SALT: a Simple Application Logic description using Transducers for Internet of Things

International audienceAs the Internet of Things (IoT) grows in interest from both research and industrial parts, the lack of standard solutions to quickly and easily build and install IoT applications becomes a topic of high interest. In this paper, we introduce a language called SALT (Simple Application Logic description using Transducers) that allows describing and deploying the distributed logic needed in order to fulfil a complete desired application. This language aims at giving extended functionalities by filling the gap between the logical capabilities offered by services orchestration and the closeness efficiency of services choreography. SALT is interpreted by a virtual machine running on devices that introduces an abstraction layer in order to simplify access to hardware capabilities. SALT implements several mechanisms to comply with organisation issues presented in the Services Oriented Computing realm dealing with Services interactions, adapted to the specific constraints of the IoT. This work details SALT's concepts, formalism and implementation

investigations en vue de la maîtrise de la qualité de l'air : la gestion du risque

La loi Lepage ne comble que partiellement un retard pris dans le domaine de la régulation environnementale de l'air. La loi est plus une loi d'équipement et d'administration de la crise qu'une loi de gestion des risques

Study of the atmospheric refraction in a single mode instrument - Application to AMBER/VLTI

International audienceThis paper presents a study of the atmospheric refraction and its effect on the light coupling efficiency in an instrument using single-mode optical fibers. We show the analytical approach which allowed us to assess the need to correct the refraction in J- and H-bands while observing with an 8-m Unit Telescope. We then developed numerical simulations to go further in calculations. The hypotheses on the instrumental characteristics are those of AMBER (Astronomical Multi BEam combineR), the near infrared focal beam combiner of the Very Large Telescope Interferometric mode (VLTI), but most of the conclusions can be generalized to other single-mode instruments. We used the software package caos (Code for Adaptive Optics Systems) to take into account the atmospheric turbulence effect after correction by the ESO system MACAO (Multi-Application Curvature Adaptive Optics). The opto-mechanical study and design of the system correcting the atmospheric refraction on AMBER is then detailed. We showed that the atmospheric refraction becomes predominant over the atmospheric turbulence for some zenith angles z and spectral conditions: for z larger than 30° in J-band for example. The study of the optical system showed that it allows to achieve the required instrumental performance in terms of throughput in J- and H-bands. First observations in J-band of a bright star, alpha Cir star, at more than 30° from zenith clearly showed the gain to control the atmospheric refraction in a single mode instrument, and validated the operating law

Sensor Integration for Low-Cost Crash Avoidance

This report is a summary of the development of sensor integration for low-cost crash avoidance for over-land commercial trucks. The goal of the project was to build and test a system composed of low-cost commercially available sensors arranged on a truck trailer to monitor the environment around the truck. The system combines the data from each sensor to increase the reliability of the sensor using a probabilistic data fusion approach. A combination of ultrasonic and magnetoresistive sensors was used in this study. In addition, Radar and digital imaging were investigated as reference signals and possible candidates for additional sensor integration. However, the primary focus of this work is the integration of the ultrasonic and magnetoresistive sensors. During the investigation the individual sensors were evaluated for their use in the system. This included communication with vendors and lab and field testing. In addition, the sensors were modeled using an analytical mathematical model to help understand and predict the sensor behavior. Next, an algorithm was developed to fuse the data from the individual sensors. A probabilistic approach was used based on Bayesian filtering with a prediction-correction algorithm. Sensor fusion was implemented using joint a probability algorithm. The output of the system is a prediction of the likelihood of the presence of a vehicle in a given region near the host truck trailer. The algorithm was demonstrated on the fusion of an ultrasonic sensor and a magnetic sensor. Testing was conducted using both a light pickup truck and also with a class 8 truck. Various scenarios were evaluated to determine the system performance. These included vehicles passing the host truck from behind and the host truck passing vehicles. Also scenarios were included to test the system at distinguishing other vehicles from objects that are not vehicles such as sign posts, walls or railroads that could produce electronic signals similar to those of vehicles and confuse the system. The test results indicate that the system was successful at predicting the presence and absence of vehicles and also successful at eliminating false positives from objects that are not vehicles with overall accuracy ranging from 90 to 100% depending on the scenario. Some additional improvements in the performance are expected with future improvements in the algorithm discussed in the report. The report includes a discussion of the mapping of the algorithm output with the implementation of current and future safety and crash avoidance technologies based on the level of confidence of the algorithm output and the seriousness of the impending crash scenario. For example, irreversible countermeasures such as firing an airbag or engaging the brakes should only be initiated if the confidence of the signal is very high, while reversible countermeasures such as warnings to the driver or nearby vehicles can be initiated with a relatively lower confidence. The results indicate that the system shows good potential as a low cost alternative to competing systems which require multiple, high cost sensors. Truck fleet operators will likely adopt technology only if the costs are justified by reduced damage and insurance costs, therefore developing an effective crash avoidance system at a low cost is required for the technology to be adopted on a large scale

