| KEYWORD |
Prediction of Mobility Trajectories and Optimal Sensor Placement
Thesis in external company
Reference persons FABRIZIO DABBENE
Description The prediction of mobility trajectories plays a crucial role in various domains such as urban planning, transportation management, and resource allocation. In addition to accurate prediction, the optimal placement of sensors is essential to capture reliable data for modeling and analysis. This thesis proposal aims to develop a comprehensive framework that combines neural networks for mobility trajectory prediction and optimization techniques for sensor placement.
Objectives:
a) Develop a neural network-based model for predicting mobility trajectories using historical data, considering various factors such as location, time-dependent variables, and external influences.
b) Investigate the impact of different input features on the accuracy of trajectory predictions and identify the most informative features.
c) Incorporate optimization techniques to determine the optimal placement of sensors for data collection, maximizing the coverage and effectiveness of the sensor network.
d) Evaluate the performance of the proposed framework by comparing it with existing methods, both in terms of trajectory prediction accuracy and sensor placement effectiveness.
See also cnr - thesis proposal on prediction of mobility trajectories.pdf
Deadline 18/07/2024
PROPONI LA TUA CANDIDATURA