Luca Varotto; Alessandra Zampieri; Angelo Cenedese Street Sensor Set Selection through Map Segmentation and Observability Measures (Inproceedings) 2019. (Abstract | BibTeX | Tags: optimization, sensor networks, sensor selection) @inproceedings{Varotto2019street, title = {Street Sensor Set Selection through Map Segmentation and Observability Measures}, author = {Luca Varotto and Alessandra Zampieri and Angelo Cenedese }, year = {2019}, date = {2019-07-03}, journal = {Mediterranean Conference on Control and Automation 2019}, abstract = {Nowadays, vehicle flow monitoring, model-based traffic management, and congestion prediction are becoming fundamental elements for the realization of the Smart City paradigm. These tasks usually require wide sensor deployments, but, due to economical, practical, and environmental constraints, they must be accomplished with a limited number of sensors. Thus motivated, this work addresses the sensors selection problem for urban street monitoring, by employing a road map image as the basic information and considering the placement of at most one sensor along each road with a chosen number of available devices. To solve the problem, the concept of system observability is exploited as the criterium for optimal sensor placement, specifically related to the capability of estimating the traffic flow in each road using the available output measurements. In this framework, different integer non- linear programming problems are proposed, whose solutions are studied and analyzed by means of numerical simulations on a real case scenario.}, keywords = {optimization, sensor networks, sensor selection}, pubstate = {published}, tppubtype = {inproceedings} } Nowadays, vehicle flow monitoring, model-based traffic management, and congestion prediction are becoming fundamental elements for the realization of the Smart City paradigm. These tasks usually require wide sensor deployments, but, due to economical, practical, and environmental constraints, they must be accomplished with a limited number of sensors. Thus motivated, this work addresses the sensors selection problem for urban street monitoring, by employing a road map image as the basic information and considering the placement of at most one sensor along each road with a chosen number of available devices. To solve the problem, the concept of system observability is exploited as the criterium for optimal sensor placement, specifically related to the capability of estimating the traffic flow in each road using the available output measurements. In this framework, different integer non- linear programming problems are proposed, whose solutions are studied and analyzed by means of numerical simulations on a real case scenario. |
List of Publications
Street Sensor Set Selection through Map Segmentation and Observability Measures (Inproceedings) 2019. |