Search Results (10)

The widespread availability of artificial intelligence (AI) tools has facilitated the development of complex, high-performance applications across a broad range of domains. Among these, processes related to the surveillance and assisted verification of indoor environments have garnered significant interest. This paper presents the implementation, testing, and validation of an autonomous mobile platform designed for the intelligent and flexible inspection of such spaces. The artificial vision system, the main component on which the study focuses, was built using a Raspberry Pi 5 development module supplemented by a Raspberry Pi AI Kit to enable hardware acceleration for image recognition tasks using AI techniques. Some of the most recognized neural network models were evaluated in line with the application’s specific requirements. Utilizing transfer learning techniques, these models were further developed and trained with additional image datasets tailored to the inspection tasks. The performance of these networks was then tested and validated on new images, facilitating the selection of the model with the best results. The platform’s flexibility was ensured by mounting the artificial vision system on a mobile structure capable of autonomously navigating indoor environments and identifying inspection points, markers, and required objects. The platform could generate reports, make decisions based on the detected conditions, and be easily reconfigured for alternative inspection tasks. Finally, the intelligent and flexible inspection system was tested and validated for its deep learning-based vision system performance. Full article

The increasing volatility of the markets and the growing demand for customized products are challenges for future production to ensure maximum flexibility and adaptability. This paper introduces software-defined value stream process systems (SVPSs), a novel approach that extends the concept of software-defined manufacturing into autonomous, reconfigurable production systems. SVPSs establish a cyber–physical chain that links product features to requirements, enabling their fulfillment through modular machine and process hardware. A modular construction kit of individually combinable hardware and associated software modules is presented. These modules are coordinated via a digital process chain that enables holistic simulations, optimizations, and planning based on a Digital Twin. This system is based on software-defined manufacturing but extends it into autonomous reconfigurable machines. By enabling virtual planning and commissioning of entire production lines, the SVPS concept provides an efficient and adaptable solution to meet the demands of volatile markets. Full article

Convolutional neural networks (CNNs) are increasingly recognized as an important and potent artificial intelligence approach, widely employed in many computer vision applications, such as facial recognition. Their importance resides in their capacity to acquire hierarchical features, which is essential for recognizing complex patterns. Nevertheless, the intricate architectural design of CNNs leads to significant computing requirements. To tackle these issues, it is essential to construct a system based on field-programmable gate arrays (FPGAs) to speed up CNNs. FPGAs provide fast development capabilities, energy efficiency, decreased latency, and advanced reconfigurability. A facial recognition solution by leveraging deep learning and subsequently deploying it on an FPGA platform is suggested. The system detects whether a person has the necessary authorization to enter/access a place. The FPGA is responsible for processing this system with utmost security and without any internet connectivity. Various facial recognition networks are accomplished, including AlexNet, ResNet, and VGG-16 networks. The findings of the proposed method prove that the GoogLeNet network is the best fit due to its lower computational resource requirements, speed, and accuracy. The system was deployed on three hardware kits to appraise the performance of different programming approaches in terms of accuracy, latency, cost, and power consumption. The software programming on the Raspberry Pi-3B kit had a recognition accuracy of around 70–75% and relied on a stable internet connection for processing. This dependency on internet connectivity increases bandwidth consumption and fails to meet the required security criteria, contrary to ZYBO-Z7 board hardware programming. Nevertheless, the hardware/software co-design on the PYNQ-Z2 board achieved an accuracy rate of 85% to 87%. It operates independently of an internet connection, making it a standalone system and saving costs. Full article

This paper presents a novel frequency reconfigurable antenna design for sub-6 GHz applications, featuring a unique combination of antenna elements and control mechanisms. The antenna is composed of an outer split-ring resonator loaded with an inner spiral resonator, which can be adjusted through the remote control of PIN diode or Single Pole Double Throw (SPDT) switches. The compact antenna, measuring 22 × 16 × 1.6 mm³, operates in broadband, or tri-band mode depending on the ON/OFF states of switches. The frequency reconfigurability is achieved using two BAR64−02V PIN diodes or two CG2415M6 SPDT switches acting as RF switches. SPDT switches are controlled remotely via Arduino unit. Additionally, the antenna demonstrates an omni-directional radiation pattern, making it suitable for wireless communication systems. Experimental results on an FR-4 substrate validate the numerical calculations, confirming the antenna’s performance and superiority over existing alternatives in terms of compactness, wide operating frequency range, and cost-effectiveness. The proposed design holds significant potential for applications in Wi-Fi (IEEE 802.11 a/n/ac), Bluetooth (5 GHz), ISM (5 GHz), 3G (UMTS), 4G (LTE), wireless backhaul (4G and 5G networks), WLAN (IEEE 802.11 a/n/ac/ax), 5G NR n1 band, and Wi-Fi access points due to its small size and easy control mechanism. The antenna can be integrated into various devices, including access points, gateways, smartphones, and IoT kits. This novel frequency reconfigurable antenna design presents a valuable contribution to the field, paving the way for further advancements in wireless communication systems. Full article

Nowadays, the demand for personalized goods is increasing, with small batches of customized products. Companies are asked to cope with this need to be more competitive; thus, it is crucial to optimally set up the production process to cope with the demand. Among the products composed of several parts, sales kits occupy a significant role. Sales kits are sets of different components, supplied as a single unit. Automation is usually used to reduce the unit direct production costs for assembled products, and this is especially true for kitting since it has minimum added value, compared to other technologies. The wide range of components leads to frequent reconfiguration of the feeding devices between different products, increasing the setup time. The aim of this work is to provide a model that minimizes the setup times of automatic kitting systems when working with a high variety of products. To reach this goal, we propose to apply the traveling salesman problem (TSP) to the production process by integrating a multi-clustering model, thus increasing its appeal to several applications. This method is applied both to simulations and to a real case study, and proves to be able to provide a good solution in a reasonable time. Full article