Enhanced Vehicle Identification Utilizing Sensor Fusion and Statistical Algorithms

Several studies in the area of vehicle detection and identification involve the use of probabilistic analysis and sensor fusion. While several sensors utilized for identifying vehicle presence and proximity have been researched, their effectiveness in identifying vehicle types has remained inadequate. This study presents the utilization of an ultrasonic sensor coupled with a magnetic sensor and the development of statistical algorithms to overcome this limitation. Mathematical models of both the ultrasonic and magnetic sensors were constructed to first understand the intrinsic characteristics of the individual sensors and also to provide a means of simulating the performance of the combined sensor system and to facilitate algorithm development. Preliminary algorithms that utilized this sensor fusion were developed to make inferences relating to vehicle proximity as well as type. It was noticed that while it helped alleviate the limitations of the individual sensors, the algorithm was affected by high occurrences of false positives. Also, since sensors carry only partial information about the surrounding environment and their measured quantities are partially corrupted with noise, probabilistic techniques were employed to extend the preliminary algorithms to include these sensor characteristics. These statistical techniques were utilized to reconstruct partial state information provided by the sensors and to also filter noisy measurement data. This probabilistic approach helped to effectively utilize the advantages of sensor fusion to further enhance the reliability of inferences made on vehicle identification. In summary, the study investigated the enhancement of vehicle identification through the use of sensor fusion and statistical techniques. The algorithms developed showed encouraging results in alleviating the occurrences of false positive inferences. One of the several applications of this study is in the use of ultrasonic-magnetic sensor combination for advanced traffic monitoring such as smart toll booths

IMECE2011-63553 APPLICATION OF FINITE STRIP METHOD IN VEHICLE DESIGN PART 2 OF 2: POST BUCKLING ANALYSIS OF THIN WALLED STRUCTURES

ABSTRACT Thin walled parts of high strength steel, under compressive loads are likely to buckle locally, and then depending on geometry and material properties the section may continue to carry additional load. For the post buckling conditions the deformations are large but finite. Therefore we need to consider geometrical non linearity in the calculations. In this paper we are extending the linear finite strip element formulation to include geometrical non linearity. Method to derive secant and tangent stiffness matrix for non linear finite strip element is developed and then the element formulation is verified for inplane and center load on a plate using Newton Raphson solver. The new non linear finite strip element can be useful in estimating maximum load capacity (including post buckling) of thin walled structures from 2D data

Performance investigation of reciprocating pump running with organic fluid for organic Rankine cycle

International audienceOrganic Rankine cycles (ORC) are used to convert lowgrade heat sources into power. Current research and development investigate small scale and variable heat sources application such as waste heat recovery. Many experimental data on ORC are available. Feed-pump performances achieved are lower than expected and some authors reported cavitation issue. Pump performance has a non-negligible impact over the ORC performance, especially for transcritical cycles. Operations of diaphragm pumps in three different test benches with different fluid and pump size are analyzed. A semi-empirical model of the pump power chain is proposed and validated. Energetic analysis show highlevel of losses in the variable speed drive and electric motor, mainly due to design oversizing. Then a model and analysis of reciprocating pump volumetric efficiency is proposed, taking into account fluid properties. Finally, cavitation limits in different conditions are calculated. Required Net Positive Suction Head (NPSHr) calculated for R134a are found to be in accordance with manufacturer limits for water. Pump vibration sensor could be used for cavitation monitoring. This work gives information for ORC feed-pump simulation, design and operation