Optimal sensor placement for bacteria detection in water distribution networks

The real-time detection of bacteria and other bio-pollutants in water distribution networks and the real-time control of the water quality is made possible by new biosensors. However, the limited communication capabilities of these sensors, which are placed underground, and their limited number, due to their high cost, pose significant challenges in the deployment and the reliable monitoring. This paper presents a preliminary study concerning the problem of the static optimal sensor placement of a wireless biosensor network in a water distribution network for real-time detection of bacterial contamination. An optimal sensor placement strategy is proposed, which maximizes the probability of detection considering a limited number of sensors while ensuring a connected communication topology. A lightweight algorithm that solves the optimal placement problem is developed. The performance of the proposed algorithm is evaluated through simulations, considering different network topologies using a water pipelines emulator. The results indicate that the proposed optimization outperforms more traditional approaches in terms of detection probability. It is concluded that the availability of a dynamic model of the bacterial propagation along with a spatio-temporal correlation of the process could lead to a more advanced real-time control of the water distribution networks.

[1]  Cynthia A. Phillips,et al.  Sensor Placement in Municipal Water Networks , 2003 .

[2]  Jameela Al-Jaroodi,et al.  Monitoring Underwater PIpelines Using Sensor Networks , 2010, 2010 IEEE 12th International Conference on High Performance Computing and Communications (HPCC).

[3]  Dimitri P. Bertsekas,et al.  Network optimization : continuous and discrete models , 1998 .

[4]  Ivan Stoianov,et al.  PIPENETa wireless sensor network for pipeline monitoring , 2007, IPSN.

[5]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[6]  Avi Ostfeld,et al.  Optimal Layout of Early Warning Detection Stations for Water Distribution Systems Security , 2004 .

[7]  Jianguo Chen,et al.  Adaptive fusion of correlated local decisions , 1998, IEEE Trans. Syst. Man Cybern. Part C.

[8]  Zoran Kapelan,et al.  Quo vadis water distribution model calibration? , 2009 .

[9]  Qi Wang,et al.  Optimal locations of monitoring stations in water distribution systems under multiple demand patterns: a flaw of demand coverage method and modification , 2012, Frontiers of Environmental Science & Engineering.

[10]  P.K. Varshney,et al.  Optimal Data Fusion in Multiple Sensor Detection Systems , 1986, IEEE Transactions on Aerospace and Electronic Systems.

[11]  L. Nachman,et al.  PIPENET: A Wireless Sensor Network for Pipeline Monitoring , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[12]  Carlo Fischione,et al.  Fast-Lipschitz optimization with wireless sensor networks applications , 2011, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks.

[13]  Zoran Kapelan,et al.  Risk-Based Sensor Placement for Contaminant Detection in Water Distribution Systems , 2010 .