IDL - International Digital Library Of Technology & Research Volume 1, Issue 5, May 2017
Available at: www.dbpublications.org
International e-Journal For Technology And Research-2017
Advance Diagnostic Tool for Android Devices: A Performance Analyzing Tool for Mobile Device Ms. CHAITHRA S1, Dr. K. THIPPESWAMY2, Dept. of Computer Science 1 M-Tech, Student, VTU Regional Office, Mysuru, India 2 Guide, Prof & HOD, VTU Regional Office, Mysuru, India
SURVEY PAPER ABSTRACT- Abstract— this paper will provide the diagnostic tool solution for the measurement of values with proper units from various signals of Android Device. This application will be used for concluding the signal strength from various Transmitters; Trans receivers of mobile device. This includes GPS Receiver, Acceleration & Gravity Sensor, Rotation Sensor, Magnetic Sensors, Orientation Sensor, Relative Humidity Sensor, Proximity Sensor, Cell Network receivers & Wi-Fi Receiver. This paper provides the diagnostic tool for all the above said components of mobile device with appropriate units. Keywords—Diagnostic Tool, Android Device, Mobile Sensors, Receivers and Senders, Units and Values. 2 INTRODUCTION Advance Mobile Data Receiver application is an Android base application which is used to diagnose a variety of unknown information about the hidden parameters of device components such as GPS, WI-FI, Mobile Network and much more. The receiver measures the transit time of each message and computes the distance to each satellite. A form of
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triangulation is used to combine these distances with the location of the satellites to determine the receiver’s location. The position is displayed, perhaps with a latitude and longitude, and elevation information, bearing, speed, calculated from position changes. This diagnostic tool will displays data reported by sensors in the phone. This diagnostic tool for cellular network provides information about the type of Network (GSM/CDMA/LTE), MCC, MNC, LAC, Cell ID, PCI/PSC and Signal Strength. 3 SURVEYS 3.1 GWS Mobile Diagnostic App This survey study about Powerful Performance Measurement Tool concepts, the app is a diagnostic tool for mobile devices that can quickly yet thoroughly test mobile and Wi-Fi networks in terms of data speed, network latency, signal strength, serving cell towers, GPS signal and other key performance indicators. Independently, the app can provide cost-effective, surface-layer performance analysis, and when combined with GWS’ industry leading testing solutions, it can serve to significantly enhance benchmarking efforts. GWS Mobile Diagnostic App Flexible and Easily Configurable: The app allows users to easily configure, run, and review multiple test scenarios involving ping, HTTP upload, HTTP
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IDL - International Digital Library Of Technology & Research Volume 1, Issue 5, May 2017
Available at: www.dbpublications.org
International e-Journal For Technology And Research-2017 download, browser, HTTP multi-thread upload, and HTTP multi-thread download. Users also have the ability to configure test controls including count, duration, or continuous testing. In addition, test configurations created for a current project can be saved for future use. Real-Time, Shareable Results: Results from a test project are instantaneous and can be shared with others. The results can be viewed in various levels of detail from individual test results to a project summary. And users can also view the trends resulting from conducting multiple tests. Comprehensive Network Assessments: In combination with Mobistat GWS’ advanced post processing technology, users can also view app test results via a secure website, and have access to interactive webbased reporting and mapping tools. Thus, adding another layer of evaluation for the performance measurements generated by the app. 3.2 Diagnosing Energy Efficiency and Performance for Mobile Internetware Applications Mobile Internetware applications sense physical and cyber environments and connect a tremendous world of users and things. Smartphone applications are one typical example. However, the smart services of many real-world smartphone applications are realized in an energy-inefficient or performance-ill way, seriously affecting user experience. What is even worse, developers lack powerful tools to combat such problems. This curbs the continuous growth of Internet-based mobile computing. There thus exists a strong call from research communities and industries for effective techniques to diagnose energy and performance bugs in smartphone applications. In this article, we study the characteristics of these bugs and discuss challenges in diagnosing them. We then review state-of-the-art techniques in this field and explore future research directions. Finally, we study the use of one representative tool in analyzing commercial Android applications and Samsung Mobile SDK. We show how the tool can provide useful diagnostic information to developers and discuss effective ways to support Internet-based mobile computing and beyond.
