aggregated mobile phone tracking data together with train network data to analyse movement patterns in, out, and within La Défense (Paris' business district). The findings can assist city planners by providing a better understanding of people's travel patterns

Summary. This research contributes to both theory and application. This is an important supplement to the research on the quality and uncertainty of spatial big data and it will help mobile phone data play a more effective application value in future research. In recent years, the rapid development of data acquisition means has led to the rapid accumulation of spatial data and generated spatial big data with geographic location information. However, the uncertainty in spatial big data leads to the quality problem of spatial big data, which is one of the main bottlenecks restricting the effective utilization of spatial big data. As an important part of spatial big data, it is necessary to study the quality and uncertainty of mobile phone data. In view of this, we delve into the key geographical environment factors that affect the positioning error of mobile phone data, extract error evaluation indexes and construct the spatial distribution model of positioning error with machine learning algorithms. To explore the distribution law of mobile phone data positioning error under different geographical scenarios. In addition, considering the high accuracy of personal travel GPS positioning, this study takes personal travel GPS positioning data as the comparative object of mobile phone data for analysis.

In the past decade society has entered a technological period characterized by handheld computing that supports input and processing from numerous sensors. Today’s mobile phones offer the ability to integrate input from sensors monitoring various external and internal sources e.g., accelerometer, magnetometer, microphone, GPS, wireless Internet, and Bluetooth. Furthermore, these raw inputs can be integrated and processed in ways that can offer novel representations of human behaviour. As a result, new opportunities to examine and better understand human spatial behaviour are available; one such application is the constant monitoring of a group of people over an extended period of time. Such a research setting lends itself to natural experiments that emerge as a result of regular and on-going observations. We report here on the observation of a natural experiment that took place in the context of a month-long monitoring study of 28 participants using mobile phone-based ubiquitous sensor monitoring. The implications for public health and transportation planning are discussed.

Mobile phone localization plays a key role in the fast-growing location-based applications domain. Most of the existing localization schemes rely on infrastructure support such as GSM, Wi-Fi or GPS. In this paper, we present FTrack, a novel floor localization system to identify the floor level in a multi-floor building on which a mobile user is located. FTrack uses the mobile phone's sensors only without any infrastructure support. It does not require any prior knowledge of the building such as floor height or floor levels. Through crowdsourcing, FTrack builds a mapping table which contains the magnetic field signature of users taking the elevator/escalator or walking on the stairs between any two floors. The table can then be used for mobile users to pinpoint their current floor levels. We conduct both simulation and field studies to demonstrate the efficiency, scalability and robustness of FTrack. Our field trial shows that FTrack achieves an accuracy of over 96% in three different buildings.

The recent trend in transportation planning information is to reduce traffic survey costs and enhance accuracy by using and converging various sources of external data. In Korea, mobile phone data can help generate useful transportation planning information, thanks to the universal use of mobile phones, which are present in a number greater than that of the population. This paper addresses measures to derive trip generation information from mobile phone data and verifies the value of the system for practical use by correlation analysis with KTDB trip generation data. The results show that trip generation information produced by mobile phone data correlates with existing (KTDB) trip generation data.

Smart phones or mobile phones enabled with global positioning system (GPS), different types of sensors, and communication technologies have become ubiquitous application development platform for Internet of Things (IoT) and new sensing technologies. Improving sensing area coverage, reducing overlap of sensing area, and energy consumption are important issues under mobile phone sensing. This paper presents human mobility-based mobile phone sensors sampling algorithm. Human mobility patterns and geographical constraints have an impact on performance of mobile phone sensing applications. The real-outdoor location traces of volunteers, collected using GPS-enabled mobile phones are used for performance analysis of proposed work. The proposed mobile phone sensor sampling algorithm considers velocity of human mobility as an important parameter for improving sensing area coverage and reduction of energy consumption. To an extent overlap between sensing area coverage is allowed to overcome, the reduction of sensor data samples caused by spatial regularities of human mobility. The performance is analyzed and evaluated by considering general regular sampling and proposed sampling method for mobile phone sensing activity. The results show that for normal human walking velocity ( $ 1.5 m/s) proposed mobile phone sensor sampling algorithm performs better in terms of sensing area coverage and reduction of battery energy consumption for mobile phone sensing activity.

