Benjamin Klotz

EURECOM · Data science department

How to understand better the knowledge provided by Google results to build future “smart vehicle-centric” applications? What is the knowledge expertise required to build a smart vehicle application (e.g., driver assistance system)? Automotive companies (e.g., Toyota, BMW, Renault) are employing Internet of Things (IoT) and Semantic Web technologies...

Modern vehicles produce big data with a wide variety of formats due to missing open standards. Thus, abstractions of such data in the form of descriptive labels are desired to facilitate the development of applications in the automotive domain. We propose an approach to reduce vehicle sensor data into semantic outcomes of dangerous driving events b...

The Web of Things offers a platform-independent solution for interacting with connected devices. An important vertical of the WoT is the transportation domain with, at its core, autonomous systems and among others, connected vehicles. They can be seen as complex artefacts , as they are composed of many sensors and actuators, legacy specifications a...

Modern vehicles are equipped with connectivity capabilities which will eventually open promising business opportunities. However , intelligent applications depend on high-quality and structured data which is difficult to obtain from the vehicle (i.e., several sensors, time-series data, different formats, etc.). Moreover, services and functions in t...

Application developers in the automotive domain have to deal with thousands of different signals, represented in highly heterogeneous formats, and coming from various car architectures. This situation prevents the development and connectivity of modern applications. We hypothesize that a formal model of car signals, in which the definition of signa...

We propose a car signal ontology named VSSo that provides a formal definition of the numerous sensors embedded in car regardless of the vehicle model and brand, re-using the work made by the GENIVI alliance with the Vehicle Signal Specification (VSS). We observe that recent progress in machine learning enables to predict a number of useful informat...

Car signal data is usually hard to access, understand and integrate for non automotive domain experts. In this paper, we use semantic technologies for enriching signal data in the automotive industry and access it through Web of Things interactions. This combination allows the access and integration of car data from the web. We built VSSo, a Vehicl...

In this paper, we use semantic technologies for enriching trajectory data in the automotive industry for offline analysis. We proposed to re-use a combination of existing ontologies and we designed a Vehicle Signal Specification ontology to provide an environment in which we developed an application that analyzes the variations of signal values and...

In this paper, we present the design and implementation of DrIveSCOVER, a recommender system for places and events in case of an in-car use, where the driving conditions such as weather and local traffic are taken into account. We integrate multiple data sources using semantic technologies and we devise recommending functions that are presented in...