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3.3 Auto-configuration server architecture with device cloud cache In this paper, a server architecture based on the TR069 communication protocol is proposed. Server provides an efficient and adaptive way to remotely control and monitor customer devices. The proposed solution is a modular because provides extendable layers to connect various statistics modules, modules for analysis and diagnosis of customer devices or for graphical presentation applications, such as web or android based applications. With increasing number of user devices, configuration and monitoring of the connected devices have become very complex and difficult task. Manufacturers and service providers are challenged to provide device monitoring to satisfy desired level of quality of service (QoS). One of the solutions is TR-069 communication protocol [1]. The protocol describes a set of Remote Procedure Call (RPC) methods that are exchanged between Customer Premises Equipment (CPE) and Auto-Configuration Server (ACS) via HTTP/HTTPS and SOAP protocols. Advantages • Reduced installation costs • System scalability 3.4 A review of wearable sensors and systems with application in rehabilitation An Advanced Home Automation System Using The aim of this review paper is to summarize recent developments in the field of wearable sensors and systems that are relevant to the field of rehabilitation. The growing body of work focused on the application of wearable technology to monitor older adults and subjects with chronic conditions in the home and community settings justifies the emphasis of this review paper on summarizing clinical applications of wearable technology currently undergoing assessment rather than describing the development of new wearable sensors and systems. A short description of key enabling technologies (i.e. sensor technology, communication technology, and data analysis techniques) that have allowed researchers to implement wearable systems is followed by a detailed
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IDL - International Digital Library Of Technology & Research Volume 1, Issue 5, May 2017
Available at: www.dbpublications.org
International e-Journal For Technology And Research-2017 description of major areas of application of wearable technology. Applications described in this review paper include those that focus on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders. The integration of wearable and ambient sensors is discussed in the context of achieving home monitoring of older adults and subjects with chronic conditions. Future work required to advance the field toward clinical deployment of wearable sensors and systems is discussed. The US health care system faces daunting challenges. With the improvements in health care in the last few decades, residents of industrialized countries are now living longer, but with multiple, often complex, health conditions [1, 2, 3]. Survival from acute trauma has also improved, but this is associated with an increase in the number of individuals with severe disabilities [4]. From an epidemiological standpoint, the cohort of "baby boomers" in the US is now reaching an age at which they will begin to severely stress the Medicare system. Finally, recent health care reform efforts may add 32 million newly insured patients to the health care system in the next few years [5]. These altered demographics raise some fundamental questions How do we care for an increasing number of individuals with complex medical conditions? how do we provide quality care to those in areas with reduced access to providers? how do we maximize the independence and participation of an increasing number of individuals with disabilities? Cleary, answers to these questions will be complex and will require changes into how we organize and pay for health care. However, part of the solution may lie in how and to what extent we take advantage of recent advances in information technology and related fields. Currently, there exist technologies that hold great promise to expand the capabilities of the health care system, extending its range into the community, improving diagnostics and monitoring, and maximizing the independence and participation of individuals. This paper will discuss these technologies in depth, with a focus on remote monitoring systems based on wearable technology. We chose to focus on these technologies because
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recent developments in wearable sensor systems have led to a number of exciting clinical applications. 3.5 Cell phone-based devices for bio analytical sciences. During the last decade, there has been a rapidly growing trend toward the use of cellphonebased devices (CBDs) in bioanalytical sciences. For example, they have been used for digital microscopy, cytometry, read-out of immunoassays and lateral flow tests, electrochemical and surface plasmon resonance based bio-sensing, colorimetric detection and healthcare monitoring, among others. Cellphone can be considered as one of the most prospective devices for the development of next-generation point-of-care (POC) diagnostics platforms, enabling mobile healthcare delivery and personalized medicine. With more than 6.5 billion cellphone subscribers worldwide and approximately 1.6 billion new devices being sold each year, cellphone technology is also creating new business and research opportunities. Many cellphonebased devices, such as those targeted for diabetic management, weight management, monitoring of blood pressure and pulse rate, have already become commercially-available in recent years. In addition to such monitoring platforms, several other CBDs are also being introduced, targeting e.g., microscopic imaging and sensing applications for medical diagnostics using novel computational algorithms and components already embedded on cellphones. This manuscript aims to review these recent developments in CBDs for bioanalytical sciences along with some of the challenges involved and the future opportunities. The use of cellphones in bioanalytical sciences has opened new opportunities and intensified research efforts for the development of next generation cellphone-based devices (CBDs) that will enable users to have access to cost-effective and compact bioanalytical technologies at any time and place. Such mobile Healthcare (mHealthcare) technologies based on CBDs will further improve the self-management of chronic patients, and will enable the supervision of physically-disabled, mentally ill or elderly individuals with minimum interference in their daily lives. Equipped with various advanced features, such as real-
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IDL - International Digital Library Of Technology & Research Volume 1, Issue 5, May 2017
Available at: www.dbpublications.org
International e-Journal For Technology And Research-2017 time geo-tagging, secure data management and analysis, high storage capacity, powerful processors, wireless connectivity through General Packet Radio Service and Wi-Fi, etc. the current generation of cellphones provides a promising digital platform for the development of various bioanalytical devices. A variety of sensors, such as Global Positioning System modules, light detectors, microphones, cameras, accelerometers as well as proximity sensors, are already integrated into the cellphones. Therefore, CBDs might especially be useful for bioanalytical applications in remote and resource-poor settings, generating real-time results, which can be remotely accessed by e.g., the analysts and certified professionals, thereby enabling the monitoring of emerging situations.
and education appears promising and exciting, more high-quality studies are needed to better understand the role it will have in this field. We recommend popular smartphone applications for physicians that are lacking in evidence and discuss future studies to support their use.
