Android App for Women Safety

The usage of smart phones equipped with GPS navigation unit have increased rapidly from 3% to more than 20% in the past five years. Hence, a smart phone can be used efficiently for personal safety or various other protection purposes especially for women. This app can be activated by a single click when the user feels she is in danger. This application communiqués the user’s location to the registered contacts for every few seconds in the form of message. Thus, it acts like a sentinel following behind the person till the user feels she is safe. This paper presents analysis a unique feature of this application to send the message to the registered contacts continuously till they are pressing ‘HELP’ button. Continuous location tracking information via SMS helps to find the location of the victim quickly and can be rescued safely. This application aims to ensure women safety. This is achieved by addressing the circumstances that compromise the safety of women in today’s day and age. This app ensures women are not put into such situations through various features offered by our system.

An App-Assisted Travel Survey in Official Statistics: Possibilities and Challenges

Advances in smartphone technology have allowed for individuals to have access to near-continuous location tracking at a very precise level. As the backbone of mobility research, the Travel Diary Study, has continued to offer decreasing response rates over the years, researchers are looking to these mobile devices to bridge the gap between self-report recall studies and a person’s underlying travel behavior. This article details an open-source application that collects real-time location data which respondents may then annotate to provide a detailed travel diary. Results of the field test involving 674 participants are discussed, including technical performance, data quality and response rate.

Tracking via Geotagged Social Media Data

Over the past twenty years, social media has changed the ways in which we plan, travel and reflect on our travels. Tourists use social media while travelling to stay in touch with friends and family, enhance their social status (Guo et al., 2015); and assist others with decision making (Xiang and Gretzel, 2010; Yoo and Gretzel, 2010). They also use it to report back to their friends and family where they are. This can be done using a geotag function that provides a location for where a post is made. While little is known about why tourists choose to geotag their social media posts, Chung and Lee (2016) suggest that geotags may be used in an altruistic manner by tourists, in order to provide information, and because they elicit a sense of anticipated reward. What is known, however, is that the function offers researchers the ability to understand where tourists travel. There are two types of geotagged social media data. The first of these is discussed in this chapter and may be defined as single point geo-referenced data – geotagged social media posts whose release is chosen by the user. This includes data gathered from social media apps such as Facebook, Instagram, Twitter and WeiChat. The method of obtaining this data involves the collation of large numbers of discrete geotagged updates or photographs. Data can be collated via an application programming interface (API) provided by the app developer to researchers, by automated data scraping via computer programs, perhaps written in Python, or manually by researchers. The second type of data is continuous location-based data from applications that are designed to track movement constantly, such as Strava or MyFitnessPal. Tracking methods using this continuous location-based data are discussed in detail in the following chapter.

Virtual By-passing of Query Server for Privacy of Users for Continuous Location Based Services

Location Based Services anticipate that customers should continually report their zone to a possibly untrusted server to get organizations reliant on their territory, which can open them to security risks. Tragically, existing security defending strategies for LBS have a couple of requirements, for instance, requiring a totally trusted in outcast, offering confined insurance confirmations and realizing high correspondence overhead. In this errand, A customer portrayed security organize structure called dynamic grid system (DGS) is proposed; the important sweeping structure that fulfills four central requirements for insurance shielding delineation and industrious LBS. The structure just requires a semi-trusted in outcast, at risk for doing clear planning undertakings viably. This semi-accepted pariah doesn't have any information about a customer's region. Secure delineation and steady zone assurance is guaranteed under the described enemy models. The correspondence cost for the customer doesn't depend upon the customer's optimal insurance level, it just depends upon the amount of huge central focuses in the area of the customer. Notwithstanding the way that the consideration is on range and k-nearest neighbor requests in this work, This structure can be easily connected with assistance other spatial inquiries without changing the estimations run by the semi-trusted in outcast and the database server, gave the essential interest an area of a spatial request can be engrossed into spatial regions. Experimental results show that the DGS is more productive than the best in class protection saving strategy for LBS.