scholarly journals Classroom Attendance Systems Based on Bluetooth Low Energy Indoor Positioning Technology for Smart Campus

Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 329 ◽  
Author(s):  
Apiruk Puckdeevongs ◽  
N. K. Tripathi ◽  
Apichon Witayangkurn ◽  
Poompat Saengudomlert

Student attendance during classroom hours is important, because it impacts the academic performance of students. Consequently, several universities impose a minimum attendance percentage criterion for students to be allowed to attend examinations; therefore, recording student attendance is a vital task. Conventional methods for recording student attendance in the classroom, such as roll-call and sign-in, are an inefficient use of instruction time and only increase teachers’ workloads. In this study, we propose a Bluetooth Low Energy-based student positioning framework for automatically recording student attendance in classrooms. The proposed architecture consists of two components, an indoor positioning framework within the classroom and student attendance registration. Experimental studies using our method show that the Received Signal Strength Indicator fingerprinting technique that is used in indoor scenarios can achieve satisfactory positioning accuracy, even in a classroom environment with typically high signal interference. We intentionally focused on designing a basic system with simple indoor devices based on ubiquitous Bluetooth technology and integrating an attendance system with computational techniques in order to minimize operational costs and complications. The proposed system is tested and demonstrated to be usable in a real classroom environment at Rangsit University, Thailand.

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 136858-136871
Author(s):  
Lu Bai ◽  
Fabio Ciravegna ◽  
Raymond Bond ◽  
Maurice Mulvenna

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 215173-215191
Author(s):  
Haiyun Yao ◽  
Hong Shu ◽  
Xinlian Liang ◽  
Hongji Yan ◽  
Hongxing Sun

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4550 ◽  
Author(s):  
Vasilis Stavrou ◽  
Cleopatra Bardaki ◽  
Dimitris Papakyriakopoulos ◽  
Katerina Pramatari

This paper has developed and deployed a Bluetooth Low Energy (BLE) beacon-based indoor positioning system in a two-floor retail store. The ultimate purpose of this study was to compare the different indoor positioning techniques towards achieving efficient position determination of moving customers in the retail store. The innovation of this research lies in its context (the retail store) and the fact that this is not a laboratory, controlled experiment. Retail stores are challenging environments with multiple sources of noise (e.g., shoppers’ moving) that impede indoor localization. To the best of the authors’ knowledge, this is the first work concerning indoor localization of consumers in a real retail store. This study proposes an ensemble filter with lower absolute mean and root mean squared errors than the random forest. Moreover, the localization error is approximately 2 m, while for the random forest, it is 2.5 m. In retail environments, even a 0.5 m deviation is significant because consumers may be positioned in front of different store shelves and, thus, different product categories. The more accurate the consumer localization, the more accurate and rich insights on the customers’ shopping behavior. Consequently, retailers can offer more effective customer location-based services (e.g., personalized offers) and, overall, better consumer localization can improve decision making in retailing.


2019 ◽  
Vol 9 (19) ◽  
pp. 4081 ◽  
Author(s):  
Marcin Kolakowski

One of the functionalities which are desired in Ambient and Assisted Living systems is accurate user localization at their living place. One of the best-suited solutions for this purpose from the cost and energy efficiency points of view are Bluetooth Low Energy (BLE)-based localization systems. Unfortunately, their localization accuracy is typically around several meters and might not be sufficient for detection of abnormal situations in elderly persons behavior. In this paper, a concept of a hybrid positioning system combining typical BLE-based infrastructure and proximity sensors is presented. The proximity sensors act a supporting role by additionally covering vital places, where higher localization accuracy is needed. The results from both parts are fused using two types of hybrid algorithms. The paper contains results of simulation and experimental studies. During the experiment, an exemplary proximity sensor VL53L1X has been tested and its basic properties modeled for use in the proposed algorithms. The results of the study have shown that employing proximity sensors can significantly improve localization accuracy in places of interest.


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