In modern days, gadgets are essential part of everyday lives and they enable to access a variety of ubiquitous services. Recently, the availability of these ubiquitous and mobile services has increased due to the different form of access provided by mobile devices, such as Bluetooth and Wi-Fi. In the same trend, the typologies of vulnerabilities exploiting these services and communication channels have boosted as well. Therefore, the presence of malware in mobile platform can seriously impact the end users privacy and security, reducing the end users trust in performing mobile access to its network services. In this, an authentication mechanism is based on screen brightness which prevents and increases security against side channel attacks.

Global positioning system (GPS) has enabled a number of geographical applications over many years. Quite a lot of location-based services, however, still suffer from considerable positioning errors of GPS (usually 1 to 20 m in practice). In this study, we design and implement a high-accuracy global positioning solution based on GPS and human mobility captured by mobile phones. Our key observation is that smartphone-enabled dead reckoning supports accurate but local coordinates of users’ trajectories, while GPS provides global but inconsistent coordinates. Considering them simultaneously, we devise techniques to refine the global positioning results by fitting the global positions to the structure of locally measured ones, so the refined positioning results are more likely to elicit the ground truth. We develop a prototype system, named GloCal, and conduct comprehensive experiments in both crowded urban and spacious suburban areas. The evaluation results show that GloCal can achieve 30 percent improvement on average error with respect to GPS. GloCal uses merely mobile phones and requires no infrastructure or additional reference information. As an effective and light-weight augmentation to global positioning, GloCal holds promise in real-world feasibility.

Background Over the last decade, the availability and use of mobile phones have grown exponentially globally and in Cambodia. In the Sihanouk Hospital Centre of Hope(SHCH) in Cambodia about half of all tuberculosis patients referred out to peripheral health facilities for TB treatment initiation or continuation were lost to contact after referral ranging from 19 to 69% between 2008 and 2013. To address this, we implemented a mobile phone-based patient tracking intervention. Here, we report the number and proportion of referred TB patients who could be contacted through a mobile phone and retained in care after the introduction of mobile phone tracking. Methods A descriptive study involving follow-up of TB patients referred out from SHCH to peripheral health facilities during May–October 2014. Standard operating procedures were used to contact individual patients and/or health facilities using a mobile phone. Results Among 109 TB patients referred to peripheral health facilities, 107(98%) had access to a mobile phone of whom, 103(97%) could be contacted directly while 5(2%) were contacted through their health care providers. A total of 108(99%) of 109 referred TB patients in intervention period were thus placed on TB treatment. Conclusions This study provides preliminary, but promising evidence that using mobile phones was accompanied with improved retention of referred TB patients compared to historical cohorts. Given the limitations associated with historical controls, we need better designed studies with larger sample size to strengthen the evidence before national scale-up.

Large public displays are widely used in public spaces for serving information. The flow of the information is largely a one-way passive communication due to a lack of user-content interaction, which in some ways limits its effectiveness as an information display system. We propose a use of mobile phones as a tool to interact with a public display. Our proposed mobile-public display user interaction uses a mobile phone to control and retrieve information from a public display. In this paper we present results of a usability test of our proposed interaction, which indicated that there was a strong correlation between the information retrieval performances and the participant's level of engagement with the mobile phone.

International audience; Profiling the diversity of land use in modern cities by mining data related to human mobility represents a challenging problem in urban planning, transportation and smart city management. Previous work on mobile phone data (i.e., Call Detail Records) has shown the existence of strong correlations between the urban tissue and the associated mobile communication demand. Similarly, GPS traces of vehicles convey information on transportation demand and human activities that can be related to the land use of the neighborhood where they take place. In this paper, we investigate the land use patterns that emerge when studying simultaneously GPS traces of probe vehicles and mobile phone data collected by network providers. To this end, we extend previous definitions of mobile phone traffic signatures for land use detection, so as to incorporate additional information on human presence and mobility conveyed by GPS traces of vehicles. Leveraging these extended signatures, we exploit an unsupervised learning technique to identify classes of signatures that are distinctive of different land use. We apply our technique to real-world data collected in French and Italian cities. Results unveil the existence of signatures that are common to all studied areas and specific to particular land uses. The combined use of mobile phone data and GPS traces outperforms previous approaches when confronted to ground-truth information, and allows characterizing land use in greater detail than in the literature to date.

