Human centric sensing by Android phones

The main objective of this project is to perform human centric sensing on Android smartphones. Nowadays, Android smartphones provide several built-in sensors that can monitor the user’s location as well as motion. This project aims to create an Android application which makes use of these sensors to...

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Main Author: Lee, Janice Jia Cin
Other Authors: Luo Jun
Format: Final Year Project
Language:English
Published: 2015
Subjects:
Online Access:http://hdl.handle.net/10356/62684
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-626842023-03-03T20:24:22Z Human centric sensing by Android phones Lee, Janice Jia Cin Luo Jun School of Computer Engineering Centre for Multimedia and Network Technology DRNTU::Engineering::Computer science and engineering The main objective of this project is to perform human centric sensing on Android smartphones. Nowadays, Android smartphones provide several built-in sensors that can monitor the user’s location as well as motion. This project aims to create an Android application which makes use of these sensors to track users’ location. This application will start queue detection when user is located in a queue potential area such as canteen or supermarket. A location detector service is implemented for controlling start and end of queue detector. This service uses two layers of detection; location sensing and Wi-Fi sensing to monitor the user’s visits to the canteen. Location sensing makes use of GPS and network provider to check if user is near to the location while the Wi-Fi sensing uses BSSID of access points to verify if user is in the location. Results show that the application has a detection rate of 100%. Location detector service took a maximum of 18 seconds to start the queue detector after the user step into the canteen and took less than a minute to detect user leaving the canteen. Current application implementation requires manual learning of nearby WAP BSSIDS. Recommendation include automated learning of BSSID to include other locations, more energy efficient location detector and exploration in in areas other than queuing for food. Bachelor of Engineering (Computer Science) 2015-04-27T04:49:54Z 2015-04-27T04:49:54Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/62684 en Nanyang Technological University 32 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Lee, Janice Jia Cin
Human centric sensing by Android phones
description The main objective of this project is to perform human centric sensing on Android smartphones. Nowadays, Android smartphones provide several built-in sensors that can monitor the user’s location as well as motion. This project aims to create an Android application which makes use of these sensors to track users’ location. This application will start queue detection when user is located in a queue potential area such as canteen or supermarket. A location detector service is implemented for controlling start and end of queue detector. This service uses two layers of detection; location sensing and Wi-Fi sensing to monitor the user’s visits to the canteen. Location sensing makes use of GPS and network provider to check if user is near to the location while the Wi-Fi sensing uses BSSID of access points to verify if user is in the location. Results show that the application has a detection rate of 100%. Location detector service took a maximum of 18 seconds to start the queue detector after the user step into the canteen and took less than a minute to detect user leaving the canteen. Current application implementation requires manual learning of nearby WAP BSSIDS. Recommendation include automated learning of BSSID to include other locations, more energy efficient location detector and exploration in in areas other than queuing for food.
author2 Luo Jun
author_facet Luo Jun
Lee, Janice Jia Cin
format Final Year Project
author Lee, Janice Jia Cin
author_sort Lee, Janice Jia Cin
title Human centric sensing by Android phones
title_short Human centric sensing by Android phones
title_full Human centric sensing by Android phones
title_fullStr Human centric sensing by Android phones
title_full_unstemmed Human centric sensing by Android phones
title_sort human centric sensing by android phones
publishDate 2015
url http://hdl.handle.net/10356/62684
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