This repository includes our works on Forecasting fine-grained sensing coverage in opportunistic vehicular sensing, consisting of two parts: a deep learning model of forecasting fine-grained sensing coverage (FiSC) and vehicle selection algorithm.
- FiSC model integrates the task requirement and coarse-grained information of candidate vehicles with a deep learning model to forecast fine-grained sensing coverage of OVS.
- Vehicle selection algorithm combines the genetic algorithm and the proposed FiSC to maximize sensing quality for a given sensing task.
A demo is provided for each part (FiSC model and Vehicle selection algorithm).