The usage of mobile devices has grown rapidly and mobile communication services are becoming more popular as well, almost everyone has a smart mobile device. Most mobile devices provide GPS satellite coordinate positions, some mobile phone companies provide both GPS and GLONASS binary coordinate system enabling faster and more accurate coordinate information. The population in Taiwan is aging with the average 10.75% of senior inhabitants. If the elder member of a family can carry a smart mobile phone when he or she is outside for activities, this elder member can always be tracked through a system that provides coordinate information through Web services. When this elder member is disoriented the instructions on the screen will guide him or her back home through the function of Augmented Reality provided by the system.

Mobile phones and short message service (SMS) have been widely used in disease control and prevention. Personalized SMSs further allows real-time, precisely targeted interventions that achieve better cost-effectiveness. Few SMSs are personalized based on spatiotemporal travel behavior of individuals, which plays an important role in disease spread. We proposed a set of SMS policies tailored to individuals' travel behavior derived from massive mobile phone tracking records. These policies tend to alter spatial, temporal, or spatiotemporal patterns of individuals' daily activities, in order to reduce the risk of disease spread. Taking Shenzhen city, China, as a study area, we simulated and evaluated these policies for Dengue Fever intervention. Our simulation results show that the spatially targeting policy that discourages discretionary trips produces the highest cost-effectiveness to control disease spread in areas with high importation risk. For the entire city, however, the temporally targeting policy that shifts individuals’ travel schedules achieves the best cost-effectiveness. Our study contributes to a new ground of precise public health that calls for individualized, real-time, and accurately targeted interventions. Utilizing big mobile phone data, we present a novel approach to design, simulate, and evaluate space-time precise intervention for disease control.

Mobile phone industry is classified among the fastest growing engineering branches. It has to be exploited for vast applications, reliability and affordability. Mobile cellular phone subscribers have reached saturation point; with such information, the basic cell phone that was mainly utilized to make calls will also be utilized for remote switching and control activities. The now developed system is based on the global system for mobile communications (GSM) radio network: it will operate as a very long distance remote switch. Utilizing the daily cell phone, a user will either put on/off any desired electric circuit located in an owned, controlled compound. Two cell phones are provided, one being a mobile transmitter user end and another being referred to as a fixed receiver end. A signal will be sent from the user end to put a consumer’s electric circuit either on or off at the receiver end; afterwards, the receiver end will notify the user-end about the on/off state of the consumer. The particularity of this publication is the system simplicity, yet cheap and safe, so that even very low income cell phone users can enjoy radio frequency (RF) technology’s increasing applications. The software utilized to develop and simulate circuits is the linear technology, LT spice. The calculative theory has quantitatively enriched the methodology. Both the building blocks and the physical implementation diagrams for the system are herein contained. The remote switching system based on GSM radio network has been successfully designed, implemented, tested and its functionality has been examined.

The processing capabilities and advantages of mobile devices equipped with portable sensors provide the basis for new context-aware services and applications tailored to the user environment and daily activities. People on the move have a grown need for real-time information and services anytime and anywhere. Context information in mobile phones e.g., location, user activity, calendar and speed can significantly improve the user experience in the current situation. A review of the literature suggests that context awareness in mobile phone can be very helpful and considered as inevitable technique in future of mobile phone application. In this paper, we give a short review about context awareness and then critically analyzed related researches to the context awareness in mobile phone. Furthermore, we proposed an architecture to reduce cost of using Global Positioning System (GPS) and improves localization in indoors area. The review argues the weakness and strength of these studies, and aims to (a) indicate the most important context in mobile phone, (b) Improving localization in indoor areas (c) reducing battery consumption of GPS sensor in mobile phone.

