There is a growing appreciation of the importance in developed societies of networks (or lifelines) of various kinds, such as water supply, energy supply, sewage disposal, communication and of course transportation. Monitoring and analyzing those big spatiotemporal data is vital importance of the planning and management in smart city. Sensors as the main means to supply such information become growing critical in the modern computational intelligence. With the limited budget, the problem of how to optimally locate sensors on a network is our focus.
- Flow Observability problem:
Increase the coverage by exact link inference. - Flow Estimation problem:
Improve the quality of flows estimates. - Flow Prediction Problem:
- Gentili, Monica and Pitu B. Mirchandani. “Survey of Models to Locate Sensors to Estimate Traffic Flows.” Transportation Research Record 2243 (2011): 108 - 116.
- Gentili, M. and P. Mirchandani. “Locating sensors on traffic networks: Models, challenges and research opportunities.” (2012).
- Castillo, E. et al. “A State-of-the-Art Review of the Sensor Location, Flow Observability, Estimation, and Prediction Problems in Traffic Networks.” (2015).
- Gentili, M. and P. Mirchandani. “Review of optimal sensor location models for travel time estimation.” Transportation Research Part C-emerging Technologies 90 (2018): 74-96.