Authors: Charles C. Castello; Ruei-Xi Chen; Jeffrey Fan; Asad Davari
Addresses: Applied Research Center, Florida International University, 10555 West Flagler Street, EC2100, C4-5, Miami, FL 33174, USA; Department of Electrical and Computer Engineering (ECE), Florida International University, 10555 West Flagler Street, EC3915, Miami, FL 33174, USA ' Computer Science and Information Engineering Department, St. John's University, 499, Section 4, Tam King Road, Tamsui, Taipei, Taiwan ' Department of ECE, Florida International University, 10555 West Flagler Street, EC3915, Miami, FL 33174, USA ' Department of ECE, West Virginia University Institute of Technology, 405 Fayette Pike, Montgomery, WV 25136, USA
Abstract: This paper introduces a temperature control framework for smart homes using wireless sensor networks (WSN). A key issue with temperature monitoring and control is standard sampling techniques which take few temperature samples into consideration to make heating and cooling decisions in large areas of space. This results in poor controllability of temperature in unmonitored locations with potentially significant temperature variations in comparison with monitored locations. To solve this problem, spatial analysis techniques, namely geostatistical analysis, can be utilised to predict temperature in unmonitored locations to aid in making more informed decisions on how to heat and cool certain parts of a dwelling. Results show independent temperature control in defined areas using the proposed temperature control framework.
Keywords: smart homes; intelligent temperature control; WSNs; wireless sensor networks; context awareness; geostatistical analysis; classical variography; ordinary point kriging; temperature monitoring; home heating; home cooling.
International Journal of Autonomous and Adaptive Communications Systems, 2013 Vol.6 No.2, pp.99 - 114
Available online: 29 Mar 2013 *Full-text access for editors Access for subscribers Purchase this article Comment on this article