Sensor placement optimization

In this work we address the problem of optimal sensor placement for a given region and task. An important issue in designing sensor arrays is the appropriate placement of the sensors such that they achieve a predefined goal. There are many problems that could be considered in the placement of multiple sensors. In this work we focus on the four problems identified by Horster and Lienhart:
– Given the number of sensors of one type and their specific parameters, determine their positions and poses in space such that coverage is maximized.
– Given several types of sensors, their parameters and specific costs as well as the maximum total price of the sensor array, determine the sensor types and positions/poses that maximize coverage in the given space.
– Given the fixed positions and respective types of a number of sensors determine their optimal poses such that coverage is maximized.
– Given a minimally required percentage of coverage determine the sensor array with minimum cost that satisfies this coverage constraint.
To solve these problems, we propose an algorithm based on Direct Search, which is able to approach the global optimal solution within reasonable time and memory consumption. The algorithm is experimentally evaluated and the results are presented on two real floorplans. The experimental results show that our DS algorithm is able to improve the results given by the most performing heuristic in the state of the art. The algorithm is then extended to work also on continuous solution spaces, and 3D problems.



Sensor Placement Optimization in Buildings
(Simone Bianco, Francesco Tisato) In Image Processing: Machine Vision Applications V, volume 8300, pp. 830003, SPIE, 2012.

 author = {Bianco, Simone and Tisato, Francesco},
 year = {2012},
 pages = {830003},
 title = {Sensor Placement Optimization in Buildings},
 volume = {8300},
 publisher = {SPIE},
 booktitle = {Image Processing: Machine Vision Applications V},
 pdf = {/download/bianco2012sensor-placement.pdf},
 doi = {10.1117/12.911021}}