Structural Health Monitoring (SHM) techniques have undergone a paradigm shift due to new
emerging technologies and developments in the field of remote communications. The use of Wireless Sensor
Networks (WSN) has been on an increase in the last decade due to its low cost deployment, ease of maintenance
and increased efficiency. However, the battery life of the sensors of such networks is limited and hence
puts severe restrictions on the use of this technology. Thus there is a need to enhance the life time of the network
through optimizing the energy usage of sensors. Sensor placement for achieving network longevity
might lead to loss of vital information, thus making the sensor placement ineffective from the SHM perspective.
This paper focuses on optimizing the location of the sensors to cater to the specific requirements of structural
engineering while adhering to the energy limitations imposed due to the use of WSN. In this paper a minimization
problem is formulated first to optimize the number of sensors, and then Genetic Algorithm (GA) is
used to optimize the sensor location for detecting structural vibration responses for SHM. The GA employs a
fitness function that combines the determinant of Fisher Information Matrix (FIM) - an indicator of the information
quality and the maximum energy used by the sensor node. The approach has been verified on an FE
model of a long span bridge and compared with other optimal sensor placement principles in order to ascertain
its suitability and effectiveness.