3.6 The Smartphone in Medicine: A Review of Current and Potential Use Among Physicians and Students. This survey support to advancements in technology have always had major impacts in medicine. The smartphone is one of the most ubiquitous and dynamic trends in communication, in which one’s mobile phone can also be used for communicating via email, performing Internet searches, and using specific applications. The smartphone is one of the fastest growing sectors in the technology industry, and its impact in medicine has already been significant. Objective: To provide a comprehensive and up-todate summary of the role of the smartphone in medicine by highlighting the ways in which it can enhance continuing medical education, patient care, and communication. We also examine the evidence base for this technology. Methods: We conducted a review of all published uses of the smartphone that could be applicable to the field of medicine and medical education with the exclusion of only surgical-related uses. Results: In the 60 studies that were identified, we found many uses for the smartphone in medicine; however, we also found that very few high-quality studies exist to help us understand how best to use this technology.While the smartphone’s role in medicine
REFERENCES: [1] S. Analytics, ”Cellphone Energy gap is widening”, SEPTEMBER 2014.
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4. CONCLUSION: This proposed system will provide a solution for the measurement of values with proper units for various signals. This application will be used for concluding the signal strength from various transmitters and transreceivers. Thus our aim is to provide a proper and accurate diagnostic tool with appropriate units using the hardware components present in the Android device.
[2] Yepang Liu, Chang Xu, S.C. Cheung, and Jian Lu, ”GreenDroid: Automated Diagnosis of Energy Inefficiency for Android phone Applications”,IEEE TRANSACTIONS SOFTWARE ENGINEERING. VOL. 40, NO. 9, SEPTEMBER 2014. [3] Ding Li and William G. J. Halfond, ”An Investigation into Energy-Saving Programming Practices for Android Android phone App Development”,India Copyright 14 ACM 978-1-45032844-9/14/06. GREENS14, June 1, 2014. [4] Ronny Hans, Manuel Zahn, Ulrich Lampe, Ralf Steinmetz, Apostolos Papageorgiou, ”Energy-efficient Web Service Invocation on Mobile Devices: The Influence of Compression and Parsing”, In Proceedings of 2nd International Conference of Mobile Services. (MS 2013). [5] Saswat Anand, Mayur Naik, Hongseok Yang,, ”Automated Concolic Testing of Android phone Apps”, SIGSOFT12/FSE-20, November 11 16, 2012,
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IDL - International Digital Library Of Technology & Research Volume 1, Issue 5, May 2017
Available at: www.dbpublications.org
International e-Journal For Technology And Research-2017 Cary, North Carolina, USA. Copyright 2012 ACM 978-1-4503-161 9/12/11. [6] G. P Perrucci, F.H Fiitzek, G Sasso, W. Kellerer and J. Widmer, ”On the impact of 2G and 3G network usagefor mobile phones’ battery life ”, In Proceedings of 15th European Conference of Mobile Services. (EWC2009). [7] T. Pering, Y. Agarwal, R. Gupta, R. Want, ”CoolSpots:Reducing the power consumption of wireless mobile devices with multiple radio interfaces”, In Proceedings of 4th International Conference of Mobile Services. (MobiSys 2006). [8] Lide Zhang, Mark S. Gordon, Robert P. Dick, Z. Morley Mao, Peter Dinda, Lei Yang, ”ADEL: An Automatic Detector of Energy Leaks for Android phone Applications”, Copyright 2012 ACM 978-14503-1426- 8/12/09.. CODES+ISSS12, October 712, 2012,Tampere, Finland. [9] Aleksandar Milenkovi, Armen Dzhagaryan, Martin Burtscher, ”Performance and Energy Consumption of Lossless Compression/Decompression Utilities on Mobile Computing Platforms”, IEEE 21st International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems. 2013. [10] Shuai Hao, Ding Li, William G. J. Halfond, Ramesh Govindan, ”Estimating Mobile Application Energy Consumption using Program Analysis”,ICSE 2013, San Francisco, USA, 978-1-4673-30763/13/2013.
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