Assessing Digital Surface Models by Verifying Shadows: A Sensor Network Approach

We propose to use wireless sensor networks to assess the accuracy and application of Digital Surface Models (DSM) for the study of shadowing and solar radiation over the built environment. Using the ability of sensor network data to provide information about solar radiation and predicting the exact time of the day that the Sun starts radiating a sensor, a comparative study and statistical analysis can be undertaken in order to evaluate the accuracy of the DSM for shadowing and radiation studies using image processing techniques. Two DSMs of the EPFL campus with different cell resolutions (1 meter and 0.5 meters), considering only information about ground, buildings with vertical walls and trees, are constructed step by step and employed. Three DSMs of the same campus with a cell resolution of 1 meter derived from raw LIDAR data and common interpolation techniques, such as Triangulated Irregular Network (TIN), kriging, Inverse Distance Weighting (IDW), are also used for comparison.

Digital Urban Morphometrics: Automatic Extraction and Assessment of Morphological Properties of Buildings

François Golay, Claudio Magalhaes Carneiro

The aim of this article is to present a method to calculate the morphological properties of the built environment using LiDAR (light-detection and ranging) data, geographic information systems (GIS) data and three-dimensional (3D) models of cities as a source of information. A hybrid approach that takes into account different types of inputs and consequently evaluates the accuracy of each type of used data is presented. This work is intended to give a first response to the lack of comprehensive and accurate procedure that uses LiDAR data in order to automatically derive precise morphological properties, such as volumes and surfaces (façades and roofs) of buildings. The method was tested on two case-study areas in the Geneva region with different characteristics, one in the old town along the Rhone River and the other on the CERN campus. A statistical analysis that compares the results of the computation with the 3D model of the built environment was used to validate the results, complemented by significance statistical tests. Outcomes showed that the proposed method to derive morphological properties can reach high levels of accuracy, thus enhancing the potential uses of LiDAR data for numerous applications, typically for the assessment of the urban environmental quality (UEQ) at the city and district scale, such as the estimation of the potential deployment of renewable energies in the built environment and the determination and monitoring of several urban indicators.

Wiley-Blackwell2010

Analysis of information processing in the olfactory bulb by in vivo experiments and theoretical modelling

Brice Bathellier

Much information is conveyed to animals by the diverse molecules propagated in their environment. This information is transmitted and treated within the olfactory system to be utilized by the rest of the brain. In this process, the sensory flow arriving from the nose first encounters the olfactory bulb. This thesis studies different aspects of the encoding and treatment of olfactory information in the bulb by a combination of experimental and theoretical approaches. The olfactory bulb consists of two functional stages: an input stage where the nerve terminals from the sensory neurons of the nose are spatially arranged in a precise manner, and an output stage corresponding to the neurons which propagate the processed information towards the more central brain areas. The first part of this thesis is focused on the development of an image processing technique to precisely map the input stage. In a second part, output neurons activity in responsive areas of the bulb was recorded in anaesthetized mice. The data obtained indicate complex dynamics in neural activity on several time scales. We show that the combination of mean firing rates from a large enough ensemble of neurons allows to accurately predict the odor presented to the animal. We also show that temporal variables related to the dynamics give very little information complementary to the ensemble rate code, suggesting that these variables are not read by brain structures downstream to the bulb. In a third part, we developed a numerical model of the olfactory bulb to understand its fast oscillatory dynamics. The model proposes a mechanism based on the negative feedback from the interneurons that regulate output neurons. Some predictions of the model are checked experimentally. An analytical interpretation of the model is also proposed and its generalization to the analysis of fast oscillation in other parts of the brain is discussed.

EPFL2007

Identity Aware Sensor Networks

Suhas Diggavi, Christina Fragouli, Mahdi Jafari Siavoshani, Lorenzo Keller

In a significant class of sensor-network applications, the identities of the reporting sensors are an essential part of the reported information. For instance, in environmental monitoring, the goal is to reconstruct physical quantities over space and time; these quantities are sampled by the sensors, and the source identity associated with each measurement is necessary for the spatial and temporal reconstruction. In many practical scenarios, source identities constitute the bulk of the communicated data, whereas the message itself can be as small as a single bit. In these scenarios, the traditional network-protocol paradigm of separately specifying the source identity and the message in distinct fields leads to inefficient communication. In this paper, we re-examine this traditional data separation and propose a scheme for joint identity-message encoding; we use this scheme to design a new efficient collection protocol for identity-aware sensor networks. Compared to conventional data collection, our protocol reduces the amount of traffic in the network at least by a factor of two (up to an order of magnitude, in lossy environments), while its performance scales better with network complexity; we show these results both through theoretical analysis and extensive simulations.

2008

Analysis of information processing in the olfactory bulb by in vivo experiments and theoretical modelling

Brice Bathellier

EPFL2007