The 3G era, the smartphone market share is higher and higher. The mobile phone based on the Android platform accounts for more than half of the market share. Once the user lost the phone, it is not only hard to find, but also to face important data leak and privacy security issues. So, the demand to provide mobile phone found function appears increasingly urgent. If the mobile phone is lost, this platform can get information on replaced mobile phone SIM card to boot for the first time, and upload the new mobile phone number and current phone location information to the server. It provides users with inquiry function on the web in order to achieve the purpose of tracking the lost mobile phone. The application prospect of this study is widespread, not only limited to track the missing phone, also involves other position service in the life need. The relevant mobile localization algorithm is detailed in this paper.

Under the application research of mobile platform, this paper individually studies android-based wireless sensor network coordinator and smart phone-based GPS positioning system. By designing and developing a mobile phone map service system on android platform, our system contains modules including GPS positioning, map pattern, route query, location search, moving track, record list, etc. We also design and realize general scheme of android platform-based GPS positioning system including function analysis, functional block diagram, anterior curtain layout and Activity skip-process behind-the-screen, and the structure for system database.

The rising of the cloud computing and the generation of GIS cloud will promote the development mode of server and client into a new high tide, and with the popularity of intelligent mobile phones and plate computer, mobile will not only the development trend but also the trend of the development of IT, and then the development of intelligent mobile phone for the mobile GIS development will be the future GIS development of one of the main trend. So in our study, we considered how to explore the future wisdom campus mobile end GIS product, from this view, so we choose the system which is today's popular Windows Phone operating , and basing on the the wisdom campus, and design mobile Phone campus GIS system.Our research and development process choose the Microsoft Visual Studio 2010 as development platform, we using c # language for development, and choose ArcGIS Server10 as GIS service server, design and develope the Windows Phone mobile Phone about the mobile Phone campus GIS system. The whole system mainly consists of campus news module, course arrangement module, map query module, my diary module, recent weather modules, the system will convenience users’ campus life, which is also a very meaningful exploration and attempt for the intelligent campus.

The mobile phone was initially a technology only associated with voice calls – and primarily constrained to usage in cars. Subsequent generations of mobile phones featured voice connectivity, short text messages, and a small set of simple builtin applications, such as a calendar, address book, and games. Billions of users across both the developed and developing world adopted the mobile phone. As technology advanced, feature phones with basic multimedia capabilities emerged. Telecommunications operators created ‘walled gardens’ allowing feature phone owners to access (and pay for) a variety of contents, such as ring tones. In the late 1990s, NTT DoCoMo established, with the iMode phone, an open system for rich mobile websites.

Today's mobile smartphones are very powerful, and many smartphone applications use wireless multimedia communications. Mobile phone security has become an important aspect of security issues in wireless multimedia communications. As the most popular mobile operating system, Android security has been extensively studied by researchers. However, few works have studied mobile phone multimedia security. In this article, we focus on security issues related to mobile phone cameras. Specifically, we discover several new attacks that are based on the use of phone cameras. We implement the attacks on real phones, and demonstrate the feasibility and effectiveness of the attacks. Furthermore, we propose a lightweight defense scheme that can effectively detect these attacks.

On the mobile phone as a `platform', location is everywhere. It may not be king, but pretty much any app that aims to provide a service now includes a location-based element, whether it is to help you find a nearby restaurant or minicab, or simply to push local promotions your way. The space-satellite-based Global Positioning System (GPS) is the key enabler. Even low-end smartphones now include not just a GPS chip, but can also locate themselves by scanning for local mobile basestations and Wi-Fi access points. Location-based services on mobile devices used to be the preserve of app-happy shoppers and geo-social networking. Now, their usefulness is being explored for more serious - even mission critical situations.

