TY - GEN
T1 - Opportunistic PM2.5 Sensing
T2 - 2017 IEEE Global Communications Conference, GLOBECOM 2017
AU - Mahajan, Sachit
AU - Liu, Hao Min
AU - Huang, Tzu Yu
AU - Tsai, Tzu Chieh
AU - Chen, Ling Jyh
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - In this paper, we present an energy, data and cost efficient model for mobile opportunistic PM2.5 sensing via bicycles. To facilitate the implementation of such systems, we first investigate the accuracy issue of different Inertial Monitoring Unit (IMU) built into the Arduino 101 for stop detection. Then, by curve fitting and optimization calculation on system parameter tuning and modeling, each sensor could start up at the optimum time in order to achieve minimum energy consumption and maximum data usability. Also we propose a formula that can count the minimum number of required PM2.5 sensors under the condition of total experiment time spent and total expected number of sampling point. Finally, we conduct a field experiment to evaluate the proposed model in a real world setting. The results show that total time spent of PM2.5 data collection is similar to the expected time derived from the system modeling.
AB - In this paper, we present an energy, data and cost efficient model for mobile opportunistic PM2.5 sensing via bicycles. To facilitate the implementation of such systems, we first investigate the accuracy issue of different Inertial Monitoring Unit (IMU) built into the Arduino 101 for stop detection. Then, by curve fitting and optimization calculation on system parameter tuning and modeling, each sensor could start up at the optimum time in order to achieve minimum energy consumption and maximum data usability. Also we propose a formula that can count the minimum number of required PM2.5 sensors under the condition of total experiment time spent and total expected number of sampling point. Finally, we conduct a field experiment to evaluate the proposed model in a real world setting. The results show that total time spent of PM2.5 data collection is similar to the expected time derived from the system modeling.
UR - http://www.scopus.com/inward/record.url?scp=85046496767&partnerID=8YFLogxK
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U2 - 10.1109/GLOCOM.2017.8254514
DO - 10.1109/GLOCOM.2017.8254514
M3 - Conference contribution
AN - SCOPUS:85046496767
T3 - 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
SP - 1
EP - 6
BT - 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 December 2017 through 8 December 2017
ER -
