Design of Environmental Sensor Networks Using Evolutionary Algorithms
Ferry Susanto, Setia Budi, Paulo Antônio de Souza Júnior, Ulrich Engelke, Jing He · IEEE Geoscience and Remote Sensing Letters · 2016
An evolutionary algorithm (EA)-assisted spatial sampling methodology is proposed to assist decision makers in sensor network (SN) deployments. We incorporated an interpolation technique with leave-one-out cross-validation (LOOCV) to assess the representativeness of a particular SN design. For the validation of our method, we utilized Tasmania's South Esk Hydrological Model developed by the Commonwealth Scientific and Industrial Research Organisation, which includes a range of environmental variables describing the landscape. We demonstrated that our proposed methodology is capable of assisting in the initial design of SN deployment. Ordinary Kriging is shown to be the best suited spatial interpolation algorithm for the EA's LOOCV under the current empirical study.