Nowadays movement patterns and people’s behavioral models are needed for traffic engineers and city planners. These observations could be used to reason about mobility and its sustainability and to support decision makers with reliable information. The very same knowledge about human diaspora and behavior extracted from these data is also valuable to the urban planner, so as to localize new services, organize logistics systems and to detect changes as they occur in the movement behavior. Moreover, it is interesting to investigate movement in places like a shopping area or a working district either for commercial purposes or for improving the service quality. These kinds of tracking data are made available by wireless and mobile communication technologies. It is now possible to record and collect a large amount of mobile phone calls in a city. Technologies for object tracking have recently become affordable and reliable and hence we were able to collect mobile phone data from a city in China from January 1, 2008 to December 31, 2008. The large amount of phone call records from mobile operators can be considered as life mates and sensors of persons to inform howmany people are present in any given area and how many are entering or leaving. Each phone call record usually contains the caller and callee IDs, date and time, and the base station where the phone calls are made. As mobile phones are widely used in our daily life, many human behaviors can be revealed by analyzing mobile phone data. Through mobile phones, we can learn the information about locations, communications between mobile phone users during their daily lives. In this work, we propose a comprehensive visual analysis system named as MViewer, Mobile phone spatiotemporal data Viewer, which is the first system to visualize and analyze the population’smobility patterns from millions of phone call records. Our system consists of three major components: 1) visual analysis of user groups in a base station; 2) visual analysis of the mobility patterns on different user groups making phone calls in certain base stations; 3) visual analysis of handoff phone call records. Some well-established visualization techniques such as parallel coordinates and pixelbased representations have been integrated into our system. We also develop a novel visualization schemes, Voronoidiagram-based visual encoding to reveal the unique features of mobile phone data. We have applied our system to real mobile phone datasets that are kindly provided by our project partners and obtained some interesting findings regarding people’s mobility patterns.

Mobile technology has been available for at least a decade and is increasingly being used in developing countries as away of contacting and connecting citizens and helping them to organize for a better life.Mobile phones are not just for phone calls, but they can also be used to collect data in several different formats and send them to a central server. There the data can be aggregated and analyzed, with tables and visualizations automatically generated. What is new is the sheer number of observation points that are potentially available by using mobile phones. With over 4 billion phones in use worldwide, the mobile phone network is emerging as a form of “global brain” with sensors everywhere. In addition, there are companies such as Fourier Systems that provide purpose-built mobile devices that are specifically designed for science experiments in school sand for data logging in any science project.

This paper studies the development trend of intelligent mobile phone, confirmed the necessity of research on intelligent mobile phone malicious code. Study on the detection technology, proposed intelligent mobile phone regular networks and random networks based on malicious code propagation model, propagation mechanism is studied. Set up a perfect malicious code discovery and defense system model, at different levels is put forward that different, prove the necessity of scanning algorithm and Semantic Detection Algorithm for eigenvalue. To improve the security of the whole communication network.

We have studied Chan-Taylor two-dimensional positioning algorithm and propose an innovative Chan-Taylor three-dimensional positioning algorithm. And we apply it to the indoor three-dimensional location problem based on wireless communication base station. According to the actual measurement of the coordinates of the 30 base stations and the value of time of arrival (TOA) between the 1100 mobile phone positions and each base station, a total of 33000 data, we get the three-dimensional coordinates of 1100 mobile phone positions by using Chan-Taylor three-dimensional positioning algorithm. The mobile phone position coordinates are compared with the known real three-dimensional coordinates of mobile phone position. We conclude that Chan-Taylor three dimensional positioning algorithm has high positioning accuracy. The average relative errors of all mobile phone positions in X, Y, Z directions are 0.024, 0.016 and 0.512. The results show that this algorithm can be used to achieve three-dimensional location of mobile phone.

Traffic flow, allocation and availability of parking space within the streets of Nairobi is a major concern to every motorist. The availability of the mobile phone and its increased affordability has led to its adoption as the main gadget and technology for contemporary communication in most developing countries. Furthermore, the convenience it offers to users and its cost effectiveness has made it the technology driver not just in developing world but also in the developed countries. One area where its application has born fruits in some countries is in mobile parking. By use of mobile communication, cities in countries such as Singapore and Germany have experienced increased efficiency in traffic management and parking fees collection. The technology also depends on banking models used in these countries; a fact that makes it necessary for any similar solution been developed elsewhere to consider the local system environment.

