Proceedings ArticleDOI
Actiotracker: A Smart Pedometer For Monitoring And Analyzing Physical Activities of School Children
TLDR
A way for concerned authorities in a school, to easily keep track of each student’s physical activity during school hours and give feedback accordingly is proposed.Abstract:
With an alarming increase in obesity levels, even among children and adolescents, there is a need to take steps for increasing their motivation and overall physical activity levels. This paper proposes a way for concerned authorities in a school, to easily keep track of each student’s physical activity during school hours and give feedback accordingly. The system uses a portable pedometer that includes a MPU6050 sensor module that uses an accelerometer and gyroscope to collect movement data from each student and stores it, via Wi-Fi communication on to the Thingspeak server. The system implements a k-NN algorithm that classifies the data for each student into activities of sitting, walking, running and cycling. The results of the analysis and feedback for each student are accessible through a web portal, hosted locally on a server located in the school premises.read more
Citations
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Proceedings ArticleDOI
GPS based Novel Approach for Secure Delivery of Online Purchased Items
TL;DR: In this article , the authors proposed a smart packing box that detects tampering with the parcel carrying the item and informs its seller and the buyer, which can be used for secure delivery of online purchased items.
Proceedings ArticleDOI
GPS based Novel Approach for Secure Delivery of Online Purchased Items
TL;DR: In this paper , the authors proposed a smart packing box that detects tampering with the parcel carrying the item and informs its seller and the buyer, which can be used for secure delivery of online purchased items.
References
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Journal ArticleDOI
Activity classification using realistic data from wearable sensors
TL;DR: Methods used for classification of everyday activities like walking, running, and cycling are described to find out how to recognize activities, which sensors are useful and what kind of signal processing and classification is required.
Journal ArticleDOI
Detection of Daily Activities and Sports With Wearable Sensors in Controlled and Uncontrolled Conditions
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Journal ArticleDOI
Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers
TL;DR: How human physical activity can be classified using on-body accelerometers, with a major emphasis devoted to the computational algorithms employed for this purpose, is discussed.
Journal ArticleDOI
Activity identification using body-mounted sensors — a review of classification techniques
Stephen J. Preece,John Y. Goulermas,Laurence Kenney,Dave Howard,Kenneth Meijer,Robin H. Crompton +5 more
TL;DR: This article reviews the different techniques which have been used to classify normal activities and/or identify falls from body-worn sensor data and illustrates the variety of approaches which have previously been applied.
Journal ArticleDOI
A Comparison of Feature Extraction Methods for the Classification of Dynamic Activities From Accelerometer Data
TL;DR: The findings show that, although the wavelet transform approach can be used to characterize nonstationary signals, it does not perform as accurately as frequency-based features when classifying dynamic activities performed by healthy subjects.