Development of human presence detection system using received signal strength indicator of wireless sensor network /
This thesis presents a novel method to detect human presence based on the Received Signal Strength Indicator (RSSI) without using additional sensors. Wireless Sensor Network (WSN) is an enabling technology for Internet of Things (IoT). This technology is widely used in many applications sucs as smar...
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| フォーマット: | 学位論文 図書 |
| 言語: | English |
| 出版事項: |
Perlis, Malaysia
School of Computer and Communication Engineering , Universiti Malaysia Perlis
2015
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| 100 | 0 | |a Jamie Siregar Cynthia Turner, |e author | |
| 245 | 1 | 0 | |a Development of human presence detection system using received signal strength indicator of wireless sensor network / |c Jamie Siregar Cynthia Turner |
| 264 | 1 | |a Perlis, Malaysia |b School of Computer and Communication Engineering , Universiti Malaysia Perlis |c 2015 | |
| 300 | |a xx, 125 pages |b colour illustration |c 30 cm. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a unmediated |b n |2 rdamedia | ||
| 338 | |a volume |b nc |2 rdacarrier | ||
| 502 | |a Thesis (Master of Science in Computer Engineering) - - Universiti Malaysia Perlis. School of Computer and Communication Engineering 2015. | ||
| 504 | |a Includes bibliographical references. | ||
| 520 | |a This thesis presents a novel method to detect human presence based on the Received Signal Strength Indicator (RSSI) without using additional sensors. Wireless Sensor Network (WSN) is an enabling technology for Internet of Things (IoT). This technology is widely used in many applications sucs as smart home control, assisted healthcare and security control that transforms ordinary devices into smart 'things'. It is expected by 2020, 30 billion of devices are connected wirelessly to the internet. | ||
| 541 | |a Gift from Centre for Graduate Studies (Master of Science - Computer Engineering ) |d 2017 | ||
| 650 | 0 | |a Sensor networks. | |
| 650 | 0 | |a Internet of things. | |
| 710 | 2 | |a Universiti Malaysia Perlis | |
| 720 | |a Dr. Latifah Munirah Kamarudin, |e supervisor | ||
| 790 | 1 | |a School of Computer and Communication Engineering | |
| 791 | 1 | |a Master of Science | |
| 792 | 1 | |a 2015 | |
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