The Experts below are selected from a list of 12006 Experts worldwide ranked by ideXlab platform
Ye Song-taob - One of the best experts on this subject based on the ideXlab platform.
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Shock Detection with Smart Mobile Phone and Its Application in Car Accident Self-rescue
Computer Engineering, 2011Co-Authors: Ye Song-taobAbstract:To address the shortcoming of relying on the car' own hardware in existing car accident self-rescue,this paper proposes an automatic alarm method based on Smart Mobile Phone.The method takes the acceleration sensing signal as sample input which reflects physical movement of Mobile Phone users,introduces frequency and time parameters to improve the existing methods of calculation of the threshold.It implements the prototype system on Symbian platform,which alarms to the rescue center automatically and real time,by taking advantage of Mobile-Phone camera and 3G Mobile Phone networks.Experimental results show that the method has better impact detection and energy saving effect.
Qin Xia - One of the best experts on this subject based on the ideXlab platform.
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methods in urban temporal and spatial behavior research in the big data era
Progress in geography, 2013Co-Authors: Qin XiaAbstract:The rapid development of information technology has taken us into the "Big Data Era",changed the organization and structure of urban space and residents' behavior,and also caused transformation of the methods in urban temporal and spatial behavior research.On the basis of summarizing the problems of traditional methods such as poor data accuracy,small sample size,weak continuity,and higher costs,this paper first combs through the data acquisition and processing technology for web data mining,residents' behavior data collection and analysis,and network map integration and visual development,which can affect the transformation of the research methods.Then it reviews the latest progress in applying big data to urban temporal and spatial behavior research at home and abroad from the perspectives of residents' behavior,urban space,and urban hierarchy,and builds up a method framework for urban temporal and spatial behavior research based on big data application.The methods in urban temporal and spatial behavior research are going through a great transformation because of the emergence of massive and various information data.Data collection methods have changed from yearbook statistics,social questionnaire survey,in-depth interview to mining of network data(social network data) and application of new spatial position technology(GPS,Smart Mobile Phone,LBS,etc.),and the data shows obviously new characteristics such as large sample size,real-time dynamic,micro and detail,with more attention paid to the extraction of residents' geographic position information.However,as to specific research methods,the traditional ones are still widely used,such as descriptive statistical analysis,cluster analysis,factor analysis,gravity model,network analysis,space-time prism,etc.Generally speaking,the researches of urban temporal and spatial behavior have obvious characteristics of using "new" data and "old" methods to study "newer" and "older" problems at the present stage,and their research scope has also expanded from residential scale to urban space and regional range.However,problems still exist with the current research,such as how to eliminate fictitious data,how to learn and innovate analytical methods,how to expand research field and embody characteristics of the era.Therefore,it is necessary to promote the cross and integration of related disciplines such as sociology,economic geography,cultural geography,tourism geography,computer science,mathematics and geographic information science,in order to find new analysis methods,and also reinforce the research of residents' behavior and urban space by using social network(Twitter,Flikr,Facebook,Sina Microblog,etc.) data or other web(SouFun.com,Dianping.com,Zhaopin.com,Taobao.com,etc.) data,and guide innovation of urban planning methods.
Maryam Shafiei - One of the best experts on this subject based on the ideXlab platform.
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Crowdsource mapping of target buildings in hazard: the utilization of SmartPhone technologies and geographic services
Applied Geomatics, 2019Co-Authors: Mohammad H. Vahidnia, Farhad Hosseinali, Maryam ShafieiAbstract:Volunteered geographical information (VGI) refers to geographical information that the general public voluntarily collects and shares in the environment instead of for-profit businesses or government entities. Crowdsourcing such information on urgent needs in a disaster can improve the quick emergency responses. This study incorporates the capability of SmartPhone sensors, GPS, Web 2.0, VGI, and server-based technologies to design and develop a system for collecting target hazard information from volunteers. One of the most important contributions in designing this system is considering the improvement of the positional accuracy of the target buildings based on the position of the Mobile device. Several approaches have been recommended for this purpose. The solutions include the use of online map services, geocoding services, and trigonometric methods based on the measurements of sensors such as camera, accelerometer, and magnetic field embedded in a Smart Mobile Phone. The accuracy assessment showed that the trigonometric method by the means of embedded sensors would yield the best result. However, geocoding is more economical in terms of time than other methods. Potentially, the evaluation of the Mobile application provided by a group of volunteers showed the overwhelming preference of crowdsource mapping over current telePhone communication systems in disaster management.
