Real-time Prototype System Research Articles

An Energy Efficient Architecture for Furnace Monitor and Control in Foundry Based on Industry 4.0 Using IoT

The global standards in the field of industrial automation are maintained in industries by completely digitizing their manufacturing process with industry 4.0 standard. Internet of Things (IoT) enables the conservation of cultural heritage with proper assistance on data management on the data collected from the sensors. However, energy efficient conservation is required to monitor the IoT sensors in order to deal with building a better infrastructure. In this paper, we develop a bio-inspired algorithm which can automate the entire furnace monitoring and controlling system in order to eliminate the human intervention involved in the physical process. The algorithm is blended as a web-based remote application for the better control of the tasks involved, energy utilized, and its subsequent log-report maintenance. The entire system employs Wi-Fi communication for data transfer from device to cloud where the stored data including temperature log, forth coming schedule, and process graphic are maintained by the proposed algorithm to predict the machine failure at an earlier stage. The real-time prototype system is supported by a heat treatment process that is completely automated using IoT to monitor and maintain the temperature during the production of metal casting process.

A Negative Imaginary Theory-based Controller Synthesis for Vibration Control of a Piezoelectric Tube Scanner

In this paper, a data-driven controller is synthesised for systems with negative imaginary (NI) properties such as the piezoelectric tube scanner (PTS) of an atomic force microscopy (AFM). The scanning speed of an AFM is limited by the dynamic behaviours of its scanning unit. The controller aims to damp vibrations, increase the closed-loop bandwidth and track reference signals with high accuracy. The measured frequency response of the PTS is used to calculate the controller frequency response at each frequency by minimising a cost function. The data-driven control optimisation problem is constrained by NI properties to guarantee that the controller is stable and identifiable. The designed controller is implemented on the AFM using a dSPACE ds1103 real-time prototyping system. Experimental results show that the controller is able to significantly damp the resonances in the scanner’s lateral axes, provide a high-bandwidth closed-loop system and allow reference signal tracking.

Higher-order differential feedback control of a flexible-joint manipulator

This paper presents a new control scheme for a flexible-joint manipulator using a higher-order differential feedback controller (HODFC). Two higher-order differential operators were designed and used to perform observations of both the reference input and the output of the manipulator, together with the requisite state derivatives. An error-based state-space model was then derived from the observed states. A pole-placement procedure with filtering was then used to drive the system error to zero. Practical controller implementation was carried out using the dSPACE real-time prototyping system. For the comparative validation of the performance of the HODFC with respect to a classical proportional-integral and proportional-integral-derivative (PID) controller, several experiments were undertaken. In these experiments, the step input, sine waves, kane trajectories, and external disturbances were applied to the controlled flexible-joint manipulator. The results showed that the HODFC controller eliminated disturbances within one second of occurrence, and produced superior kane trajectory tracking. Moreover, based on the root-mean-square tracking error criterion, the HODFC was observed to track both the sine and kane function trajectories with one-fourth the tracking error obtained with classical PID control.

On the Hardware/Software Design and Implementation of a High Definition Multiview Video Surveillance System

This paper proposes a distributed architecture for high definition multiview video surveillance system. It adopts a modular design where single view/stereo intelligent internet protocol (IP)-based video surveillance cameras are connected to a front-end field programmable gate array (FPGA) board(s) which are connected to a back-end local video server through the IP network. The data intensive video analytics (VA) algorithms such as background modeling, connected component labeling and single view object tracking are implemented in the FPGA using an efficient fix-point based architecture. Each back-end video server is equipped with a storage and graphics processing units for supporting high-level VA and other processing algorithms such as video decompression/display, mean depth estimation and consistent labeling. A real-time prototype system was constructed to illustrate the architecture and VA algorithms involved. Satisfactory results were obtained for both publicly available data set and real surveillance video data.

Tracking Multiple Fishes Using Colour Changes Identification and Enhanced Object Tracking Algorithm

Tracking multiple fishes using computational methods have become a research endeavor among researchers. Different concepts have been taken such as installing water sensors and video cameras to identify movement speed, colours, shapes and swimming patterns displayed by the fishes. In this research, an enhanced algorithm consisting of motion detection algorithm and condensation algorithm is proposed. This algorithm is further integrated with colour changes identification technique which considers the changes in colour on fishes. This is to identify overlapping fishes and to detect the distance between the camera and the fishes in the water. In our case study, a cultured fish tank installed with water sensors to monitor water pH, dissolved oxygen and temperature is set up together with two network cameras. Koi fishes are chosen due to their active swimming behaviour, variety of colours and easy-to-adapt habitat in the water. A real-time prototype system which models the fish swimming pattern consisting of the enhanced algorithm and the colour changes identification is developed.

Real-Time Vision and Speech Driven Avatars for Multimedia Applications

Recent progress in advanced video communication services and multimedia applications is grounded on novel human machine interfaces, improved usability, and user friendliness driven by user centric research and development. In this paper, we describe a complete system concept and algorithmic details of an example application within this area. The key features of the system are vision and speech based interfaces, which are used to animate an avatar for an audio-visual representation of a communication partner. The system is applied in two application scenarios, namely video chat and customer care services. Both applications are mass-market oriented and therefore careful design and development of robust and supporting user interfaces are required. The presented approach is integrated into a complete real-time prototype system, which is permanently demonstrated in the showcase at the head quarter of Deutsche Telekom, Bonn, Germany.

Toward a decision-theoretic framework for affect recognition and user assistance

There is an increasing interest in developing intelligent human–computer interaction systems that can fulfill two functions—recognizing user affective states and providing the user with timely and appropriate assistance. In this paper, we present a general unified decision-theoretic framework based on influence diagrams for simultaneously modeling user affect recognition and assistance. Affective state recognition is achieved through active probabilistic inference from the available multi modality sensory data. User assistance is automatically accomplished through a decision-making process that balances the benefits of keeping the user in productive affective states and the costs of performing user assistance. We discuss three theoretical issues within the framework, namely, user affect recognition, active sensory action selection, and user assistance. Validation of the proposed framework via a simulation study demonstrates its capability in efficient user affect recognition as well as timely and appropriate user assistance. Besides the theoretical contributions, we build a non-invasive real-time prototype system to recognize different user affective states (stress and fatigue) from four-modality user measurements, namely physical appearance features, physiological measures, user performance, and behavioral data. The affect recognition component of the prototype system is subsequently validated through a real-world study involving human subjects.