TY - GEN
T1 - Just send me the summary! Analyzing sensor data for accurate summary reports in indoor environments
AU - Ko, Jeong Gil
AU - Park, Jongjun
AU - Jun, Jong Arm
AU - Kim, Naesoo
PY - 2012
Y1 - 2012
N2 - As the number of sensors increase in wireless sensing applications, it is important for nodes to provide meaningful summary reports of the original data to the gateway. In doing so, given the resource constraints of the sensing devices, we need a light weight, yet, effective scheme to minimize the number of reports at the sensors while preserving the accuracy of the original data. However, we show in this work that unlike outdoors environments where various sensors may show a similar phenomena (e.g., high spatial correlation), this may not be true for sensors deployed in a typical indoors environment. To resolve this issue, we introduce a data summarizing scheme for such indoor applications that combines two techniques. First, our scheme detects events in a data stream by comparing the short term mean of the recent measurements with the most recent report sent to the gateway. Second, we include an exponentially increasing/decreasing timer that triggers additional reports where the timer's interval is reconfigured dynamically with respect to the result of our event detection method. Evaluations with temperature and humidity data collected in an indoors environment indicate that our scheme significantly reduces the number of transmissions while maintaining a mean error as low as ≈0.07°C and ≈0.08%RH.
AB - As the number of sensors increase in wireless sensing applications, it is important for nodes to provide meaningful summary reports of the original data to the gateway. In doing so, given the resource constraints of the sensing devices, we need a light weight, yet, effective scheme to minimize the number of reports at the sensors while preserving the accuracy of the original data. However, we show in this work that unlike outdoors environments where various sensors may show a similar phenomena (e.g., high spatial correlation), this may not be true for sensors deployed in a typical indoors environment. To resolve this issue, we introduce a data summarizing scheme for such indoor applications that combines two techniques. First, our scheme detects events in a data stream by comparing the short term mean of the recent measurements with the most recent report sent to the gateway. Second, we include an exponentially increasing/decreasing timer that triggers additional reports where the timer's interval is reconfigured dynamically with respect to the result of our event detection method. Evaluations with temperature and humidity data collected in an indoors environment indicate that our scheme significantly reduces the number of transmissions while maintaining a mean error as low as ≈0.07°C and ≈0.08%RH.
UR - http://www.scopus.com/inward/record.url?scp=84873435270&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84873435270&partnerID=8YFLogxK
U2 - 10.1145/2426656.2426690
DO - 10.1145/2426656.2426690
M3 - Conference contribution
AN - SCOPUS:84873435270
SN - 9781450311694
T3 - SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems
SP - 325
EP - 326
BT - SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems
T2 - 10th ACM Conference on Embedded Networked Sensor Systems, SenSys 2012
Y2 - 6 November 2012 through 9 November 2012
ER -