title: A deployment of fine-grained sensor network and empirical analysis of urban temperature.
abstract: Temperature in an urban area exhibits a complicated pattern due to complexity of infrastructure. Despite geographical proximity, structures of a group of buildings and streets affect changes in temperature. To investigate the pattern of fine-grained distribution of temperature, we installed a densely distributed sensor network called UScan. In this paper, we describe the system architecture of UScan as well as experience learned from installing 200 sensors in downtown Tokyo. The field experiment of UScan system operated for two months to collect long-term urban temperature data. To analyze the collected data in an efficient manner, we propose a lightweight clustering methodology to study the correlation between the pattern of temperature and various environmental factors including the amount of sunshine, the width of streets, and the existence of trees. The analysis reveals meaningful results and asserts the necessity of fine-grained deployment of sensors in an urban area.
authors.affiliation: School of Science and Technology for Future Life, Tokyo Denki University, 501 Daikou Building, 2-5 Kanda-Nishikichou, Chiyoda, Tokyo, 101-0054, Japan. wat@u-netlab.jp
authors.forename: Niwat
authors.initials: N
authors.lastname: Thepvilojanapong
authors.forename: Takahiro
authors.initials: T
authors.lastname: Ono
authors.forename: Yoshito
authors.initials: Y
authors.lastname: Tobe
mesh_terms: D002947:Cities; D016000:Cluster Analysis; D004784:Environmental Monitoring / Q000295:instrumentation* / Q000379:methods; D058998:Remote Sensing Technology / Q000295:instrumentation*; D013472:Sunlight; D013696:Temperature; D013821:Thermometers; D014041:Tokyo; D014197:Trees