Quantifying the Spatio-Temporal Potential of Drive-by Sensing in Smart Cities

References

• A. Anjomshoaa, F. Duarte, D. Rennings, T. J. Matarazzo, P. deSouza, and C. Ratti, “City Scanner: Building and Scheduling a Mobile Sensing Platform for Smart City Services,” IEEE Internet of Things Journal 5: 6 (2018) 4567–4579. doi: 10.1109/JIOT.2018.2839058
   Web of Science ®Google Scholar
• F. Aurenhammer, “Voronoi Diagrams: A Survey of a Fundamental Geometric Data Structure,” ACM Computing Surveys (CSUR) 23: 3 (1991) 345–405. doi: 10.1145/116873.116880
   Web of Science ®Google Scholar
• R. Bhoraskar, N. Vankadhara, B. Raman, and P. Kulkarni, “Wolverine: Traffic and Road Condition Estimation Using Smartphone Sensors,” paper presented at the Fourth International Conference on Communication Systems and Networks (Bangalore, January 3, 2012).
   Google Scholar
• N. Biggs, E.K. Lloyd, and R.J. Wilson, Graph Theory 1736-1936 (New York: Oxford University Press, 1986).
   Google Scholar
• G. Boeing, “Planarity and Street Network Representation in Urban form Analysis,” Environment and Planning B: Urban Analytics and City Science (2018) <https://doi.org/10.1177/2399808318802941> Accessed May 22, 2020.
   Google Scholar
• G. Bruno, A. Genovese, and G. Improta, “Routing Problems: A Historical Perspective,” Journal of the British Society for the History of Mathematics 26: 2 (2011) 118–127.
   Google Scholar
• P. deSouza, A. Anjomshoaa, F. Duarte, R. Kahn, P. Kumar, and C. Ratti, “Air Quality Monitoring Case Study Using Mobile Low-cost Sensors mounted on Trash-Trucks: Methods Development and Lessons Learned,” Sustainable Cities and Society (2020) <https://doi.org/10.1016/j.scs.2020.102239>.
   Web of Science ®Google Scholar
• L. Deville Cavellin, S. Weichenthal, R. Tack, M. S. Ragettli, A. Smargiassi, and M. Hat-zopoulou, “Investigating the Use of Portable Air Pollution Sensors to Capture the Spatial Variability of Traffic-related Air Pollution,” Environmental Science & Technology 50: 1 (2015) 313–320. doi: 10.1021/acs.est.5b04235
   PubMed Web of Science ®Google Scholar
• R. Du, P. Santi, M. Xiao, A. V. Vasilakos, and C. Fischione, “The Sensable City: A Survey on the Deployment and Management for Smart City Monitoring,” IEEE Communications Surveys & Tutorials 21: 2 (2018) 1533–1560. doi: 10.1109/COMST.2018.2881008
   Web of Science ®Google Scholar
• J. Edmonds and E. L. Johnson, “Matching, Euler Tours and the Chinese Postman,” Mathematical Programming 5: 1 (1973) 88–124. doi: 10.1007/BF01580113
   Google Scholar
• H. A. Eiselt, M. Gendreau, and G. Laporte, “Arc Routing Problems, Part i: The Chinese Postman Problem,” Operations Research 43: 2 (1995) 231–242. doi: 10.1287/opre.43.2.231
   Web of Science ®Google Scholar
• M. Kwan, “Graphic Programming Using Odd or Even points,” Chinese Mathematics 1 (1962) 273–277.
   Google Scholar
• L. Li, J. Gong, and J. Zhou, “Spatial Interpolation of Fine Particulate Matter Concentrations Using the Shortest Wind-field Path Distance,” PloS One 9: 5 (2014) e96111. doi: 10.1371/journal.pone.0096111
   PubMed Web of Science ®Google Scholar
• X. Li, W. Shu, M. Li, H.-Y. Huang, P.-E. Luo, and M.-Y. Wu, “Performance Evaluation of Vehicle-based Mobile Sensor Networks for Traffic Monitoring,” IEEE Transactions on Vehicular Technology 58: 4 (2008) 1647–1653.
   Web of Science ®Google Scholar
• Y. Lu, Y. Zhang, Y. Cao, J. G. McDaniel, and M. L. Wang, “A Mobile Acoustic Subsurface Sensing (MASS) System for Rapid Roadway Assessment,” Sensors 13: 5 (2013) 5881–5896. doi: 10.3390/s130505881
   PubMed Web of Science ®Google Scholar
• G. R. McKercher, J. A. Salmond, and J. K. Vanos, “Characteristics and Applications of Small, Portable Gaseous Air Pollution Monitors,” Environmental Pollution 223 (2017) 102–110. doi: 10.1016/j.envpol.2016.12.045
   PubMed Web of Science ®Google Scholar
• K. P. O’Keeffe, A. Anjomshoaa, S. H. Strogatz, P. Santi, and C. Ratti, “Quantifying the Sensing Power of Vehicle Fleets,” Proceedings of the National Academy of Sciences 116: 26 (2019) 12752–12757. doi: 10.1073/pnas.1821667116
   PubMed Web of Science ®Google Scholar
• C. H. Papadimitriou, “On the Complexity of Edge Traversing,” Journal of the ACM 23: 3 (1976) 544–554. doi: 10.1145/321958.321974
   Web of Science ®Google Scholar
• F. Pasqualetti, J. W. Durham, and F. Bullo, “Cooperative Patrolling via Weighted Tours: Performance Analysis and Distributed Algorithms,” IEEE Transactions on Robotics 28: 5 (2012) 1181–1188. doi: 10.1109/TRO.2012.2201293
   Web of Science ®Google Scholar
• Y. Ramos, B. St-Onge, J.-P. Blanchet, and A. Smargiassi, “Spatio-temporal Models to Estimate Daily Concentrations of Fine Particulate Matter in Montreal: Kriging with External Drift and Inverse Distance-weighted Approaches,” Journal of Exposure Science and Environmental Epidemiology 26: 4 (2016) 405–414, <https://doi.org/10.1038/jes.2015.79>.
   PubMed Web of Science ®Google Scholar
• A. Rosenfeld, M. Dorman, J. Schwartz, V. Novack, A. C. Just, and I. Kloog, “Estimating Daily Minimum, Maximum, and Mean Near Surface Air Temperature Using Hybrid Satellite Models Across Israel,” Environmental Research 159 (2017) 297–312. doi: 10.1016/j.envres.2017.08.017
   PubMed Web of Science ®Google Scholar
• S. Vardoulakis, N. Gonzalez-Flesca, B. E. Fisher, and K. Pericleous, “Spatial Variability of Air Pollution in the Vicinity of a Permanent Monitoring Station in Central Paris,” Atmospheric Environment 39: 15 (2005) 2725–2736. doi: 10.1016/j.atmosenv.2004.05.067
   Web of Science ®Google Scholar
• M. Wang, R. Birken, and S. S. Shamsabadi, “Framework and Implementation of a Continuous Network-wide Health Monitoring System for Roadways,” paper presented at the SPIE Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security (San Diego, California, March 8, 2014).
   Google Scholar
• C. K. Wikle and J. A. Royle, “Space: Time Dynamic Design of Environmental Monitoring Networks,” Journal of Agricultural, Biological, and Environmental Statistics 4: 4 (1999) 489–507. doi: 10.2307/1400504
   Web of Science ®Google Scholar