Gamma correction is a common image processing technique that is common in video or still image systems. However, this simple and efficient method is typically expressed using the power law, which gives rise to practical difficulties in designing a reconfigurable hardware implementation. For example, the conventional approach calculates all possible outputs for a pre-determined gamma value, and this information is hardwired into memory components. As a result, reconfigurability is unattainable after deployment. This study proposes using the Taylor series to approximate gamma correction to overcome the aforementioned challenging problem, hence, facilitating the post-deployment reconfigurability of the hardware implementation. In other words, the gamma value is freely adjustable, resulting in the high appropriateness for offloading gamma correction onto its dedicated hardware in system-on-a-chip applications. Finally, the proposed hardware implementation is verified on Zynq UltraScale+ MPSoC ZCU106 Evaluation Kit, and the results demonstrate its superiority against benchmark designs. Full article

Finding context, examples, and ample hands-on experimentation is fundamental for understanding complex ideas in subjects such as science and math. Recent popularity of competitive robotics has become a catalyst in the development of DIY and hobby kits. Manufacturers have made available easy to work, re-configurable, and functional, structural elements as well as control electronics. Additionally, extensive participation from the open-source software community is providing cutting edge and effective software. Despite all the right ingredients, competitive robotics continues to be unregulated and non-standardized. Additionally, in absence of regulations and standards, the organizers, suppliers, educators, and participants are left to their own means and resources that necessarily may not align with systematic learning. The cost of approved competitive kits as well as field kits becomes inhibitive for students from poorer communities. This paper surveys a wide range of competitive robotics avenues available to school-age students. A survey with various stake holders including participants, mentors, referees, and organizers is done and findings are included. A path for standardizing competitive robotics within the framework of the World Robotics League is found to be an effective tool to train the students. A description of the World Robotics League framework and initial findings are reported. Full article

Assembly kitting lines typically deal with components that present different quantities in the final kit. Re-configurable feeders are not advisable for low quantity components since this solution leads to high inefficiency, due to the time required for retooling and for the feeding rate unbalance between the components. On the other hand a fully flexible feeder can increase the flexibility of the system at the cost of reducing the throughput. An assembly kitting problem was therefore addressed in different ways for low quantity components and high quantity components, studying the two different subsystems that compose a hybrid flexible assembly system. To optimize the re-configurable feeders, which supply the high quantity components, the opening sequence of a system composed by several hoppers was analyzed. We propose a solution which replaces the weighing device with a vision inspection system, showing its impact on the productivity of the line. A model coded into a Matlab script was developed to perform the optimization of the system and understand its behavior. Furthermore a fully flexible assembly system was developed in the laboratory in order to test the kitting of the low quantity components with the proposed subsystem. Finally the Overall Equipment Effectiveness of the line was calculated to evaluate the possible improvements obtained by the proposed solution. Full article

As an important national strategy infrastructure, the Space Information Network (SIN) is a powerful platform for future information support. The architecture model of the SIN is of great significance to the construction and development of the SIN. For the problems related to the poor versatility, portability, and recombination of the existing architecture modeling methods of the SIN, in this paper, based on the Data as a Center (DaaC) modeling idea, we propose a reconfigurable model of the task-oriented architecture of the SIN. Combining with the typical characteristics of the SIN, and drawing on the advantages of activity-based flexibility, service-oriented integrity, and object-oriented reusability, we propose a DaaC modeling idea with space data. The DaaC modeling idea can solve the problems related to the poor versatility and portability of the SIN architecture. Based on the DaaC idea, we analyze the requirements of the task-oriented architecture, and define the basic concepts of SIN reorganization, including the reconfigurable target, reconfigurable scheme, and reconfigurable SIN. We establish the reconfigurable principles of loose coupling, compatibility, isolation, and deconstruction. Meanwhile, we analyze the realization mechanism and methods of the task-oriented reconfigurable model of the SIN based on DaaC. Finally, we take a typical SIN as an example, and make a case study on land-based anti-missile combat activities as the task background based on the DoDAF2.0 (Department of Defense Architectural Framework 2.0) framework and the STK (Satellite Tool Kit) simulation platform. The case results are consistent with the theoretical expectation, and it verifies the feasibility and effectiveness of our proposed method. Full article

This paper presents an effort to revitalize a large introductory engineering course for incoming freshman students that teaches them analytical design through a project-based curriculum. This course was completely transformed from a seminar-based to a project-based course that integrates hands-on experimentation with analytical work. The project is centered on a reconfigurable trebuchet kit that student groups assemble and work to identify design decisions that will maximize projectile launch distance. Challenges include streamlining the project experience for the large enrollment (up to 148 students) with limited contact hours, and helping students fuse hands-on experiences with quantitative engineering analysis. A mixed-methods approach supported the claim that the curriculum improved the students’ engineering judgment and demonstrated to students the value of engineering analysis and mathematical models in practical engineering design. A rigorous statistical analysis of student trebuchet launch performance at different course stages is included. A qualitative assessment of student learning is derived through students’ reflection of their course experience. Comprehensive results comparing students’ design iterations versus algorithmic design optimization iterations provide important insights into student design intuition, paving the way for hybrid design education models that teach students how to combine human design intuition with quantitative design tools to design superior systems. Full article