This paper considers the problem of network-based mobile-phone positioning when multiple providers are available. This paper proposes two cross-provider localization algorithms via a cooperative approach, which are called linear regression (LR) and locally cooperative embedding (LCE), to efficiently exploit the complementary information from each network provider. The former chooses the provider weights that minimize the mean-square positioning errors. The latter dynamically embeds the cooperation and iteratively refines the positioning process according to each provider's local accuracy surrounding the user. This paper applies the proposed cross-provider positioning algorithms to actual Global System for Mobile Communications (GSM) networks, using a dual-subscriber-identity-module (SIM) mobile phone connecting to multiple providers simultaneously. On-site experiments clearly demonstrated that the proposed cross-provider approaches provide better positioning accuracy than any individual provider, where LCE achieves the best performance.

This study designs a method of identifying the camera model used to take videos that are distributed through mobile phones and determines the original version of the mobile phone video for use as legal evidence. For this analysis, an experiment was conducted to find the unique characteristics of each mobile phone. The videos recorded by mobile phones were analyzed to establish the delay time of sound signals, and the differences between the delay times of sound signals for different mobile phones were traced by classifying their characteristics. Furthermore, the sound input signals for mobile phone videos used as legal evidence were analyzed to ascertain whether they have the unique characteristics of the original version. The objective of this study was to find a method for validating the use of mobile phone videos as legal evidence using mobile phones through differences in the delay times of sound input signals.

Remote control technology has been developed by utilizing various transmission media. Some of them are remote control by the media using infrared, radio, internet and telephone line. Remote control system via the telephone line has an advantage in terms of distance range and practicality compared to other media. The presence of mobile phone or mobile phone that has been known and used by many people, who are able to communicate wherever they are, without being limited by space and range of cable lengths could be a solution for the needs of remote objects as described above. One of the most popular mobile phone function is to send and receive SMS. SMS is suitable for the control system of wireless real time because the speed of data delivery, efficiency and breadth of coverage, but the excess mobile phone with SMS facility of its still needs to be connected to a control device to be able to control on / off devices electric remotely.

Semantic place prediction problem is the process of giving semantic names, such as school, home, office, to locations. Different than the localization problem where the coordinates of a place are predicted, the aim is to semantically characterize the location. While the GPS coordinates of a place can be utilized in solving the problem, phone usage patterns of the users in that location can be used as well. In this paper, the aim is to semantically classify locations of smart phone users utilizing the data collected from wireless interfaces and the motion sensors available on the phones with machine learning algorithms. The efficiency of features extracted from raw data is analysed in terms of metrics such as accuracy, using different classification algorithms. The results show that, while random forest and decision tree algorithms achieve 66% accuracy with only temporal features, adding features from device properties and activity features increases the accuracy up to 99%.

The record-and-replay approach for software testing is important and valuable for developers in designing mobile applications. However, the existing solutions for recording and replaying Android applications are far from perfect. When considering the richness of mobile phones' input capabilities including touch screen, sensors, GPS, etc., existing approaches either fall short of covering all these different input types, or require elevated privileges that are not easily attained and can be dangerous. In this paper, we present a novel system, called MobiPlay, which aims to improve record-and-replay testing. By collaborating between a mobile phone and a server, we are the first to capture all possible inputs by doing so at the application layer, instead of at the Android framework layer or the Linux kernel layer, which would be infeasible without a server. MobiPlay runs the to-be-tested application on the server under exactly the same environment as the mobile phone, and displays the GUI of the application in real time on a thin client application installed on the mobile phone. From the perspective of the mobile phone user, the application appears to be local. We have implemented our system and evaluated it with tens of popular mobile applications showing that MobiPlay is efficient, flexible, and comprehensive. It can record all input data, including all sensor data, all touchscreen gestures, and GPS. It is able to record and replay on both the mobile phone and the server. Furthermore, it is suitable for both white-box and black-box testing.

Every mobile phone emits radio frequency electromagnetic energy. The amount of this energy absorbed by the human head is measured by the specific absorption rate (SAR). There are standard limits, according to which phones sold should be below certain SAR level. To maintain these limits, shields can be used for the mobile phones. In this paper using ANSYS HFSS, modelling of the human head is done. The modern mobile phone design is used for simulation. SAR distribution is measured for different layers of the head due to exposure to radiation from the mobile phone operating at GSM-1800 frequency band. The performance of the mobile phone antenna due to different shields is observed. Proper shielding material properties are found.

