Laser sensing in its many approaches is a key technology in multiple future applications, e.g. enabling the ubiquity of information generation expected for the Internet of Things. Most laser sensing techniques, however, become limited when multiple scattering media is present. There the laser beam loses partially its coherence, is depolarized, or becomes spread radiometrically degrading its performance as sensor. Such problem initially appeared in biophotonics, where the presence of highly scattering tissue complicates the laser sensing process. In tissue optics, statistical methods based on Monte Carlo (MC) and finite element (FEM) models are used to solve the radiative transfer equation (RTE) to model light propagation in scattering media. However, interoperable software tools which enable to combine the FEM and MC approaches, and the effect of macro and microscale events in electromagnetic fields have appeared in the last years, and may be applied to model scattering. Further, polarization effects in scattering media are already used qualitatively in imaging instruments (the dermatoscope) or in atmospheric lidar (characterization of clouds). In our past project of the Plan Nacional, we used MC methods to introduce depth-sectioning features to Optical Feedback Interferometry (OFI) sensors. Within this project, we will extend this know-how into the detailed solution of the RTE and depolarization events to time dependent signals (pulsed or modulated sources). The goal of the project is the quantification of depolarization and radiometric data in multiple scattering media to develop new laser sensing strategies, or to complement existing ones. From the theoretical point of view, novel tools will be used to build models of the interaction of laser light with multiple scattering media to predict the performance of the sensors of interest. Basic geometric models (flat surfaces and uniform media with multiple scatterers) will be used as starting point to understand the physics of real-world situations and get acquainted with the novel tools, and to validate the proposed models. A controlled experimental testbed for multiple scattering media (solids,fluids and gases) will be built to check the predictions of the models. The findings of the theoretical models will be used to build two proof-of-concept instruments targetting specific applications. A first one will implement a polarization-enhanced OFI sensor applied to the measurement of changes in parameters in a flowing fluid, to monitor flow of liquids and gases in multiple scattering media. This will be applied to the analysis of the state of conservation of blood bags or liquid aliments, such as milk. A second proof-of-concept will focus on the problems of lidar imagers in multiple scattering media, such as e.g dense fog, dust, smoke or rain. Lidar imagers are key technologies in the new generations of automated vehicles, and its behavior in harsh atmospheric conditions is a problem currently not solved. Laser pulses in scattering media are delayed and dispersed, affecting the reliability of the measurements, which may be quantified radiometrically. Besides, polarimetric measurements may identify the density and type of the scattering element in the environment. The application of the models to lidar imaging setups will contribute to improve the accuracy of the measurements and to widen the reliability of lidar imagers.