Indoor positioning system survey using BLE beacons

This project provides a survey of indoor positioning systems and reports experimental work with Bluetooth Low Energy (BLE) Beacons. A positioning algorithm based on the Received Signal Strength Index (RSSI) from Bluetooth Low Energy signals is proposed for indoor tracking of the position of a drone. Experimental tests for characterization of beacon signals are presented. The application of a Kalman filter to reduce the effect of fluctuations in beacons signals is described

Feasibility of Bluetooth iBeacons for indoor localization

Location-based services in buildings represent a great advantage for people to search places, products or people. In our paper we examine the feasibility of Bluetooth iBeacons for indoor localization. In the first part we define and evaluate the iBeacon technology through different experiments. In the second part our solution application is described. Our system is able to estimate the position of the user’s smartphone based on RSSI measurements. Therefore we used the built-in smartphone sensor and a building map with required sender information. Trilateration is used as positioning technique in contrast to fingerprinting to minimize beforehand effort. Results are promising but cannot reach the same accuracy level as sensor-fusion or fingerprinting approaches

Students' intention to use in-app advertisements in Pakistan

With the proliferation of smartphone apps, in-app advertisements (ads) have emerged as an important communication and financial tool. However, there are limited studies conducted in the developing countries on how app features in in-app ads influence students' intention to use in-app ads. Therefore, this research aims to examine the influence of perceived collaboration, perceived usefulness, and perceived financial benefits on students' intention to use in-app ads. The mediating roles of attitude and perceived usefulness and the moderating role of self-efficacy were also examined. The underpinning theory used in this study was the Technology Acceptance Model (TAM). Data were collected using the proportional stratified sampling technique among students from selected public universities in Pakistan. An online questionnaire was used for this purpose. Responses from 400 respondents were analyzed using the partial least squares-structural equation modelling (PLS-SEM) approach. The results revealed that the most significant factor influencing students' intentions to use in-app ads was their attitude. Other contributing factors were perceived financial benefits, perceived collaboration, and perceived usefulness. Apart from that, attitude and perceived usefulness showed mediation effects, while self-efficacy demonstrated no moderating effect. The findings conclude that advertisers should effectively use app features and consider the target market's attitude in order to influence their intention to use in-app ads. Advertisers and in-app service providers should collaborate and provide financial benefits to customers for increased business activity. This research has extended the findings on in-app ads from a developing country's perspective. The suggestions for future research are also discussed