Along with globally approaching of the 3G era, the progress of mobile communication technology and the development of mobile terminal devices will rapidly promote the mobilization development of traditional Ecommerce. In order to ensure it to achieve further development, secure, flexible and reliable mobile payment system is becoming more and more important. Compared with the payment pattern of ordinary commerce, there will be profound changes in the mobile payment, such as special payment channel, payment carrier and etc. After deep studying about previous payment methods and future 3G communication technology, this paper introduces a new mobile payment model by combining with IC chip, mobile phone and mobile internet, and then gives some improvement measures for current settlement mechanisms in the network transaction, which is entirely around payment channel, payment carrier, security authentication and other key issues in 3G environment. The real time processing of information flow, capital flow and logistics in mobile environment can be easily achieved, forming a complete and reliable business operation for mobile users, which can bring some great conveniences and profound influences for mobile payment industry.

Phone lost has been a major problem these days. This case can happened because of the user own fault (he place it in the wrong place and forget it) or because of intentional phone stealing. Seeing many of this missing case we try to develop a system for tracking and securing a missing phone. Android platform is selected because it is one of the best operating system for mobile phone right now and the user growth is very promising. This application will give an extra security when a phone gone missing, as we know we store a lot of sensitive data on our phone. The system work flow is very simple actually, our application will be on standby and monitor command that it received via SMS and it will work in the background so user won’t be get any distraction from this application. Using these commands user can lock his phone, sound the phone alarm, delete his phone data, get his phone data, and get his phone last location. This application have some other feature too, like lock his phone when someone change his phone card and send the new number that attach in his phone to the owner. When system get any request about phone's last position then system will process that request to get phone's latitude and longitude via GPS, after that system will quietly send it to the owner.

One of the important features of Communication System is to find the Location of a Person. Finding the location of Person is either through Internet or through Mobile Devices. Most of the valuable location-based services are enabled by this feature of Location Tracking. There are various Location technologies which can be used and implemented by telecommunication managers and engineers. The technologies are GPS, GPRS, and WiFi with android operating Systems. Location can also be searched without GPS through Internet. The paper briefly discussed GSM network and cellular data networks from point of view of IP Clients, used for finding location of mobile phone. Further, a paper determined the location through IPaddress, through mobile Number, through SMS, through facebook and also through google latitude. Finally the study compares the result that leads to conclusions and key issues for further research.

This study investigates the realistic conditions of ‘digital Korea’, especially as they are exemplified by the Samsung SDI scandal in South Korea. Samsung SDI, the world's largest plasma TV maker and a subsidiary of the Samsung Group, has fallen under suspicion due to using illegally cloned mobile phones to track the location data of some activist workers who tried to organise a union. The study stresses that this example of mobile tracking represents the shady side of mobile phone use created by management's excessive desire for labour control, and confirms that mobile tracking techniques make possible the spatial expansion of the scope of power. The spatial vocabulary of power is not totalitarian, but dispersed and nomadic in action, and resides in the space of ‘flows’ constructed by electronic impulses. This study discloses that, for private corporations, mobile tracking facilitates a form of efficient, invisible labour control over ‘targeted’ workers, even outside the workplace. It concludes that the control of labourers in Korea has been reinforced by the confluence of business interests, the under-developed political system and a societal lack of interest in privacy.

We propose a novel way to augment a real-world scene with minimal user intervention on a mobile phone; the user only has to point the phone camera to the desired location of the augmentation. Our method is valid for horizontal or vertical surfaces only, but this is not a restriction in practice in manmade environments, and it avoids going through any reconstruction of the 3-D scene, which is still a delicate process on a resource-limited system like a mobile phone. Our approach is inspired by recent work on perspective patch recognition, but we adapt it for better performances on mobile phones. We reduce user interaction with real scenes by exploiting the phone accelerometers to relax the need for fronto-parallel views. As a result, we can learn a planar target in situ from arbitrary viewpoints and augment it with virtual objects in real-time on a mobile phone.