Sensor Data Analysis and Management

5 Feature Detection and Extraction Techniques for Real-Time Student Monitoring in Sensor Data Environments

Dr. V. Saravanan, Dr (Ms). N. Shanmuga Priya

Department of Computer Applications (PG), Dr. SNS Rajalakshmi College of Arts and Science, Coimbatore, India

5.1 Introduction

The research mainly focuses on the potential of student motion behavior analysis. This study is conducted for the learning of repeated motion behavior with respect to the students (i.e., the frequently visited places and the paths taken between the places) and thereafter to show that it is possible to detect unusual behavior using the knowledge of frequent behavior [1]. The best example for this scenario is taking a wrong route and getting lost. An important objective of pervasive computing is to give accurate information about people behavior. It has a wide range of applications such as in medicine, security solutions, and student monitoring in educational campuses [2].

Computer vision is a technology in which complex and tiny sensors such as video cameras are used to capture human motion [3]. The detection of human motion is a promising area of research. Sensors that are embedded in wearable objects are attached to the body, which is studied for its patterns or behavior. The data generated are normally from GPS sensors. The need of the hour is to process these data using signal-processing methods and to recognize patterns of real-time human motion [4]. This chapter presents a novel framework using deep ...