Wen-tsai Sung - One of the best experts on this subject based on the ideXlab platform.
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Employing cross-platform Smart home control system with IOT technology based
Proceedings - 2016 IEEE International Symposium on Computer Consumer and Control IS3C 2016, 2016Co-Authors: Kuang-yow Lian, Sung-jung Hsiao, Wen-tsai SungAbstract:The proposed method changes the original remote controller for home appliances become IOT (internet of things) technology-based and cross-platform control by the Smart Phone remote wireless control. In our research, Smart Phone will replace the traditional remote control operation. When the controller press Mobile Web App, in addition to the circuit module will emitting infrared signals, our hardware module will also upload information to the cloud database. Such an innovative approach would be able to provide accurate monitoring by real-time monitoring status and real-time analysis. In the proposed Smart home embedded system, data sent back from each sensor inside the household can be instantaneously analyzed, Furthermore, the use of Network Address Translation (NAT) technology to control remotely via the Internet. In terms of the construction process of the Smart factory system, this dissertation proposes an instantaneous method that carries out the monitoring of factory area temperature, humidity and air quality using Smart Mobile Phone. At the same time, the system detects potential flame, analyze and monitor power loading. These monitoring also include shock detection of operating machines in factory premises. The study proposes integrating ZigBee and Wi-Fi protocol Smart monitoring system in the structure of the whole factory. Via ZigBee communication Protocol, the sensors in the factory transmit messages and the instantaneously detected data to the integrated regulating system. Lastly, this research study will, in depth, analyse hands-on problems generated during instantaneous integration of signal packing for various communication protocols. As well as composing the know-how of overcoming these problems using the innovative methods of this study while proposing efficient solution schemes. The above become the greatest features in the building of this integrated regulation system.
Min Tang - One of the best experts on this subject based on the ideXlab platform.
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exploiting user experience from online customer reviews for product design
International Journal of Information Management, 2019Co-Authors: Bai Yang, Ying Liu, Yan Liang, Min TangAbstract:Abstract Understanding user experience (UX) becomes more important in a market-driven design paradigm because it helps designers uncover significant factors, such as user’s preference, usage context, product features, as well as their interrelations. Conventional means, such as questionnaire, survey and self-report with predefined questions and prompts, are used to collect information about users’ experience during various UX studies. However, such data is often limited and restricted by initial setups, and they won’t easily allow designers to identify all critical elements such as user profile, context, related product features, etc. Meanwhile, with widely accessible social media, the volume and velocity of customer-generated data are fast-increasing. While it is generally acknowledged that such data contains important elements in understanding and analyzing UX, extracting them to assist product design remains a challenging issue. In this study, how UX data underlying product design can be isolated and restored from customer online reviews is examined. A faceted conceptual model is proposed to elucidate the crucial factors of UX, which serves as an operational mechanism connecting to product design. A methodology of establishing a UX knowledge base from customer online reviews is then proposed to support UX-centered design activities, which consists of three stages, i.e., UX discovery to extract UX data from a single review, UX data integration to group similar data and UX network formalization to build up the causal dependencies among UX groups. Using a case study on Smart Mobile Phone reviews, examples of UX data discovered are demonstrated and both customers and designers concerned key product features and usage situations are exemplified. This study explores the feasibility to discover valuable UX data as well as their relations automatically for product design and business strategic plan by analyzing a large volume of customer online data.