Particle-Filter-Based Intelligent Video Surveillance System

In this study, an intelligent video surveillance (IVS) system is designed based on the particle filter. The designed IVS system can gather the information of the number of persons in the area and hot spots of the area. At first, the Gaussian mixture background model is utilized to detect moving objects by background subtraction. The moving object appearing in the margin of the video frame is considered as a new person. Then, a new particle filter is assigned to track the new person when it is detected. A particle filter is canceled when the corresponding tracked person leaves the video frame. Moreover, the Kalman filter is utilized to estimate the position of the person when the person is occluded. Information of the number of persons in the area and hot spots is gathered by tracking persons in the video frame. Finally, a user interface is designed to feedback the gathered information to users of the IVS system. By applying the proposed IVS system, the load of security guards can be reduced. Moreover, by hot spot analysis, the business operator can understand customer habits to plan the traffic flow and adjust the product placement for improving customer experience

Minimization procedure of experimental tests for calibration purposes, within HVAC&R energy efficiency framework

Simulation models and predictive tools need to be fast, accurate and robust at the same time. The models that have to provide numerical solutions under transient conditions for a long period of time need to be simple with the aim of minimizing the time respond, without losing the accuracy. Thus, previous experimental data and a calibration methodology are necessary to assure this objective, both are strictly necessary to reproduce the behaviour with accuracy expected. Consequently, even accurate information (e.g. look-up tables) for HVAC&R components (e.g. heat exchangers, fan/compressor, auxiliary elements, etc.) is known and all coupling system is developed, the minimization of experimental tests for calibration purposed based scattered data interpolation is now an important aspect, which looks for reducing the quantity of experiments necessary to assure the accuracy expected from an optimization point of view. The present work shows an optimization procedure based on test number minimization according detailed error comparison against existing previous data. Illustrative results for a specific component are presented highlighting test number reduction without losing accuracy.This project has received funding from the Clean Sky 2 Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 755517.Peer ReviewedPostprint (published version

The application of a new PID autotuning method for the steam/water loop in large scale ships

In large scale ships, the most used controllers for the steam/water loop are still the proportional-integral-derivative (PID) controllers. However, the tuning rules for the PID parameters are based on empirical knowledge and the performance for the loops is not satisfying. In order to improve the control performance of the steam/water loop, the application of a recently developed PID autotuning method is studied. Firstly, a 'forbidden region' on the Nyquist plane can be obtained based on user-defined performance requirements such as robustness or gain margin and phase margin. Secondly, the dynamic of the system can be obtained with a sine test around the operation point. Finally, the PID controller's parameters can be obtained by locating the frequency response of the controlled system at the edge of the 'forbidden region'. To verify the effectiveness of the new PID autotuning method, comparisons are presented with other PID autotuning methods, as well as the model predictive control. The results show the superiority of the new PID autotuning method

First order plus frequency dependent delay modeling : new perspective or mathematical curiosity?

The first-order-plus-dead-time model (FOPDT) is a popular simplified representation of higher order dynamics. However, a well known drawback is the rapid decrease of the frequency response accuracy with increasing process order. This especially applies to the higher frequency range. Literature offers solutions by extending this three parameter model with more parameters. Here, a fractional dead time is proposed. As such, a Frequency-Dependent Delay (FDD) is introduced, which offers a better approximation. As the fractional-order term introduces nonlinear coupling between the phase and the magnitude of the process, the fitting of the function becomes an iterative process, so a constrained multi-objective optimization is needed. This novel model, first-order-plus-frequency-dependent-delay or FOPFDD is fitted on a real electrical ladder network of resistors and capacitors of four and eight parts. The classic model, which is clearly a special case of the new model, is outperformed in the entire bandwidth

Experimental testing of a modular flexible actuator based on sma wires

A flexible finger made up of three actuator modules based on shape memory wires (SMA) is experimentally studied in this research. A module is composed by few simple components: a plastic body and SMA wires. The body is a thin cylinder with a lower and upper base and two intermediate disks. Three equidistant SMA wires are longitudinally placed and allow the module to bend in any direction when one or more wires are actuated. The motion of the module is performed with the heating and cooling of the wire and the central rod exerts bias force, necessary to the stretching of the wire to the original length. Two test benches were built to perform both positioning tests and force tests. To evaluate the actuator workspace different tests were performed, with different power supply, heating and cooling time, actuation sequence. Force tests were performed with different distance between the undeformed finger and the obstacle. The results achieved with this first prototype are encouraging since the finger shows stable and correct operation. The planar projection of the workspace is a circle of about 30-40 mm of radius and exerted force is similar to mathematical model results (about 1 N at 5 mm). These results are encouraging, even though, probably due to manufacturing imperfections and frictions, the movement is not very regular along the various directions

Flying Free: A Research Overview of Deep Learning in Drone Navigation Autonomy

With the rise of Deep Learning approaches in computer vision applications, significant strides have been made towards vehicular autonomy. Research activity in autonomous drone navigation has increased rapidly in the past five years, and drones are moving fast towards the ultimate goal of near-complete autonomy. However, while much work in the area focuses on specific tasks in drone navigation, the contribution to the overall goal of autonomy is often not assessed, and a comprehensive overview is needed. In this work, a taxonomy of drone navigation autonomy is established by mapping the definitions of vehicular autonomy levels, as defined by the Society of Automotive Engineers, to specific drone tasks in order to create a clear definition of autonomy when applied to drones. A top–down examination of research work in the area is conducted, focusing on drone navigation tasks, in order to understand the extent of research activity in each area. Autonomy levels are cross-checked against the drone navigation tasks addressed in each work to provide a framework for understanding the trajectory of current research. This work serves as a guide to research in drone autonomy with a particular focus on Deep Learning-based solutions, indicating key works and areas of opportunity for development of this area in the future